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  • Articles  (5,219)
  • Institute of Electrical and Electronics Engineers (IEEE)  (5,219)
  • Energy, Environment Protection, Nuclear Power Engineering  (2,668)
  • Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics  (2,551)
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  • 1
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Print ISSN: 0018-9499
    Electronic ISSN: 1558-1578
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
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  • 2
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Description: Programming languages like C and Ada combined with proprietary embedded operating systems have dominated the real-time application space for decades. The new C++11 standard includes native, language-level support for concurrency, a required feature for any nontrivial event-oriented real-time software. Threads, Locks, and Atomics now exist to provide the necessary tools to build the structures that make up the foundation of a complex real-time system. The National Spherical Torus Experiment Upgrade (NSTX-U) at the Princeton Plasma Physics Laboratory (PPPL) is breaking new ground with the language as applied to the needs of fusion devices. A new Digital Coil Protection System (DCPS) will serve as