ALBERT

Beschreibung: This paper presents a demand response (DR) framework that intertwines thermodynamic building models with a genetic algorithm (GA)-based optimization method. The framework optimizes heating/cooling schedules of end-users inside a business park microgrid with local distributed generation from renewable energy sources (DG-RES) based on two separate objectives: net load minimization and electricity cost minimization. DG-RES is treated as a curtailable resource in anticipation of future scenarios where the infeed of DG-RES to the regional distribution network could be limited. We test the DR framework with a case study of a refrigerated warehouse and an office building located in a business park with local PV generation. Results show the technical potential of the DR framework in harnessing the flexibility of the thermal masses from end-user sites in order to: (1) reduce the energy exchange at the point of connection; (2) reduce the cost of electricity for the microgrid end-users; and (3) increase the local utilization of DG-RES in cases where DG-RES exports to the grid are restricted. The results of this work can aid end-users and distribution network operators to reduce energy costs and energy consumption.

Beschreibung: In this paper, a full-color photovoltaic (PV) module, called the artist PV module, is developed by laser processes. A full-color image source is printed on the back of a protective glass using an inkjet printer, and a brightened grayscale mask is used to precisely define regions on the module where colors need to be revealed. Artist PV modules with 1.1 × 1.4 m2 area have high a retaining power output of 139 W and an aesthetic appearance making them more competitive than other building-integrated photovoltaic (BIPV) products. Furthermore, the installation of artist PV modules as curtain walls without metal frames is also demonstrated. This type of installation offers an aesthetic advantage by introducing supporting fittings, originating from the field of glass technology. Hence, this paper is expected to elevate BIPV modules to an art form and generate research interests in developing more functional PV modules.

Beschreibung: This paper pays attention to magnetic flux linkage optimization of a direct-driven surface-mounted permanent magnet synchronous generator (D-SPMSG). A new compact representation of the D-SPMSG nonlinear dynamic differential equations to reduce system parameters is established. Furthermore, the nonlinear dynamic characteristics of new D-SPMSG equations in the process of varying magnetic flux linkage are considered, which are illustrated by Lyapunov exponent spectrums, phase orbits, Poincaré maps, time waveforms and bifurcation diagrams, and the magnetic flux linkage stable region of D-SPMSG is acquired concurrently. Based on the above modeling and analyses, a novel method of magnetic flux linkage optimization is presented. In addition, a 2 MW D-SPMSG 2D/3D model is designed by ANSYS software according to the practical design requirements. Finally, five cases of D-SPMSG models with different magnetic flux linkages are simulated by using the finite element analysis (FEA) method. The nephograms of magnetic flux density are agreement with theoretical analysis, which both confirm the correctness and effectiveness of the proposed approach.

Beschreibung: The construction of two marine bulk terminals in the Pacific Northwest region of the United States are currently under review and would open up additional thermal coal exports to Asia on the order of almost 100 million additional tonnes per year. The major exporters of coal to Asian markets include Indonesia and Australia. This life cycle analysis (LCA) seeks to understand the role of transportation and mining in the cradle-to-busbar environmental impacts of coal exports from the Powder River Basin (PRB) to Asian countries, when compared to the competitor countries. This LCA shows that: (1) the most significant greenhouse gas (GHG) impacts in the cradle-to-busbar life cycle of coal for power generation come from the combustion of coal in a power plant, even when 90% carbon capture is applied; (2) for non-GHG air impacts, power plant combustion impacts are less dominant and variations in upstream impacts (mining and transportation) are more important; and (3) when comparing impacts between countries, upstream impacts vary for both GHG and non-GHG results, but conclusions that rank countries cannot be made. Future research should include expansion to include non-air impacts, potential consequential effects of coal exports, and a better understanding around the characterization of non-GHG ocean transport impacts.

Beschreibung: Recently, Vernier permanent magnet (VPM) machines, one special case of magnetic flux-modulated (MFM) machines, benefiting from their compact, simple construction and low-speed/ high-torque characteristics, have been receiving increasing interest. In this paper, the Vernier structure is integrated with an axial-flux PM machine to obtain the magnetic gear effect and produce an improved torque density for direct-drive wind power generation application. Another advantage of the proposed machine is that the stator flux rotating speed can be relatively high when the shaft speed is low. With this benefit, sensorless control strategy can be easily implemented in a wide speed range. In this paper, an improved sliding mode observer (SMO) is proposed to estimate the rotor position and the speed of the proposed machine. With the estimated shaft speeds, the maximum power point tracking (MPPT) control strategy is applied to maximize the wind power extraction. The machine design and the sensorless MPPT control strategy are verified by finite element analysis and experimental verification.

Beschreibung: A fractional derivative system identification approach for modeling battery dynamics is presented in this paper, where fractional derivatives are applied to approximate non-linear dynamic behavior of a battery system. The least squares-based state-variable filter (LSSVF) method commonly used in the identification of continuous-time models is extended to allow the estimation of fractional derivative coefficents and parameters of the battery models by monitoring a charge/discharge demand signal and a power storage/delivery signal. In particular, the model is combined by individual fractional differential models (FDMs), where the parameters can be estimated by a least-squares algorithm. Based on experimental data, it is illustrated how the fractional derivative model can be utilized to predict the dynamics of the energy storage and delivery of a lithium iron phosphate battery (LiFePO 4 ) in real-time. The results indicate that a FDM can accurately capture the dynamics of the energy storage and delivery of the battery over a large operating range of the battery. It is also shown that the fractional derivative model exhibits improvements on prediction performance compared to standard integer derivative model, which in beneficial for a battery management system.

Beschreibung: In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

Beschreibung: This study contributes to the realization of intended nationally determined contributions (INDCs) by analyzing their implications for the energy production system and the economy, and determines the role of renewable energies (RE) in reducing the challenge of committing to the INDCs. The Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model was used to assess seven scenarios having the same socioeconomic development but different shares of RE in power generation. By comparing different relative reductions caused by the emission constraints vis-a-vis the business-as-usual (BaU) scenario, the mitigation costs can be estimated. Results show that the economic impact could be reduced by around 55% in terms of welfare loss (from 6.0% to 2.7%) and by around 36% in terms of gross domestic product (GDP) loss (from 3.4% to 2.1%) through the incorporation of high levels of renewable energy. Furthermore, the additional double deployment of wind and SPV to 5.4% and 12.0%, respectively, which currently comprise 43.1% of the renewable energies used in electricity generation, could reduce the GDP loss from 2.1% to 1.9% and reduce the welfare loss from 2.7% to 1.5% in order to achieve a 25.0% GHG emissions reduction. These losses are less than those in the pricing-only scenario (2.1% and 2.3%, respectively).

Beschreibung: The axial magnetic-field-modulated brushless double-rotor machine (MFM-BDRM) is a novel possible alternative power-split device for hybrid electric vehicles (HEVs). This paper proposes a two-dimensional (2-D) analytical method to predict the performance of the axial MFM-BDRM to reduce computing time. The computation is based on the solution of Laplace’s or Poisson’s equation with boundary conditions for each elementary rectangular region. By taking account of the existence of modulating ring and the stator slotting effect, the proposed model is able to calculate magnetic-field distribution with high accuracy. In order to assess the proposed method, the 2-D analytical and three-dimensional (3-D) finite element analysis (FEA) results have been compared, and good agreements have been achieved. As the analytical computation is much faster and more flexible, the proposed method can be used in the preliminary design process of the axial MFM-BDRM.

Beschreibung: A microgrid is a micro-power system composed of local distributed generators, energy storage systems, loads, and other components in a local power network. Because renewable energy sources show relatively large output power variation, the integration of distributed generators in a microgrid often requires the installation of a large-scale energy storage system. The energy storage system is connected to a local AC bus via the DC/AC converter with an output inductor-capacitor (LC) filter. The energy storage system power converters generally form the local AC bus voltage. This grid-forming operation requires fast and robust voltage control to properly maintain a stable energy flow and high power quality in the local AC bus. In this paper, two major voltage control schemes—double-loop control and direct voltage control—are analytically compared, and their effects on the power quality of the microgrid are illustrated. The dynamic performance is compared through simulations and experimental results.

Beschreibung: The UK is currently suffering great overheating issues in summer, especially in residential buildings where no air-conditioning has been installed. This overheating will seriously affect people’s comfort and even health, especially for elderly people. Phase change materials (PCMs) have been considered as a useful passive method, which absorb excessive heat when the room is hot and release the stored heat when the room is cool. This research has adopted a simulation method in DesignBuilder to evaluate the effectiveness of using PCMs to reduce the overheating issues in UK residential applications and has analyzed potential factors that will influence the effectiveness of overheating. The factors include environment-related (location of the building, global warming/climate change) and construction-related (location of the PCM, insulation, heavyweight/lightweight construction). This research provides useful evidence about using PCMs in UK residential applications and the results are helpful for architects and engineers to decide when and where to use PCMs in buildings to maintain a low carbon lifestyle.

Beschreibung: Micro (0.5–10 kW) organic Rankine cycle (ORC) power systems are nowadays considered for domestic power generation. Selection of a suitable expander is one of the most important problems connected with the domestic ORC system design. Volumetric machines or micro-turbines can be adopted as an expander in domestic ORC systems. Scroll and screw expanders are a common choice and were successfully applied in different small- and micro-power applications. However, micro-turbines as well as scroll and screw expanders are mechanically complicated and expensive. An alternative are rotary-vane machines, which are simple and cheap compared to micro-turbines. This paper documents a study providing the experimental and numerical analyses on the rotary vane expander operating conditions in a micro-ORC system. A test-stand was designed and set up and a series of experiments was performed using the test-stand. Results of these experiments were further used as an input to numerical simulations of an expander operation. In order to simulate the expander operating conditions, a three-dimensional numerical model has been prepared. The analysis presented in this paper indicates that a properly designed multi-vane expander is a cheap and mechanically simple alternative to other expansion devices proposed for domestic ORC systems.

Beschreibung: Plate Fin Heat Sinks (PFHS) are among the simplest and most widespread devices for electronics cooling. Because of the many design parameters to be considered, developing both cost and thermal effective PFHS is a critical issue. Here, a novel thermal model of PFHS is presented. The model has a broad field of applicability, being comprehensive of the effects of flow bypass, developing boundary layers, fin efficiency and spreading resistance. Experiments are then carried out to validate the proposed thermal model, and its good accuracy is demonstrated. Finally, an optimization methodology based on genetic algorithms is proposed for a cost-effective selection of the design parameters of PFHS, which is particularly effective with semi-active configurations. Such an optimization methodology is then tested on a commercial heat sink, resulting in a possible 53% volume reduction at fixed thermal performances.

Beschreibung: Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy (RE) has gained significant attention in the last few years, contributing to the deployment, management and optimization of RE systems. The main objective of this paper is to review the most important classification algorithms applied to RE problems, including both classical and novel algorithms. The paper also provides a comprehensive literature review and discussion on different classification techniques in specific RE problems, including wind speed/power prediction, fault diagnosis in RE systems, power quality disturbance classification and other applications in alternative RE systems. In this way, the paper describes classification techniques and metrics applied to RE problems, thus being useful both for researchers dealing with this kind of problem and for practitioners of the field.

Beschreibung: The day-ahead electricity market is closely related to other commodity markets such as the fuel and emission markets and is increasingly playing a significant role in human life. Thus, in the electricity markets, accurate electricity price forecasting plays significant role for power producers and consumers. Although many studies developing and proposing highly accurate forecasting models exist in the literature, there have been few investigations on improving the forecasting effectiveness of electricity price from the perspective of reducing the volatility of data with satisfactory accuracy. Based on reducing the volatility of the electricity price and the forecasting nature of the radial basis function network (RBFN), this paper successfully develops a two-stage model to forecast the day-ahead electricity price, of which the first stage is particle swarm optimization (PSO)-core mapping (CM) with self-organizing-map and fuzzy set (PCMwSF), and the second stage is selection rule (SR). The PCMwSF stage applies CM, fuzzy set and optimized weights to obtain the future price, and the SR stage is inspired by the forecasting nature of RBFN and effectively selects the best forecast during the test period. The proposed model, i.e., CM-PCMwSF-SR, not only overcomes the difficulty of reducing the high volatility of the electricity price but also leads to a superior forecasting effectiveness than benchmarks.

Beschreibung: In order to evaluate and control the seismic effect of blasting, as well as its planning, it is required to determine the soil oscillation law, with the strike/mining facilities to be protected. One of the most commonly used equations is that of M.A. Sadovskii, defining the law of alteration in the oscillation velocity of the soil depending on distance, the explosive amount, and conditions of blasting and geologic characteristics of the soil; all of this being determined on the basis of test blasting for the specific work environment. In the Sadovskii equation two parameters, K and n appear and they are conditioned both by rock mass characteristics and blasting conditions. The practical part of this study includes experimental investigations performed in the Veliki Krivelj Open Pit in the Bor District located in Eastern Serbia and investigations carried out during mass mining in the Kovilovača Open Pit near Despotovac, Eastern Serbia. Thus this paper offers several modes for determination of parameters K and n in the Sadovskii equation. To determine the parameters in the Sadovskii formula, in addition to the usual least square method, two more new models were applied. In the models the parameters K and n were determined by applying the quotient of the relative growth of oscillation velocities and reduced distances for Model 2. The link between the parameters K and n is determined by applying the trapezoidal formula for finding the value of definite integral for Model 3. In doing so, it was noted that all three models can be used to calculate the oscillation velocity of the rock mass.

Beschreibung: Carbon emissions are the major cause of the global warming; therefore, the exploration of carbon emissions reduction potential is of great significance to reduce carbon emissions. This paper explores the potential of carbon intensity reduction in Beijing in 2020. Based on factors including economic growth, resident population growth, energy structure adjustment, industrial structure adjustment and technical progress, the paper sets 48 development scenarios during the years 2015–2020. Then, the back propagation (BP) neural network optimized by improved particle swarm optimization algorithm (IPSO) is used to calculate the carbon emissions and carbon intensity reduction potential under various scenarios for 2016 and 2020. Finally, the contribution of different factors to carbon intensity reduction is compared. The results indicate that Beijing could more than fulfill the 40%–45% reduction target for carbon intensity in 2020 in all of the scenarios. Furthermore, energy structure adjustment, industrial structure adjustment and technical progress can drive the decline in carbon intensity. However, the increase in the resident population hinders the decline in carbon intensity, and there is no clear relationship between economy and carbon intensity. On the basis of these findings, this paper puts forward relevant policy recommendations.

Beschreibung: There is considerable interest recently in by-products for application in green buildings. These materials are widely used as building envelope insulators or blocks. In this study, an experimental study was conducted to test stranded driftwood residues as raw material for possible thermo-acoustic insulation panel and environmentally sustainable brick. The thermal and acoustic characteristics of such a natural by-product were examined. Part of samples were mineralized by means of cement-based additive to reinforce the material and enhance its durability as well as fire resistance. Several mixtures with different sizes of ground wood chips and different quantities of cement were investigated. The thermo-acoustic in-lab characterization was aimed at investigating the thermal conductivity, thermal diffusivity, volumetric specific heat, and acoustic transmission loss. All samples were tested before and after mineralization. Results from this study indicate that it is possible to use stranded driftwood residues as building materials with competitive thermo-acoustic properties. In fact, the thermal conductivity was shown to be always around 0.07 W/mK in the unbound samples, and around double that value for the mineralized samples, which present a much higher volumetric specific heat (1.6 MJ/m3K) and transmission loss capability. The lignin powder showed a sort of intermediate behavior between the unbound and the mineralized samples.

Beschreibung: Micro energy grids have many merits and promising applications under the smart grid vision. There are demanding procedures for their optimal planning and performance enhancement. One of the key features of a micro energy grid is its ability to separate and isolate itself from the main electrical network to continue feeding its own islanded portion. In this paper, an optimal sizing and operation strategy for micro energy grids equipped with renewable and non-renewable based distributed generation (DG) and storage are presented. The general optimization objective is to define the best DG mix and energy storage units for self-sufficient micro energy grids. A multi-objective genetic algorithm (GA) was applied to solve the planning problem at a minimum optimization goal of overall cost (including investment cost, operation and maintenance cost, and fuel cost) and carbon dioxide emission. The constraints include power and heat demands constraints, and DGs capacity limits. The candidate technologies include CHPs (combined heat and power) with different characteristics, boilers, thermal and electrical storages, and renewable generators (wind and photovoltaic). In order to assess different configuration options and components sizes, several case studies for a typical micro energy grid have been presented.

Beschreibung: Along-track multichannel synthetic aperture radar is usually used to achieve ground moving target detection and imaging. Nevertheless, there is a design dilemma between azimuth high resolution and wide swath (HRWS). To solve this problem in HRWS mode, we introduce a virtual multichannel (VMC) scheme. For each virtual channel, the low real pulse repetition frequency (PRF) improves the ability of resolving range ambiguity for wide-swath, and the high virtual PRF improves the capability of resolving Doppler ambiguity for azimuth high resolution. For multiple virtual channels, strong ground clutter is eliminated by the joint VMC processing. Furthermore, a detailed signal model of a moving target in the virtual channel is given, and the special false-peak effect in the azimuthal image is analyzed. Moreover, we propose a novel ground moving target processing method based on the VMC scheme and the clutter suppression interferometry (CSI) technique, which is called VMC-CSI. The integration of detection, location, velocity estimation, and imaging for ground moving targets can be achieved. Accounting for the unresolved main peak and false peak for a moving target, in the VMC-CSI method, we adopt a two-step scheme to estimate the radial velocity and along-track velocity, namely, rough estimation and precise estimation. Meanwhile, considering the same interferometric phases of the main peak and the false peak, we use false peaks first for the robustness of initial azimuth location estimation and remove false peaks afterward. Numerical simulations are provided for testing the effect of the false peak and the effectiveness of VMC-CSI.

Beschreibung: This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations' canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumping can be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models.

Beschreibung: Multifrequency and multioffset ground-penetrating radar data acquisition modes are used to maximize the information content and parameter retrieval capabilities. However, they also increase the computational cost dedicated to the inversion procedure. In this paper, the impact of the number of frequencies and the multistatic configurations on the information retrieval capabilities is investigated through the response surface topographies of the objective functions. We resort to a full-wave-inversion procedure and a recently developed electromagnetic model which takes advantage of a closed-form solution of Maxwell's equations to describe the antenna–medium system. We show with numerical and laboratory experiments the possibility of reducing the number of frequencies from several hundreds to one or several tens of components without affecting the information retrieval capabilities. We also show through several scenarios that the presence of a perfect electrical conductor increases the number of frequencies required to ensure an acceptable retrieval of the subsurface properties whereas the conductivity of the first layer and the relative permittivity of the second layer do not affect it. The results highlight that information content analyses are important in order to study and optimize data acquisition and inversion procedures, and thereby the computation time.

Beschreibung: This paper addresses some important aspects for the spaceborne/stationary bistatic synthetic aperture radar (SAR) (SS-BiSAR) imaging with the transmitter, TerraSAR-X, operated in staring spotlight (ST) mode. With the large integration time reaching 7.5 s and the azimuth steering span reaching $pm 2.2^{0}$ , several significant effects occur, including troposphere delay, precision phase and time synchronization, the curved orbit effect, azimuth spectrum aliasing problem, and efficient frequency domain focusing algorithm. To circumvent the main effects, corresponding solutions are proposed, including a precise synchronization strategy with troposphere delay correction based on the direct signal from the transmitter and a modified and integrative bistatic polar format algorithm (PFA). This paper covers the theoretical development, implementation, and analysis of the SS-BiSAR PFA based on 2-D fast Gaussian gridding nonuniform fast Fourier transform with wavefront curvature correction. Furthermore, the high-resolution ST-mode SS-BiSAR image processed by the proposed algorithm is acquired, and the differences of scattering behaviors between monostatic and bistatic SAR images are analyzed in detail.

Beschreibung: The ground penetrating radar (GPR) is a popular and successful remote sensing modality that has been investigated for landmine detection. GPR offers excellent detection performance, but it is limited by a low rate of advance (ROA) due to its short sensing standoff distance. Standoff distance refers to the distance between the sensing platform and the location in front of the platform where the GPR senses the ground. Large standoff (high ROA) sensing modalities have been investigated as alternatives to the GPR, but they do not yet achieve comparable detection performance. This paper proposes a new sensor management approach, called multistate management (MSM), which combines large and short standoff sensors on the same platform in a way that leverages their respective advantages, yielding a system with better ROA and detection performance. MSM is more difficult to analyze than traditional systems because it allows sensor activity and system velocity to change over time. Therefore, a new probabilistic model based on queuing theory, called Q-MSM, is also proposed for analyzing and designing detection systems operating with MSM. Simulations were conducted using real field-collected data for a system with a large standoff forward-looking infrared camera and a GPR. The system is operated with MSM, and the results show that this leads to better ROA and detection performance than can be attained otherwise. Furthermore, the results show that Q-MSM can accurately predict the behavior of the MSM system, validating its utility for analyzing and designing such systems.

Beschreibung: The concept of simultaneous source has recently become of interest in seismic exploration, due to its efficient or economic acquisition or both. The blended data overlapped between shot records are acquired in simultaneous source acquisition. Separating the blended data and recovering the single-shot seismic signals (the recovery) are of great importance in the scenario of current workflows, which can be called seismic simultaneous source separation. In the context of general random time-dithering firing, we propose an alternative method to separate the blended data by combining patchwise dictionary learning with sparse inversion, in which the dictionary is directly learned from the measured blended data. Apart from the sparse coding used for the coefficients, an additional regularization term on the dictionary is particularly designed to remove the severe interference noise. The efficient and flexible alternating direction method of multipliers (ADMM) is used to update the dictionary in the used alternating optimization scheme. The results obtained from the synthetic and real examples reasonably suggest that the separated seismic signals by using dictionary learning are more accurate and robust compared with that using the fixed transform basis, such as the local discrete cosine transform. The learned dictionary tailors for the recovery and is similar to the local seismic waveform, which improves the sparsity of the recovery substantially and is highly advantageous for producing the promised results.

Beschreibung: This paper investigates the impact of the soil moisture distribution in the top layer on the accuracy of soil moisture retrieval by microwave remote sensing methods. We modeled soil emission at L-band by coherent and noncoherent models for the different moisture distributions in the top layer. As a result, it is found that, at high moisture gradients, the difference between average moisture within the sensing depth at L-band and the moisture retrievable from remote sensing data can be more than 20% in absolute terms. In addition, high differences between Soil Moisture and Ocean Salinity (SMOS) Level 2 data and the in situ measurements were revealed in cases of high gradients. Such high gradients may be observed during some time in the top layer of the drying soil after rainfall. These differences are significantly more than the accuracy declared by SMOS development team. We proposed a simple method that allows the assessment of the type of soil moisture profile by SMOS and Global Change Observation Mission‐Water “SHIZUKU” (GCOM-W1) satellites data. The procedure for simple processing of data of the two satellites is described. In addition, we compared the type of soil moisture profile retrieved from satellite data and the soil moisture profile found by in situ measurements.

Beschreibung: An iterative alternating direction method of multipliers (ADMM) is proposed for inverse finite-element–boundary-integral (FE–BI) problem with total variation (TV) regularization. The inverse FE–BI fits to a wide class of penetrable sensing applications, where this study specifically targets the problem of radio tomography of asteroid interior structure using orbiting spacecraft. The TV regularizer enforces sparsity on the gradient of reconstructed permittivity, which agrees well with the “piecewise constant” reality of “rocks embedded in soil” scenario and, meanwhile, addresses the inherent ill-posedness. For large-scale asteroid problems, the distributed ADMM algorithm is adapted to solve the linear TV inversion at each iteration. The 2-D inversion is validated with the Fresnel Institute measurement data. Simulated cases of asteroid internal imaging are also presented. The proposed iterative ADMM can be also applied to similar penetrable imaging applications.

Beschreibung: GNSS Reflectometry, Scatterometry and Radio Occultation aboard ISS is the mission concept under study within the European Space Agency. Its core payload consists of an interferometric GNSS-Reflectometry ocean altimeter/scatterometer which does not need to generate any clean replicas of the GNSS codes for its operation. This paper describes a new interferometric technique by which such payload could also perform radio occultation as an add-on, without requiring any additional hardware resources, like the generation of clean code replicas or a storage of them. Two possibilities are studied. The first one consists of performing the complex autocorrelation function of the received signal transmitted by a rising or setting GNSS satellite. The autocorrelation function is evaluated around time epochs that are multiples of the period of suitable codes found in the modulation of the navigation signals. Satellite discrimination has to be performed spatially, through the antenna pattern. The second possibility consists in acquiring the reference signal separately from the occultation event which, in turn, has two options depending upon the geometry at which the reference is recorded: zenithal and top of the atmosphere. The signal-to-noise ratio, the satellite discrimination, and the impact of clock errors are assessed.

Beschreibung: Geophysics experts are interested in understanding the behavior of volcanoes and forecasting possible eruptions by monitoring and detecting the increment on volcano-seismic activity, with the aim of safeguarding human lives and material losses. This paper presents an automatic volcanic event detection and classification system, which considers feature extraction and feature selection stages, to reduce the processing time toward a reliable real-time volcano early warning system (RT-VEWS). We built the proposed approach in terms of the seismicity presented in 2009 and 2010 at the Cotopaxi Volcano located in Ecuador. In the detection stage, the recordings were time segmented by using a nonoverlapping 15-s window, and in the classification stage, the detected seismic signals were 1-min long. For each detected signal conveying seismic events, a comprehensive set of statistical, temporal, spectral, and scale-domain features were compiled and extracted, aiming to separate long-period (LP) events from volcano-tectonic (VT) earthquakes. We benchmarked two commonly used types of feature selection techniques, namely, wrapper (recursive feature extraction) and embedded (cross-validation and pruning). Each technique was used within a suitable and appropriate classification algorithm, either the support vector machine (SVM) or the decision trees. The best result was obtained by using the SVM classifier, yielding up to 99% accuracy in the detection stage and 97% accuracy and sensitivity in the event classification stage. Selected features and their interpretation were consistent among different input spaces in simple terms of the spectral content of the frequency bands at 3.1 and 6.8 Hz. A comparative analysis showed that the most relevant features for automatic discrimination between LP and VT events were one in the time domain, five in the frequency domain, and nine in the scale domain. Our study provides the framework for an event classification system with high - ccuracy and reduced computational requirements, according to the orientation toward a future RT-VEWS.

Beschreibung: Classification of hyperspectral images usually suffers from high dimensionality and few reference data, which limits the performance of the pixelwise classifiers. The spectral–spatial classifiers, which integrate the spectral data and the spatial information during the classification, perform impressively in terms of the high classification accuracy and the homogeneous appearance of the classification map. In this paper, we propose a new probabilistic framework for spectral–spatial classification (PFSSC), which integrates the spectral data and the spatial information from the probabilistic point of view. Both the spectral data and the spatial information are used to estimate the per-pixel probability, which gives the likelihood that one pixel belongs to one class, respectively. The classification map can then be directly derived from the joint probability. In the proposed framework, a pixelwise probabilistic classifier can be extended as a spectral–spatial one since it can integrate spatial information easily. Furthermore, these spectral–spatial classifiers in the proposed framework are realized in an iterative way to avoid the problem caused by the limited reference data to some extent. In each iterative step, some unassigned pixels are classified by considering the pixels assigned in previous iterative steps. In this iterative process, pixels are assigned to specific labels step by step gradually. In the proposed framework, the probabilistic support vector machine (SVM) and random forest (RF) are extended to be two spectral–spatial classifiers. In short, we denote them as SVM-PFSSC and RF-PFSSC, respectively. The experimental results show that SVM-PFSSC and RF-PFSSC outperform some pixelwise and spectral–spatial classifiers.

Beschreibung: Land cover/land use (LCLU) information extraction from multitemporal sequences of remote sensing imagery is becoming increasingly important. Mixed pixels are a common problem in Landsat and MODIS images that are used widely for LCLU monitoring. Recently developed subpixel mapping (SPM) techniques can extract LCLU information at the subpixel level by dividing mixed pixels into subpixels to which hard classes are then allocated. However, SPM has rarely been studied for time-series images (TSIs). In this paper, a spatiotemporal SPM approach was proposed for SPM of TSIs. In contrast to conventional spatial dependence-based SPM methods, the proposed approach considers simultaneously spatial and temporal dependences, with the former considering the correlation of subpixel classes within each image and the latter considering the correlation of subpixel classes between images in a temporal sequence. The proposed approach was developed assuming the availability of one fine spatial resolution map which exists among the TSIs. The SPM of TSIs is formulated as a constrained optimization problem. Under the coherence constraint imposed by the coarse LCLU proportions, the objective is to maximize the spatiotemporal dependence, which is defined by blending both spatial and temporal dependences. Experiments on three data sets showed that the proposed approach can provide more accurate subpixel resolution TSIs than conventional SPM methods. The SPM results obtained from the TSIs provide an excellent opportunity for LCLU dynamic monitoring and change detection at a finer spatial resolution than the available coarse spatial resolution TSIs.

Beschreibung: The ability to classify urban objects in large urban scenes from point clouds efficiently and accurately still remains a challenging task today. A new methodology for the effective and accurate classification of terrestrial laser scanning (TLS) point clouds is presented in this paper. First, in order to efficiently obtain the complementary characteristics of each 3-D point, a set of point-based descriptors for recognizing urban point clouds is constructed. This includes the 3-D geometry captured using the spin-image descriptor computed on three different scales, the mean RGB colors of the point in the camera images, the LAB values of that mean RGB, and the normal at each 3-D point. The initial 3-D labeling of the categories in urban environments is generated by utilizing a linear support vector machine classifier on the descriptors. These initial classification results are then first globally optimized by the multilabel graph-cut approach. These results are further refined automatically by a local optimization approach based upon the object-oriented decision tree that uses weak priors among urban categories which significantly improves the final classification accuracy. The proposed method has been validated on three urban TLS point clouds, and the experimental results demonstrate that it outperforms the state-of-the-art method in classification accuracy for buildings, trees, pedestrians, and cars.

Beschreibung: Target detection in hyperspectral images (HSIs) is an active area of research; it seeks to detect objects that are small in both number and size within a scene. The proposed work presents a new methodology for target detection in HSIs by combining kurtosis, level sets, and a size-based thresholding strategy. Kurtosis is used as a preprocessing step to initially enhance the targets in an image. Then, level sets identify and mark associations of pixels with similar spectral information as candidate targets. Finally, the size-based thresholding strategy detects true targets and discards false alarms that do not fit with target dimensions set as input parameter. In addition, we propose a novel version of level sets, which is suitable for target detection tasks in HSIs. Results show that the proposed algorithm could successfully detect targets in HSIs, and it gave better performance in terms of the receiver operating characteristic curve than other techniques widely used in target detection such as orthogonal subspace projection, constrained signal detector, constrained energy minimization, adaptive cosine/coherent estimator algorithm, and generalized-likelihood ratio test.

Beschreibung: A high-pulse-repetition-frequency (PRF) radar can handle the high Doppler frequencies of clutter echoes received by a fast-moving airborne radar. However, high-PRF radar causes range ambiguity. In addition, the clutter is range dependent when the airborne radar works in a forward-looking geometry. The range ambiguity and range dependence will lead to severe performance degradation of the traditional space-time adaptive processing (STAP) methods. In this paper, a vertical frequency diverse array (FDA), which applies frequency diversity in the vertical of a planar array, is explored to circumvent the range ambiguity problem in STAP radar. A range-ambiguous clutter suppression approach is devised, which consists of vertical spatial frequency compensation and pre-STAP filtering. In the vertical-FDA radar, the vertical spatial frequency depends not only on the depression angle but also on the slant range. By using this characteristic, the range-ambiguous clutter can be separated in the vertical spatial frequency domain, and then, clutter suppression is achieved for each separated range region. As a result, both problems of range ambiguity and range dependence are solved. Simulation results are provided to demonstrate the effectiveness of the proposed method.

Beschreibung: Synthetic aperture radar (SAR) interferometric baseline parameters form important input for SAR interferometry. In this paper, a nonlinear error model is established for the SAR interferometric baseline and parameterized as a polynomial based on the natural nonlinearity of the orbit of a satellite. Unlike conventional models, the proposed model takes into account the nonlinear part of the baseline error. A theoretical derivation is performed based on the imaging geometry of interferometric SAR, and the results of the analysis show that the parameters of the nonlinear baseline error model can be obtained from the relationship between the orbit, the nominal baseline, the baseline error, and the residual interferogram phase. A sample data set from the Japanese Earth Resources Satellite-1 (JERS-1) L-band SAR is used to validate the proposed model, and the results indicated that the compensation of the residual interferogram phase of the test data is superior to that provided by conventional models.

Beschreibung: Leaf area index (LAI) is an important vegetation biophysical variable and has been widely used for crop growth monitoring and yield estimation, land-surface process simulation, and global change studies. Several LAI products currently exist, but most have limited temporal coverage. A long-term high-quality global LAI product is required for greatly expanded application of LAI data. In this paper, a method previously proposed was improved to generate a long time series of Global LAnd Surface Satellite (GLASS) LAI product from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data. The GLASS LAI product has a temporal resolution of eight days and spans from 1981 to 2014. During 1981–1999, the LAI product was generated from AVHRR reflectance data and was provided in a geographic latitude/longitude projection at a spatial resolution of 0.05°. During 2000–2014, the LAI product was derived from MODIS surface-reflectance data and was provided in a sinusoidal projection at a spatial resolution of 1 km. The GLASS LAI values derived from MODIS and AVHRR reflectance data form a consistent data set at a spatial resolution of 0.05°. Comparison of the GLASS LAI product with the MODIS LAI product (MOD15) and the first version of the Geoland2 (GEOV1) LAI product indicates that the global consistency of these LAI products is generally good. However, relatively large discrepancies among these LAI products were observed in tropical forest regions, where the GEOV1 LAI values were clearly lower than the GLASS and MOD15 LAI values, particularly in January. A quantitative comparison of temporal profiles shows that the temporal smoothness of the GLASS LAI product is superior to that of the GEOV1 and MODIS LAI products. Direct validation with the mean values of high-resolution LAI maps demonstrates that the GLASS LAI values were closer to the mean values of the high-resolution LAI maps ( $text{RMSE}=0.7848$ and $R^{2}=0.8095$ ) than the GEOV1 LAI values ( $text{RMSE}=0.9084$ and $R^{2}=0.7939$ ) and the MOD15 LAI values ( $text{RMSE}=1.1173$ and $R^{2}=0.6705$ ).

Beschreibung: A novel approach called Spectral–Spatial 1-D Manifold Embedding (SS1DME) is proposed in this paper for remotely sensed hyperspectral image (HSI) classification. This novel approach is based on a generalization of the recently developed smooth ordering model, which has gathered a great interest in the image processing area. In the proposed approach, first, we employ the spectral–spatial information-based affinity metric to learn the similarity of HSI pixels, where the contextual information is encoded into the affinity metric using spatial information. In our derived model, based on the obtained affinity metric, the created multiple 1-D manifold embeddings (1DMEs) consist of several different versions of 1DME of the same set of all HSI points. Since each 1DME of the data is a 1-D sequence, a label function on the data can be obtained by applying the simple 1-D signal processing tools (such as interpolation/regression). By collecting the predicted labels from these label functions, we build a subset of the current unlabeled points, on which the labels are correctly labeled with high confidence. Next, we add a proportion of the elements from this subset to the original labeled set to get the updated labeled set, which is used for the next running instance. Repeating this process for several loops, we get an extended labeled set, where the new members are correctly labeled by the label functions with much high confidence. Finally, we utilize the extended labeled set to build the target classifier for the whole HSI pixels. In the whole process, 1DME plays the role of learning data features from the given affinity metric. With the incrementation of learning features during iteration, the proposed scheme will gradually approximate the exact labels of all sample points. The proposed scheme is experimentally demonstrated using four real HSI data sets, exhibiting promising classification performance when compared with other recently introduced - patial analysis alternatives.

Beschreibung: We evaluate the potential of troposphere models derived from ground meteorological data (pressure, temperature, and relative humidity) and Global Positioning System (GPS) data to improve InSAR measurements and models derived from them. We test this approach on an ERS-2/Envisat data set collected during a transient surface deformation episode that occurred from January to July 2005 in the San Gabriel Valley, southern California, USA. We find that the interferometric phase change observed over the corresponding period cannot be solely attributed to hydrological uplift associated with rising groundwater levels but also includes a significant contribution from differential tropospheric delay due to differing quantities of water vapor in the troposphere on the two SAR observation dates. We show that, if the tropospheric phase contribution is mistakenly interpreted as the range change associated with changes in groundwater storage, both the surface displacement and the groundwater storage coefficient may be overestimated by up to 30%. This method could be applied in real time where meteorological measurements are available near one or more GPS permanent site(s).

Beschreibung: In the booming era of high-resolution synthetic aperture radar (SAR) technology, SAR advanced information retrieval is critical for effective utilization of huge-volume SAR data. One important aspect of high-resolution SAR interpretation is to explore the anisotropic and dispersive information embedded among subaperture and subband SAR images. This paper formulates the polarimetric subaperture analysis as a singular-value decomposition problem, where polarimetric and anisotropic features can be simultaneously decomposed. The decomposed singular values and left singular vectors are equivalent to eigenanalysis-based polarimetric target decomposition, whereas the right singular vectors give the corresponding anisotropic feature vectors. A physics-based parameterization is proposed for anisotropic patterns, where two anisotropic entropy parameters, namely, compactness and directivity, are proposed. Both simulation results and real SAR image analyses demonstrate that these proposed anisotropic entropies can effectively identify specific types of scatterers depending on their geometric scale, curvature, and form of spatial distribution. The proposed anisotropic entropies could be applied to single- and dual-polarization high-resolution SAR data as well.

Beschreibung: This paper presents a method for estimating the solar transmittance of urban trees using airborne light detection and ranging (LiDAR), and the radiative transfer simulation of vegetation. The leaf area density (LAD) distribution of trees with voxel size $1 text{m}times 1 text{m}times 0.5 text{m}$ is estimated using high-resolution and multireturn airborne LiDAR data. The LAD of voxels having few incident laser beams is corrected from the surrounding voxels. The LAD of the periphery of the crown is discretized into $0.5 text{m}times 0.5 text{m}times 0.5 text{m}$ voxels to accurately calculate the shaded area. The resulting LAD distribution is used in a radiative transfer simulation to calculate the solar transmittance of the trees. We verified the accuracy of the calculated transmittance by comparing it with empirical data for a Zelkova serrata . The comparisons were conducted under different angles of incidence of laser beams and solar radiation. When the angle between the incident laser beams and solar radiation was small, the transmittance could be accurately estimated. The LAD correction enabled the method to be applied to a broader range of the angle between beams and solar radiation. When the zenith angle of the incident laser beams was small $(< 10^{circ})$ and the LAD correction was carried out, the errors in transmittance were within 0.06 for solar altitudes greater than 40°. Next, we examined the difference in solar transmittance among streets caused by the layout of trees and buildings and the growth condition of the trees. It was shown that the present method is able to quantify the solar shading provided by urban trees and take into account LAD, tree layout, and the spatial geometry of the surr- unding buildings.

Beschreibung: This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph cut called pruning to extract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and analyzed in the context of PolSAR images for segmentation. Through the objective evaluation of the resulting partitions by means of precision-and-recall-for-boundaries curves, the best pruning technique is identified, and the influence of the tree construction on the performances is assessed.

Beschreibung: Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day–night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for significantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified “candidate fire pixel selection” approach from FILDA that lowers the 4- $mutext{m}$ brightness temperature (BT) threshold but includes a minimum DNB radiance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4- $mutext{m}$ BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

Beschreibung: Hyperspectral image (HSI) denoising is a crucial preprocessing task that is used to improve the quality of images for object detection, classification, and other subsequent applications. It has been reported that noise can be effectively removed using the sparsity in the nonnoise part of the image. With the appreciable redundancy and correlation in HSIs, the denoising performance can be greatly improved if this redundancy and correlation is utilized efficiently in the denoising process. Inspired by this observation, a noise reduction method based on joint spectral–spatial distributed sparse representation is proposed for HSIs, which exploits the intraband structure and the interband correlation in the process of joint sparse representation and joint dictionary learning. In joint spectral–spatial sparse coding, the interband correlation is exploited to capture the similar structure and maintain the spectral continuity. The intraband structure is utilized to adaptively code the spatial structure differences of the different bands. Furthermore, using a joint dictionary learning algorithm, we obtain a dictionary that simultaneously describes the content of the different bands. Experiments on both synthetic and real hyperspectral data show that the proposed method can obtain better results than the other classic methods.

Beschreibung: Miniaturized hyperspectral imaging sensors are becoming available to small unmanned airborne vehicle (UAV) platforms. Imaging concepts based on frame format offer an attractive alternative to conventional hyperspectral pushbroom scanners because they enable enhanced processing and interpretation potential by allowing for acquisition of the 3-D geometry of the object and multiple object views together with the hyperspectral reflectance signatures. The objective of this investigation was to study the performance of novel visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral frame cameras based on a tunable Fabry–Pérot interferometer (FPI) in measuring a 3-D digital surface model and the surface moisture of a peat production area. UAV image blocks were captured with ground sample distances (GSDs) of 15, 9.5, and 2.5 cm with the SWIR, VNIR, and consumer RGB cameras, respectively. Georeferencing showed consistent behavior, with accuracy levels better than GSD for the FPI cameras. The best accuracy in moisture estimation was obtained when using the reflectance difference of the SWIR band at 1246 nm and of the VNIR band at 859 nm, which gave a root mean square error (rmse) of 5.21 pp (pp is the mass fraction in percentage points) and a normalized rmse of 7.61%. The results are encouraging, indicating that UAV-based remote sensing could significantly improve the efficiency and environmental safety aspects of peat production.

Beschreibung: This paper analyzes the availability and accuracy of coastal altimetry sea level products in the Strait of Gibraltar. All possible repeats of two sections of the Envisat and AltiKa ground-tracks were used in the eastern and western portions of the strait. For Envisat, along-track sea level anomalies (SLAs) at 18-Hz posting rate were computed using ranges from two sources, namely, the official Sensor Geophysical Data Records (SGDRs) and the outputs of a coastal waveform retracker, the Adaptive Leading Edge Subwaveform (ALES) retracker; in addition, SLAs at 1 Hz were obtained from the Centre for Topographic studies of the Ocean and Hydrosphere (CTOH). For AltiKa, along-track SLA at 40 Hz was also computed both from SGDR and ALES ranges. The sea state bias correction was recomputed for the ALES-retracked Envisat SLA. The quality of these altimeter products was validated using two tide gauges located on the southern coast of Spain. For Envisat, the availability of data close to the coast depends crucially on the strategy followed for data screening. Most of the rejected data were due to the radar instrument operating in a low-precision nonocean mode. We observed an improvement of about 20% in the accuracy of the Envisat SLAs from ALES compared to the standard (SGDR) and the reprocessed CTOH data sets. AltiKa shows higher accuracy, with no significant differences between SGDR and ALES. The use of products from both missions allows longer times series, leading to a better understanding of the hydrodynamic processes in the study area.

Beschreibung: This paper describes the analysis performed on coherent simultaneously recorded monostatic and bistatic sea clutter data. The data were generated using a networked pulsed radar system, namely, NetRAD. This analysis is completed in both the temporal and Doppler domains, and the parameters characterized are compared between multiple bistatic angles and different polarizations. The K-distribution model is used to assess the variation in the clutter amplitude statistics between multiple bistatic data and the corresponding monostatic data. Key characteristics of the Doppler data, such as the spectrum width, center of gravity (CoG), and variance of the spectral width, are evaluated as a function of bistatic angle allowing novel relationships to be defined. The results conclude that the bistatic Doppler data have a lower K-distribution shape parameter in the majority of bistatic angles compared with the simultaneous monostatic data. In addition, novel trends in the relationship between the clutter spectrum CoG and the clutter intensity are presented.

Beschreibung: Icebergs represent hazards to maritime traffic and offshore operations. Satellite synthetic aperture radar (SAR) is very valuable for the observation of polar regions, and extensive work was already carried out on detection and tracking of large icebergs. However, the identification of small icebergs is still challenging especially when these are embedded in sea ice. In this paper, a new detector is proposed based on incoherent dual-polarization SAR images. The algorithm considers the limited extension of small icebergs, which are supposed to have a stronger cross-polarization and higher cross- over copolarization ratio compared to the surrounding sea or sea ice background. The new detector is tested with two satellite systems. First, RADARSAT-2 quad-polarimetric images are analyzed to evaluate the effects of high-resolution data. Subsequently, a more exhaustive analysis is carried out using dual-polarization ground-detected Sentinel-1a extra wide swath images acquired over the time span of two months. The test areas are in the east coast of Greenland, where several icebergs have been observed. A quantitative analysis and a comparison with a detector using only the cross-polarization channel are carried out, exploiting grounded icebergs as test targets. The proposed methodology improves the contrast between icebergs and sea ice clutter by up to 75 times. This returns an improved probability of detection.

Beschreibung: A novel wavelet-based scheme to increase coefficient independence in hyperspectral images is introduced for lossless coding. The proposed regression wavelet analysis (RWA) uses multivariate regression to exploit the relationships among wavelet-transformed components. It builds on our previous nonlinear schemes that estimate each coefficient from neighbor coefficients. Specifically, RWA performs a pyramidal estimation in the wavelet domain, thus reducing the statistical relations in the residuals and the energy of the representation compared to existing wavelet-based schemes. We propose three regression models to address the issues concerning estimation accuracy, component scalability, and computational complexity. Other suitable regression models could be devised for other goals. RWA is invertible, it allows a reversible integer implementation, and it does not expand the dynamic range. Experimental results over a wide range of sensors, such as AVIRIS, Hyperion, and Infrared Atmospheric Sounding Interferometer, suggest that RWA outperforms not only principal component analysis and wavelets but also the best and most recent coding standard in remote sensing, CCSDS-123.

Beschreibung: The hump feature is one of the major instabilities in pump-turbines. When pump-turbines operate in the hump region, strong noise and serious fluctuations can be observed, which are harmful to their safe and stable operation and can even destroy the whole unit as well as water conveyance system. In this paper, a low specific speed (nq = 36.1 min−1) pump-turbine model was experimentally investigated. Firstly, the hump characteristic was obtained under 19 mm guide vane opening conditions. More interestingly, when the hump characteristic was measured in two directions (increasing and decreasing the discharge), characteristic hysteresis was found in the hump region. The analysis of performance characteristics reveals that the hump instability is the result of Euler momentum and hydraulic losses, and different Euler momentum and hydraulic losses in the two development processes lead to the hysteresis phenomenon. Then, 12 pressure sensors were mounted in the different parts of the pump-turbine model to obtain the time and frequency characteristics. The analysis of the corresponding fast Fourier transform confirms that the hump characteristic is related to low-frequency (0.04–0.15 times rotational frequency) vortices. The occurrence and cessation of vortices depend on the operating condition and measurement direction, which contribute to the hysteresis feature. Finally, the type of the low-frequency vortices was analyzed through the cross power spectrum.

Beschreibung: In day-ahead electricity price forecasting (EPF) variable selection is a crucial issue. Conducting an empirical study involving state-of-the-art parsimonious expert models as benchmarks, datasets from three major power markets and five classes of automated selection and shrinkage procedures (single-step elimination, stepwise regression, ridge regression, lasso and elastic nets), we show that using the latter two classes can bring significant accuracy gains compared to commonly-used EPF models. In particular, one of the elastic nets, a class that has not been considered in EPF before, stands out as the best performing model overall.

Beschreibung: It is a common practice for storage batteries to be connected to DC microgrid buses through DC-DC converters for voltage support on islanded operation mode. A feed-forward control based dual-loop constant voltage PI control for three-branch interleaved DC-DC converters (TIDC) is proposed for storage batteries in DC microgrids. The working principle of TIDC is analyzed, and the factors influencing the response rate based on the dual-loop constant voltage control for TIDC are discussed, and then the method of feed-forward control for TIDC is studied to improve the response rate for load changing. A prototype of the TIDC is developed and an experimental platform is built. The experiment results show that DC bus voltage sags or swells caused by load changing can be reduced and the time for voltage recovery can be decreased significantly with the proposed feed-forward control.

Beschreibung: Increasingly complex air path concepts are investigated to achieve a substantial reduction in fuel consumption while improving the vehicle dynamics. One promising technology is the two-stage turbocharging for gasoline engines, where a high pressure and a low pressure turbocharger are placed in series. For exploiting the high potential, a control concept has to be developed that allows for coordinated management of the two turbocharger stages. In this paper, the control strategy is investigated. Therefore, the effect of the actuated values on transient response and pumping losses is analyzed. Based on these findings, an optimization-based control algorithm is developed that allows taking both requirements into account. The developed new controller allows achieving a fast transient response, while at the same time reducing pumping losses in stationary operation.

Beschreibung: Due to the rapid growth in the amount of wind energy connected to distribution grids, they are exposed to higher network constraints, which poses additional challenges to system operation. Based on regulation, the system operator has the right to curtail wind energy in order to avoid any violation of system constraints. Energy storage systems (ESS) are considered to be a viable solution to solve this problem. The aim of this paper is to provide the best locations of both ESS and wind power by optimizing distribution system costs taking into account network constraints and the uncertainty associated to the nature of wind, load and price. To do that, we use a mixed integer linear programming (MILP) approach consisting of loss reduction, voltage improvement and minimization of generation costs. An alternative current (AC) linear optimal power flow (OPF), which employs binary variables to define the location of the generation, is implemented. The proposed stochastic MILP approach has been applied to the IEEE 69-bus distribution network and the results show the performance of the model under different values of installed capacities of ESS and wind power.

Beschreibung: To achieve the carbon free electricity generation target for 2050, the penetration of renewable energy sources should further increase. To address the impacts of their unpredictable and intermittent characteristics on the future electricity grid, Pumped Hydro Energy Storage (PHES) plants should enhance their regulation capability by extending their continuous operating range far beyond the optimal normal working range. However, for the time being, the regulation capability of the new generation of PHES, equipped with reversible pump-turbines due to their cost-effectiveness, is limited at part load by instability problems. The aim of this paper is to analyse, during a pumping power reduction scenario, the onset and development of unsteady phenomena leading to unstable behaviour. A 3D transient numerical simulation was carried out on the first stage of a variable-speed two-stage pump-turbine from full load to the unstable operating zone by progressively reducing the speed from 100% to 88% rpm corresponding to a power reduction from full load to about 60% with a ramp rate of 1.5% per s. Two three-dimensional unsteady flow structures affecting the return channel and the wicket gates at the end of the first stage were identified and their evolution in the power regulation scenario was fluid-dynamically and spectrally characterized to determine the fluid-dynamical conditions causing the head drop in the hump zone.

Beschreibung: A new control technique known as inverted error deviation (IED) control is incorporated into the main DC-link capacitor voltage regulation algorithm of a three-level neutral-point diode clamped (NPC) inverter-based shunt active power filter (SAPF) to enhance its performance in overall DC-link voltage regulation so as to improve its harmonics mitigation performances. In the SAPF controller, DC-link capacitor voltage regulation algorithms with either the proportional-integral (PI) or fuzzy logic control (FLC) technique have played a significant role in maintaining a constant DC-link voltage across the DC-link capacitors. However, both techniques are mostly operated based on a direct voltage error manipulation approach which is insufficient to address the severe DC-link voltage deviation that occurs during dynamic-state conditions. As a result, the conventional algorithms perform poorly with large overshoot, undershoot, and slow response time. Therefore, the IED control technique is proposed to precisely address the DC-link voltage deviation. To validate effectiveness and feasibility of the proposed algorithm, simulation work in MATLAB-Simulink and experimental implementation utilizing a TMS320F28335 Digital Signal Processor (DSP) are performed. Moreover, conventional algorithms with PI and FLC techniques are tested too for comparison purposes. Both simulation and experimental results are presented, confirming the improvement achieved by the proposed algorithm in terms of accuracy and dynamic response in comparison to the conventional algorithms.

Beschreibung: This paper presents a Monte Carlo approach for reliability assessment of distribution systems with distributed generation using parallel computing. The calculations are carried out with a royalty-free power flow simulator, OpenDSS (Open Distribution System Simulator). The procedure has been implemented in an environment in which OpenDSS is driven from MATLAB. The test system is an overhead distribution system represented by means of a three-phase model that includes protective devices. The paper details the implemented procedure, which can be applied to systems with or without distributed generation, includes an illustrative case study and summarizes the results derived from the analysis of the test system during one year. The goal is to evaluate the test system performance considering different scenarios with different level of system automation and reconfiguration, and assess the impact that distributed photovoltaic generation can have on that performance. Several reliability indices, including those related to the impact of distributed generation, are obtained for every scenario.

Beschreibung: Because of their simplicity and dynamic response, current pulse series are often used to extract parameters for equivalent electrical circuit modeling of Li-ion batteries. These models are then applied for performance simulation, state estimation, and thermal analysis in electric vehicles. However, these methods have two problems: The assumption of linear dependence of the matrix columns and negative parameters estimated from discrete-time equations and least-squares methods. In this paper, continuous-time equations are exploited to construct a linearly independent data matrix and parameterize the circuit model by the combination of non-negative least squares and genetic algorithm, which constrains the model parameters to be positive. Trigonometric functions are then developed to fit the parameter curves. The developed model parameterization methodology was applied and assessed by a standard driving cycle.

Beschreibung: Environmental radiation in space (from the Sun, etc.) and operational thermal loads result in heat flows inside the structure of satellites. Today these heat flows remain unused and are collected, transported to a radiator and emitted to space to prevent the satellite from overheating, but they hold a huge potential to generate electrical power independently of solar panels. Thermoelectric generators are a promising approach for such applications because of their solid state characteristics. As they do not have any moving parts, they do not cause any vibrations in the satellite. They are said to be maintenance-free and highly reliable. Due to the expected small heat flows modern devices based on BiTe have to be considered, but these devices have no flight heritage. Furthermore, energy harvesting on space systems is a new approach for increasing the efficiency and reliability. In this paper, different systems studies and applications are discussed based some experimental characterisation of the electrical behaviour and their dependence on thermal cycles and vibration.

Beschreibung: This paper presents real time information based energy management algorithms to reduce electricity cost and peak to average ratio (PAR) while preserving user comfort in a smart home. We categorize household appliances into thermostatically controlled (tc), user aware (ua), elastic (el), inelastic (iel) and regular (r) appliances/loads. An optimization problem is formulated to reduce electricity cost by determining the optimal use of household appliances. The operational schedules of these appliances are optimized in response to the electricity price signals and customer preferences to maximize electricity cost saving and user comfort while minimizing curtailed energy. Mathematical optimization models of tc appliances, i.e., air-conditioner and refrigerator, are proposed which are solved by using intelligent programmable communication thermostat ( iPCT). We add extra intelligence to conventional programmable communication thermostat (CPCT) by using genetic algorithm (GA) to control tc appliances under comfort constraints. The optimization models for ua, el, and iel appliances are solved subject to electricity cost minimization and PAR reduction. Considering user comfort, el appliances are considered where users can adjust appliance waiting time to increase or decrease their comfort level. Furthermore, energy demand of r appliances is fulfilled via local supply where the major objective is to reduce the fuel cost of various generators by proper scheduling. Simulation results show that the proposed algorithms efficiently schedule the energy demand of all types of appliances by considering identified constraints (i.e., PAR, variable prices, temperature, capacity limit and waiting time).

Beschreibung: Energy is considered as a main influence on urban configurations. However, there is a difficulty on translating the city models based on theoretical renewable energy concepts into practical applications. This study considers the possibility of understanding this future model as a transformation of the existing urban centres. With this objective, a methodology to intervene in existing cities based on the study of solar access is developed. Therefore, an analysis of solar potential in relation with urban morphology is carried on through a simulation software in l’Eixample, a neighbourhood of Barcelona. The distribution of the sun factor in the different areas of the building blocks envelope displays possible morphological modifications that would facilitate solar energy collection. Consequently, the analytical method presented could be applied to regulate urban interventions with the aim of obtaining more solar energy based cities.

Beschreibung: Local electricity generation and sharing has been given considerable attention recently for its disaster resilience and other reasons. However, the process of designing local sharing communities (or local grids) is still unclear. Thus, this study empirically compares algorithms for electricity sharing community clustering in terms of self-sufficiency, sharing cost, and stability. The comparison is performed for all 12 months of a typical year in Yokohama, Japan. The analysis results indicate that, while each individual algorithm has some advantages, an exhaustive algorithm provides clusters that are highly self-sufficient. The exhaustive algorithm further demonstrates that a clustering result optimized for one month is available across many months without losing self-sufficiency. In fact, the clusters achieve complete self-sufficiency for five months in spring and autumn, when electricity demands are lower.

Beschreibung: This book contains the successful invited submissions [1–25] to a Special Issue of Energies on the subject area of “Electrical Power and Energy Systems for Transportation Applications”.

Beschreibung: In this paper, we develop and investigate the optimal control of a group of 104 heat pumps and a central Combined Heat and Power unit (CHP). The heat pumps supply space heating and domestic hot water to households. Each house has a buffer for domestic hot water and a floor heating system for space heating. Electricity for the heat pumps is generated by a central CHP unit, which also provides thermal energy to a district heating system. The paper reviews recent smart grid control approaches for central and distributed levels. An online algorithm is described based on the earliest deadline first theory that can be used on the aggregator level to control the CHP and to give signals to the heat pump controllers if they should start or should wait. The central controller requires only a limited amount of privacy-insensitive information from the heat pump controllers about their deadlines, which the heat pump controllers calculate for themselves by model predictions. In this way, a robust heat pump and CHP control is obtained, which is able to minimize energy demand and results in the desired thermal comfort for the households. The simulations demonstrate fast computation times due to minor computational and communication overheads.

Beschreibung: Outdoor thermal comfort is an essential factor of people’s everyday life and deeply affects the habitability of outdoor spaces. However the indices used for its evaluation were usually developed for indoor environments assuming still air conditions and absence of solar radiation and were only later adapted to outdoor spaces. For this reason, in a previous study the Mediterranean Outdoor Comfort Index (MOCI) was developed, which is an empirical index able to estimate the thermal perception of people living in the Mediterranean area. In this study it was compared numerically (by using the data obtained through a field survey) with other selected thermal indices. This comparison, performed in terms of Spearman’s rho correlation coefficient, association Gamma, percentage of correct predictions and cross-tabulation analysis, led to identify the MOCI as the most suitable index to examine outdoor thermal comfort in the interested area. As a matter of fact it showed a total percentage of correct predictions of 35.5%. Good performances were reported even in thermophysiological indices as the Physiological Equivalent Temperature (PET) and Predicted Mean Vote (PMV). Moreover it was revealed that adaptation and acclimatization phenomena tend to have a certain influence as well.

Beschreibung: Although Permanent Magnet Synchronous Generator (PMSG) wind turbines (WTs) mitigate gearbox impacts, they requires high reliability of generators and converters. Statistical analysis shows that the failure rate of direct-drive PMSG wind turbines’ generators and inverters are high. Intelligent fault diagnosis algorithms to detect inverters faults is a premise for the condition monitoring system aimed at improving wind turbines’ reliability and availability. The influences of random wind speed and diversified control strategies lead to challenges for developing intelligent fault diagnosis algorithms for converters. This paper studies open-circuit fault features of wind turbine converters in variable wind speed situations through systematic simulation and experiment. A new fault diagnosis algorithm named Wind Speed Based Normalized Current Trajectory is proposed and used to accurately detect and locate faulted IGBT in the circuit arms. It is compared to direct current monitoring and current vector trajectory pattern approaches. The results show that the proposed method has advantages in the accuracy of fault diagnosis and has superior anti-noise capability in variable wind speed situations. The impact of the control strategy is also identified. Experimental results demonstrate its applicability on practical WT condition monitoring system which is used to improve wind turbine reliability and reduce their maintenance cost.

Beschreibung: While previous studies have examined China’s changing industrial energy consumption at the national level, this study argues that it is more useful, from a policy standpoint, to conduct a regional-level analysis owing to the significant regional disparity in industrialisation in the country. This study focuses particularly on Northeast China, where the implementation of the Northeast Revitalisation Strategy in 2003 has contributed to rapid reindustrialisation, which has a serious implication for industrial energy consumption. We decompose the region’s energy consumption changes into activity, structure, and intensity effects. Our results show that the intensity effect is not the only negative factor impacting industrial energy consumption during 2003–2012. The structure effect also has a negative impact on industrial energy consumption between 2005 and 2012. However, the negative impact of the two factors is weakening and not strong enough to counter the positive impact of the activity effect. This result highlights the problem of uncoordinated policy-making in Northeast China. The development strategy, which still depends highly on traditional heavy industries, is in conflict with the national strategy of energy conservation. The two conflicting objectives of industrial revitalization and energy conservation must be reconciled for sustainability in the long term. The study concludes with policy recommendations on how to achieve such reconciliation.

Beschreibung: In order to determine the most cost effective alternative among hardening options of power systems, the direct monetary benefits should be evaluated above all other things. Therefore, this paper presents a life-cycle cost model which describes total monetary costs experienced in annual time increments during the project with consideration for the time value of money. In addition, to minimize the risks associated with estimated cost errors due to uncertainties of input data, the stochastic input data are considered. Using the Monte Carlo method, the probabilities and cost ranges in the case studies can be predicted, in turn resulting in better decisions in the selection of hardening options which are cost effective.

Beschreibung: The realization of the Smart Grid vision will change the way of producing and distributing electrical energy. It paves the road for end-users to become pro-active in the distribution system and, equipped with renewable energy generators such as a photovoltaic panel, to become a so called “prosumer”. The prosumer is engaged in both energy production and consumption. Prosumers’ energy can be transmitted and exchanged as a commodity between end-users, disrupting the traditional utility model. The appeal of such scenario lies in the engagement of the end user, in facilitating the introduction and optimization of renewables, and in engaging the end-user in its energy management. To facilitate the transition to a prosumers’ governed grid, we propose a novel strategy for optimizing decentralized energy exchange in digitalized power grids, i.e., the Smart Grid. The strategy considers prosumer’s involvement, energy loss of delivery, network topology, and physical constraints of distribution networks. To evaluate the solution, we build a simulation program and design three meaningful evaluation cases according to different energy flow patterns. The simulation results indicate that, compared to traditional power distribution system, the maximum reduction of energy loss, energy costs, energy provided by the electric utility based using the proposed strategy can reach 51 % , 66 % , 97.5 % , depending on the strategy. Moreover, the proportion of energy self-satisfaction approaches reaches 98 % .

Beschreibung: In electric power systems, there are always power quality disturbances (PQDs). Usually, noise contamination interferes with their detection and classification. Common methods perform frequency or time-frequency analyses on the power distribution signal for detecting and classifying a limited number of PQDs with some difficulties at low signal-to-noise ratio (SNR). In this regard, recently proposed methodologies for PQD detection estimate several parameters and apply distinct signal processing techniques to improve the detection of PQD. In this work, a novel methodology that merges empirical mode decomposition (EMD), the moments of a random variable, and an artificial neural network (ANN) is proposed for detecting and classifying different PQD. The proposed method estimates skewness, kurtosis, and Shannon entropy from the EMD of one-phase voltage/current signal. Then, an ANN is in charge of classifying the input signal into one of nine different classes for PQD, receiving these parameters as inputs. The effectiveness of the proposed method was verified through computer simulations and experimentation with real data. Obtained results demonstrate its high effectiveness reaching an outstanding 100% of accuracy in detecting and classifying all treated PQD through a few number of parameters, outperforming most of previously proposed approaches.

Beschreibung: Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in this paper and a group of the highly dynamic models is selected for comparison. A new open circuit voltage (OCV) model is proposed. The new model can simulate the OCV curves of lithium iron magnesium phosphate (LiFeMgPO4) battery type at different temperatures. It also considers both charging and discharging cases. The most remarkable features from different models, in addition to the proposed OCV model, are integrated in a single hybrid electrical model. A lumped thermal model is implemented to simulate the temperature development in the battery cell. The synthesized electro-thermal battery cell model is extended to model a battery pack of an actual electric vehicle. Experimental tests on the battery, as well as drive tests on the vehicle are performed. The proposed model demonstrates a higher modeling accuracy, for the battery pack voltage, than the constituent models under extreme maneuver drive tests.

Beschreibung: This article presents heat transfer and fluid flow characteristics in a solar air heater (SAH) channel with multi V-type perforated baffles. The flow passage has an aspect ratio of 10. The relative baffle height, relative pitch, relative baffle hole position, flow attack angle, and baffle open area ratio are 0.6, 8.0, 0.42, 60°, and 12%, respectively. The Reynolds numbers considered in the study was in the range of 3000–10,000. The re-normalization group (RNG) k-ε turbulence model has been used for numerical analysis, and the optimum relative baffle width has been investigated considering relative baffle widths of 1.0–7.0.The numerical results are in good agreement with the experimental data for the range considered in the study. Multi V-type perforated baffles are shown to have better thermal performance as compared to other baffle shapes in a rectangular passage. The overall thermal hydraulic performance shows the maximum value at the relative baffle width of 5.0.

Beschreibung: The introduction of uncontrollable renewable energy is having a positive impact on our health, the climate, and the economy, but it is also pushing the limits of the power system. The main reason for this is that, in any power system, the generation and consumption must match each other at all times. Thus, if we want to further introduce uncontrollable generation, we need a large ability to manage the demand. However, the ability to control the power consumption of existing demand management approaches is limited, and most of these approaches cannot contribute to the introduction of reneweables, because they do not consider distributed uncontrolled consumption and generation in the control. Furthermore, these methods do not allow users to exchange or jointly manage their power generation and consumption. In this context, we propose an augmented energy management model for prosumers (i.e., producer and consumer). This model considers controlled and uncontrolled generation and consumption, as well as the prosumer’s ability (i) to plan the intended power consumption; and (ii) to manage real-time deviations from the intended consumption. We apply this model to the energy management of prosumer communities, by allowing the prosumers to coordinate their power consumption plan, to manage the deviations from the intended consumption, and to help each other by compensating deviations. The proposed approach seeks to enhance the power system, and to enable a prosumer society that takes account social and environmental issues, as well as each prosumer’s quality of life.

Beschreibung: The objective of this paper is to numerically investigate the effects of the atmospheric boundary layer on the aerodynamic performance and loads of a novel dual-rotor wind turbine (DRWT). Large eddy simulations are carried out with the turbines operating in the atmospheric boundary layer (ABL) and in a uniform inflow. Two stability conditions corresponding to neutral and slightly stable atmospheres are investigated. The turbines are modeled using the actuator line method where the rotor blades are modeled as body forces. Comparisons are drawn between the DRWT and a comparable conventional single-rotor wind turbine (SRWT) to assess changes in aerodynamic efficiency and loads, as well as wake mixing and momentum and kinetic energy entrainment into the turbine wake layer. The results show that the DRWT improves isolated turbine aerodynamic performance by about 5%–6%. The DRWT also enhances turbulent axial momentum entrainment by about 3.3 %. The highest entrainment is observed in the neutral stability case when the turbulence in the ABL is moderately high. Aerodynamic loads for the DRWT, measured as out-of-plane blade root bending moment, are marginally reduced. Spectral analyses of ABL cases show peaks in unsteady loads at the rotor passing frequency and its harmonics for both rotors of the DRWT.

Beschreibung: In cognitive radio (CR), the spectrum sensing of the primary user (PU) may consume some electrical power from the battery capacity of the secondary user (SU), resulting in a decrease in the transmission power of the SU. In this paper, a multislot simultaneous spectrum sensing and energy harvesting model is proposed, which uses the harvested radio frequency (RF) energy of the PU signal to supply the spectrum sensing. In the proposed model, the sensing duration is divided into multiple sensing slots consisting of one local-sensing subslot and one energy-harvesting subslot. If the PU is detected to be present in the local-sensing subslot, the SU will harvest RF energy of the PU signal in the energy-harvesting slot, otherwise, the SU will continue spectrum sensing. The global decision on the presence of the PU is obtained through combining local sensing results from all the sensing slots by adopting “Or-logic Rule”. A joint optimization problem of sensing time and time splitter factor is proposed to maximize the throughput of the SU under the constraints of probabilities of false alarm and detection and energy harvesting. The simulation results have shown that the proposed model can clearly improve the maximal throughput of the SU compared to the traditional sensing-throughput tradeoff model.

Beschreibung: Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed for conventional data networks with different requirements. It is therefore necessary to investigate how much of existing communication technologies can be retrofitted into the new energy infrastructure to cost-effectively deliver acceptable level of service. This paper investigates broadband power line communications (BPLC) as a backhaul solution in AMI. By applying the disparate traffic characteristics of selected AMI applications, the network performance is evaluated. This study also examines the communication network response to changes in application configurations in terms of packet sizes. In each case, the network is stress-tested and performance is assessed against acceptable thresholds documented in the literature. Results show that, like every other communication technology, BPLC has certain limitations; however, with some modifications in the network topology, it indeed can fulfill most AMI traffic requirements for flexible and time-bounded applications. These opportunities, if tapped, can significantly improve fiscal and operational efficiencies in AMI services. Simulation results also reveal that BPLC as a backhaul can support flat and clustered AMI structures with cluster size ranging from 1 to 150 smart meters.

Beschreibung: This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative.

Beschreibung: This paper presents the development of a WebGIS application aimed at providing safe and reliable data needed for reclamation of abandoned mines in national parks and other protected areas in Vojvodina in compliance with existing legal regulations. The geodatabase model for this application has been developed using UML and the CASE tool Microsoft Visio featuring an interface with ArcGIS. The WebGIS application was developed using GeoServer, an open source tool in the Java programming language, with integrated PostgreSQL DB and the possibility of generating and publishing WMS, WFS and KML services. The WebGIS application is publicly available, based on an appropriate central database, which for the first time encompasses all available data on abandoned mines in Vojvodina, and as such may serve as a model for similar databases on the territory of the Republic of Serbia.

Beschreibung: This paper presents a review of over a decade of research on Vertical Axis Wind Turbines (VAWTs) conducted at Uppsala University. The paper presents, among others, an overview of the 200 kW VAWT located in Falkenberg, Sweden, as well as a description of the work done on the 12 kW prototype VAWT in Marsta, Sweden. Several key aspects have been tested and successfully demonstrated at our two experimental research sites. The effort of the VAWT research has been aimed at developing a robust large scale VAWT technology based on an electrical control system with a direct driven energy converter. This approach allows for a simplification where most or all of the control of the turbines can be managed by the electrical converter system, reducing investment cost and need for maintenance. The concept features an H-rotor that is omnidirectional in regards to wind direction, meaning that it can extract energy from all wind directions without the need for a yaw system. The turbine is connected to a direct driven permanent magnet synchronous generator (PMSG), located at ground level, that is specifically developed to control and extract power from the turbine. The research is ongoing and aims for a multi-megawatt VAWT in the near future.

Beschreibung: As safety and reliability critical components, lithium-ion batteries always require real-time diagnosis and prognosis. This often involves a large amount of computation, which makes diagnosis and prognosis difficult to implement, especially in embedded or mobile applications. To address this issue, this paper proposes a run-time Reconfigurable Computing (RC) system on Field Programmable Gate Array (FPGA) for Relevance Vector Machine (RVM) to realize real-time Remaining Useful Life (RUL) estimation. The system leverages state-of-the-art run-time dynamic partial reconfiguration technology and customized computing circuits to balance the hardware occupation and computing efficiency. Optimal hardware resource consumption is achieved by partitioning the RVM algorithm according to a multi-objective optimization. Moreover, pipelined and parallel computation circuits for kernel function and matrix inverse are proposed on FPGA to further accelerate the computation. Experimental results with two different battery data sets show that, without sacrificing the RUL prediction performance, the embedded RC platform significantly reduces the computation time and the requirement of hardware resources. This demonstrates that complex prognostic tasks can be implemented and deployed on the proposed system, and it can be extended to the embedded computation of other machine learning algorithms.

Beschreibung: Interior permanent magnet (IPM) motors are widely used in electric vehicles (EVs), benefiting from the excellent advantages of a more rational use of energy. For further improvement of energy utilization, this paper presents an analytical method of d- and q-axis inductance calculation for IPM motors with V-shaped rotor in no-load condition. A lumped parameter magnetic circuit model (LPMCM) is adopted to investigate the saturation and nonlinearity of the bridge. Taking into account the influence of magnetic field distribution on inductance, the winding function theory (WFT) is employed to accurately calculate the armature reaction airgap magnetic field and d- and q-axis inductances. The validity of the analytical technique is verified by the finite element method (FEM).

Beschreibung: A building integrated holographic concentrating photovoltaic-thermal system has been optically and energetically simulated. The system has been designed to be superimposed into a solar shading louvre; in this way the concentrating unit takes profit of the solar altitude tracking, which the shading blinds already have, to increase system performance. A dynamic energy simulation has been conducted in two different locations—Sde Boker (Israel) and Avignon (France)—both with adequate annual irradiances for solar applications, but with different weather and energy demand characteristics. The simulation engine utilized has been TRNSYS, coupled with MATLAB (where the ray-tracing algorithm to simulate the holographic optical performance has been implemented). The concentrator achieves annual mean optical efficiencies of 30.3% for Sde Boker and 43.0% for the case of Avignon. Regarding the energy production, in both locations the thermal energy produced meets almost 100% of the domestic hot water demand as this has been considered a priority in the system control. On the other hand, the space heating demands are covered by a percentage ranging from 15% (Avignon) to 20% (Sde Boker). Finally, the electricity produced in both places covers 7.4% of the electrical demand profile for Sde Boker and 9.1% for Avignon.

Beschreibung: In order to investigate how artificial neural networks (ANNs) have been applied for partial discharge (PD) pattern recognition, this paper reviews recent progress made on ANN development for PD classification by a literature survey. Contributions from several authors have been presented and discussed. High recognition rate has been recorded for several PD faults, but there are still many factors that hinder correct recognition of PD by the ANN, such as high-amplitude noise or wide spectral content typical from industrial environments, trial and error approaches in determining an optimum ANN, multiple PD sources acting simultaneously, lack of comprehensive and up to date databank of PD faults, and the appropriate selection of the characteristics that allow a correct recognition of the type of source which are currently being addressed by researchers. Several suggestions for improvement are proposed by the authors include: (1) determining the optimum weights in training the ANN; (2) using PD data captured over long stressing period in training the ANN; (3) ANN recognizing different PD degradation levels; (4) using the same resolution sizes of the PD patterns when training and testing the ANN with different PD dataset; (5) understanding the characteristics of multiple concurrent PD faults and effectively recognizing them; and (6) developing techniques in order to shorten the training time for the ANN as applied for PD recognition Finally, this paper critically assesses the suitability of ANNs for both online and offline PD detections outlining the advantages to the practitioners in the field. It is possible for the ANNs to determine the stage of degradation of the PD, thereby giving an indication of the seriousness of the fault.

Beschreibung: Attributing to the advantages of high efficiency, low electromagnetic interference (EMI) noise and closest to the pulse-width-modulation (PWM) converter counterpart, zero-voltage-transition (ZVT) PWM soft-switching inverters are very suitable for high-performance applications. However, the conventional control algorithms intended for high efficiency generally results in voltage distortion. Thus, this paper, for the first time, proposes a high-precision control method to eliminate the dead-time effect through controlling the auxiliary current in the auxiliary resonant snubber inverter (ARSI), which is a typical ZVT PWM inverter. The dead-time effect of ARSI is analyzed, which is distinguished from hard-switching inverters. The proposed high-precision control is introduced based on the investigation of dead-time effect. A prototype was developed to verify the effectiveness of the proposed control. The experimental results shows that the total harmonic distortion (THD) of the output current of the ARSI can be reduced compared with that of the hard-switching inverter, because the blanking delay error is eliminated. The quality of the output current and voltage can be further improved by utilizing the proposed control method.

Beschreibung: Trigeneration plants can use different types of chillers in the same plant, typically single effect and double effect absorption chillers, vapour compression chillers and also cooling storage systems. The highly variable cooling demand of the buildings connected to a district heating and cooling (DHC) network has to be distributed among these chillers to achieve lower operating costs and higher energy efficiencies. This problem is difficult to solve due to the different partial load behaviour of each chiller and the different chiller combinations that can cover a certain cooling demand using an appropriate sizing of the cooling storage. The objective of this paper is to optimize the daily plant operation of an existing trigeneration plant based on cogeneration engines and to study the optimal cooling load sharing between different types of absorption chillers using a mixed integer linear programming (MILP) model. Real data from a trigeneration plant connected to a DHC close to Barcelona (Spain) is used for the development of this model. The cooling load distribution among the different units is heavily influenced by the price of the electricity sold to the grid which rules the duration of the operation time of the engines. The main parameter to compare load distribution configurations is the primary energy saving indicator. Cooling load distribution among the different chillers changes also with the load of the whole plant because the chiller performance changes with load.

Beschreibung: This study describes the environmental impact of the material production, transportation, and construction phases from the construction site perspective. CO2 emissions for each process were determined using the Korea Life Cycle Inventory Database (LCI DB) in the material production phase, and the actual amounts of oil consumption for transportation equipment were identified in the material transportation phase. Generally, the oil and electric energy consumed during the construction was evaluated by direct monitoring. Through the construction period and cost according to work type, a correlation with CO2 emissions was also investigated. In addition, CO2 emissions were examined through the system capacity and gross floor area for each work type. The calculations have shown that CO2 emissions from the material production phase constitute 93.4% of the total CO2 emissions. In addition, CO2 emissions from the material transportation and on-site construction account for 2.4% and 4.2% of the total CO2 emissions, respectively. This paper concludes that it is important to select appropriate input materials and resources for the reduction of CO2 emissions. Furthermore, the amount of CO2 emissions arising from the construction site was reduced by finding and practicing measures to reduce CO2 emissions for each process.

Beschreibung: In the context of the liberalization of electricity markets, forecasting prices is essential. With this aim, research has evolved to model the particularities of electricity prices. In particular, dynamic factor models have been quite successful in the task, both in the short and long run. However, specifying a single model for the unobserved factors is difficult, and it cannot be guaranteed that such a model exists. In this paper, model averaging is employed to overcome this difficulty, with the expectation that electricity prices would be better forecast by a combination of models for the factors than by a single model. Although our procedure is applicable in other markets, it is illustrated with an application to forecasting spot prices of the Iberian Market, MIBEL (The Iberian Electricity Market). Three combinations of forecasts are successful in providing improved results for alternative forecasting horizons.

Beschreibung: Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capable of peak-shaving at the transformer level, while keeping the voltages well within legal bounds, keeping the cable load low and obtaining low losses. Further advantages of the methodology are a low communication overhead, low computational requirements and ease of implementation.

Beschreibung: The objective of this work was to monitor and analyse temperature changes in the ground with installed linear and Slinky-type horizontal ground heat exchangers (HGHEs), used as low-potential heat pump energy sources. Specific heat flows and specific energies extracted from the ground during the heating season were also measured and compared. The verification results showed that the average daily ground temperatures with the two HGHEs are primarily affected by the temperature of the ambient environment. The ground temperatures were higher than ambient temperature during most of the heating season, were only seldom below zero, and were higher by an average 1.97 ± 0.77 K in the ground with the linear HGHE than in the ground with the Slinky-type HGHE. Additionally, the specific thermal output extracted from the ground by the HGHE was higher by 8.45 ± 16.57 W/m2 with the linear system than with the Slinky system. The specific energies extracted from the ground over the whole heating season were 110.15 kWh/m2 and 57.85 kWh/m2 for the linear and Slinky-type HGHEs, respectively.

Beschreibung: Integrating natural resources and ecological services in the production process is crucial to implement sustainable agriculture. However, the measurement of natural resource efficiency remains difficult. This paper aims at contributing to this issue, by investigating French farms’ use and excess (slack) of energy resources through Data Envelopment Analyses (DEA). Results show that disentangling energy resources from the rest of intermediate consumption highlights energy use excess which is masked when considering intermediate consumption as a whole. The analysis of the determinants of energy use excess and of intermediate consumption shows a discrepancy in results, which policy-makers should take into account when designing energy policies. In addition, results show that large and highly capital intensive farms perform better in terms of energy use excess, while the dependence on public subsidies is a constraint.

Beschreibung: Fuel cells are the most clean and efficient power source for vehicles. In particular, proton exchange membrane fuel cells (PEMFCs) are the most promising candidate for automobile applications due to their rapid start-up and low-temperature operation. Through extensive global research efforts in the latest decade, the performance of PEMFCs, including energy efficiency, volumetric and mass power density, and low temperature startup ability, have achieved significant breakthroughs. In 2014, fuel cell powered vehicles were introduced into the market by several prominent vehicle companies. However, the low durability and high cost of PEMFC systems are still the main obstacles for large-scale industrialization of this technology. The key materials and components used in PEMFCs greatly affect their durability and cost. In this review, the technical progress of key materials and components for PEMFCs has been summarized and critically discussed, including topics such as the membrane, catalyst layer, gas diffusion layer, and bipolar plate. The development of high-durability processing technologies is also introduced. Finally, this review is concluded with personal perspectives on the future research directions of this area.

Beschreibung: In this paper, a photovoltaic (PV)-based single ended primary-inductor converter (SEPIC) is developed with introduction of dual-fuzzy logic controller (FLC) maximum power point tracking (MPPT) algorithm. Separate FLC parts, for the first time used for MPPT, are configured for optimal operations of both buck and boost operations. During buck operation, a high overshoot voltage exists, and during boost operation, an undershoot voltage occurs, both during the initial rising period. Definitely, a single-FLC MPPT could not be able to minimize both problems, which on the other hand can be handled by the proposed MPPT algorithm. For evaluation purposes, buck operation has been conducted during high irradiance, while during low irradiance, boost operation has been conducted. The dual-FLC MPPT with SEPIC was simulated in MATLAB-Simulink, and further a laboratory prototype was implemented with a TMS320F28335 eZdsp board. Both simulation and experimental results and comparison analysis (with the single-FLC MPPT) have been presented. From the results and analysis, the dual-FLC MPPT performs better than the single-FLC MPPT in terms of faster response time, lower overshoot and undershoot, and further significant reduction of power losses.

Beschreibung: The development of renewable energy is one of the aspirations of the European Union energy policy, being generated by the struggle against climatic changes and by the intention of achieving a high rate of energy autonomy. In this context, geothermal energy is a viable solution which has been little exploited so far. Analysing the EU’s dependence on imported energy, the paper provides a short review of the utilization of geothermal energy, of the advantages and of the problems raised by the exploitation of this resource. It also analyzes the availability of this resource in Romania and the contribution it can have towards the energy autonomy of local communities. The paper presents a particular methodology for calculating the energy autonomy. Using this methodology, one can obtain an energetic overview of the community or the area analyzed, can calculate the degree of energy autonomy and, based on the results achieved, a sustainable development strategy can be designed. The low enthalpy case study used emphasizes the way this methodology can be deployed and, moreover, allows an analysis of the contribution of geothermal energy to the degree of autonomy of the Romanian community.

Beschreibung: Heat dissipation per unit volume has grown rapidly, as the size of modern electronic devices has continued to decrease. The air flow induced by an oscillating cantilever blade enhances the heat transfer performance of high heat density devices. The heat transfer improvement mainly depends on the velocity magnitude and distribution of air streams induced by the vibrating blade. Accordingly, this study numerically and experimentally examines the time-varying flow characteristics of a vibrating cantilever for five blade types. The blades are rectangular or trapezoidal with various widths and actuated at various frequencies. The fluid domain is numerically discretized using a dynamic meshing scheme to model the three-dimensional time-varying vibrating blade. The experiment utilizes nine hot-wire velocity meters to measure the average velocities. The flow structure with streamlines and velocity contours of the induced air flow are determined at various section planes. The results show that a major maximum-velocity region appears around the blade tip and that four minor local-maximum-velocity regions appear at the four corners. In addition, the width and width ratio of the blade significantly affects the velocity distribution of the flow induced by the vibrating cantilever blade.

Beschreibung: The critical problem arising from the depletion of fossil fuels has stimulated recent interests in alternative sources for petroleum-based fuel. An alternative fuel should be technically feasible, readily available, sustainable, and techno-economically competitive. Biodiesel is considered as a potential replacement of conventional diesel fuel, which is prepared from non-edible and high-acid feedstock via transesterification technology. The focus of this study is to investigate the catalytic activity of mixed metal oxides (MMOs) as catalysts for biodiesel production by using non-edible jatropha oil as feedstock. Various types of MMOs (CaO-MgO, CaO-ZnO, CaO-La2O3, and MgO-ZnO) were synthesized via a co-precipitation method. In this study, transesterification activities are closely related to the physicochemical properties of catalysts. The presence of different active metals in the binary system greatly influenced the surface area, basicity, and the stability of catalysts. The catalytic activity of MMO catalysts was increased in the order of CaO-ZnO (94% ± 1%) &gt; CaO ~ CaO-MgO ~ CaO-La2O3 (~90% ± 2%) &gt; MgO-ZnO (83% ± 2%) &gt; MgO (64% ± 1%) &gt; ZnO (41% ± 2%) &gt; La2O3 (23% ± 1%). In addition, the MMO catalysts, especially CaO-ZnO, demonstrated high reusability and catalyst stability for four cycles of transesterification reaction of jatropha oil.

Beschreibung: Super typhoon activity is likely to make the electric power network fail, or blow the wind-measuring device off, which all lead to the yaw control system of wind turbine being inactive. Under this condition, blades can be blown by the violent side wind from unfavorable directions, and the aerodynamic loads on the wind turbine will be increased by a large amount, which can lead to low-cycle fatigue damage and other catastrophic collapses. So far, not enough consideration has been given to the above problems in wind turbine design. Using the transient computational fluid dynamics (CFD), this study investigates the wind load characteristics of offshore wind turbines under typhoon condition with 360-degree full wind directions. Two primary influence factors of the aerodynamic characteristics of wind turbines are clarified: variation of the wind direction and different parking positions of the wind rotor. Using 3D-numerical simulation results, this study provides detailed references for the ultimate strength and fatigue life in wind turbine design, and presents the best parking position of the wind turbine with a free yawing strategy.

Beschreibung: Plasma stability is one of the obstacles in the path to the successful operation of fusion devices. Numerical control-oriented codes as it is the case of the widely accepted RZIp may be used within Tokamak simulations. The novelty of this article relies in the hierarchical development of a dynamic control loop. It is based on a current profile Model Predictive Control (MPC) algorithm within a multiloop structure, where a MPC is developed at each step so as to improve the Proportional Integral Derivative (PID) global scheme. The inner control loop is composed of a PID-based controller that acts over the Multiple Input Multiple Output (MIMO) system resulting from the RZIp plasma model of the Tokamak à Configuration Variable (TCV). The coefficients of this PID controller are initially tuned using an eigenmode reduction over the passive structure model. The control action corresponding to the state of interest is then optimized in the outer MPC loop. For the sake of comparison, both the traditionally used PID global controller as well as the multiloop enhanced MPC are applied to the same TCV shot. The results show that the proposed control algorithm presents a superior performance over the conventional PID algorithm in terms of convergence. Furthermore, this enhanced MPC algorithm contributes to extend the discharge length and to overcome the limited power availability restrictions that hinder the performance of advanced tokamaks.

Beschreibung: A multi-variable optimization program has been developed to investigate the performance of Organic Rankine Cycles (ORCs) for low temperature heat recovery applications using both turbine and twin-screw expanders when account is taken of performance variation due to changes in ambient conditions. The cycle simulation contains thermodynamic models of both types of expander. In the case of the twin-screw machine, the methods used to match the operation of the expander to the requirements of the cycle are described. The performance of turbine expanders in a superheated ORC has been modelled using correlations derived from operational data for single stage reaction turbines to predict the turbine efficiency at “off-design” conditions. Several turbine configurations have been considered including variable nozzle area and variable speed. The capability of the cycle model has been demonstrated for the case of heat recovery from a steady source of pressurized hot water at 120 °C. The system parameters are optimised for a typical operating condition, which determines the required size of heat exchangers and the expander characteristics. Performance at off-design conditions can then be optimized within these constraints. This allows a rigorous investigation of the effect of air temperature variation on the system performance, and the seasonal variation in net power output for the turbine and twin-screw ORC systems. A case study is presented for a low temperature heat recovery application with system electrical power output of around 100 kWe at design conditions. The results indicate that similar overall performance can be achieved for ORC systems using either type of expander.

Beschreibung: Automatic target generation process (ATGP) has been widely used for unsupervised target detection. However, as designed, it detects targets using full-band information. Unfortunately, on many occasions, various targets can be detected using varying bands, and ATGP can only provide one-shot target detection with all bands being used. This paper develops a new approach which can implement ATGP bandwise in a progressive manner, called progressive band processing of ATGP (PBP-ATGP) so that ATGP can be carried out band by band. Since PBP-ATGP must repeatedly implement orthogonal projections, recursive equations are further derived for PBP-ATGP, to be called recursive band processing of ATGP (RBP-ATGP) which can implement PBP-ATGP recursively. As a result, many advantages can be benefited from RBP-ATGP. Most importantly, RBP-ATGP can generate 3-D interband progressive profiles from band to band that can be used for progressive target detection, a task for which no target detection techniques using full-band information can provide.

Beschreibung: With the steadily increasing spatial resolution of synthetic aperture radar images, the need for a consistent but locally adaptive image enhancement rises considerably. Numerous studies already showed that adaptive multilooking, able to adjust the degree of smoothing locally to the size of the targets, is superior to uniform multilooking. This study introduces a novel approach of multiscale and multidirectional multilooking based on intensity images exclusively but applicable to an arbitrary number of image layers. A set of 2-D circular and elliptical filter kernels in different scales and orientations (named Schmittlets) is derived from hyperbolic functions. The original intensity image is transformed into the Schmittlet coefficient domain where each coefficient measures the existence of Schmittlet-like structures in the image. By estimating their significance via the perturbation-based noise model, the best-fitting Schmittlets are selected for image reconstruction. On the one hand, the index image indicating the locally best-fitting Schmittlets is utilized to consistently enhance further image layers, e.g., multipolarized, multitemporal, or multifrequency layers, and on the other hand, it provides an optimal description of spatial patterns valuable for further image analysis. The final validation proves the advantages of the Schmittlets over six contemporary speckle reduction techniques in six different categories (preservation of the mean intensity, equivalent number of looks, and preservation of edges and local curvature both in strength and in direction) by the help of four test sites on three resolution levels. The additional value of the Schmittlet index layer for automated image interpretation, although obvious, still is subject to further studies.

Beschreibung: The Clouds and the Earth's Radiant Energy System (CERES) instrument requires in-flight calibration and validation to maintain its accuracy during orbit operations over an extended period. An internal calibration system provides calibration for the three channels; however, there is no device for calibration of the shortwave response of the total channel. A three-channel comparison technique has been developed to calibrate the shortwave response of the total channel using the tropical oceans as a vicarious calibration target. The difference between day and night outgoing longwave radiances (OLR) averaged over the tropical oceans is used to validate the day OLR. This paper evaluates the efficacy of the technique. A relation is computed at night between the window channel radiance and the OLR retrieved from the total channel for each month for each instrument. The relation has a standard deviation of 0.28 $text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ . Given 120 months of data, the precision of the curved line faired through these data is better than 0.05 $text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ . A bias is found between FM-1 and FM-3 of 0.3 $text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ , which is taken to be the accuracy with which the total channels can be calibrated with the internal blackbodies. This result includes the differences of longwave spectral responses of the instruments. The tropical mean OLR is between 87.4 and 90.2 $text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ at night, with a standard deviation of 0.44 for FM-1 and 0.47 $text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ for FM-3. The avera- e difference between day and night tropical mean from the four instruments is $0.6pm 0.09 text{W}cdottext{m}^{-2}cdottext{sr}^{-1}$ over their data periods.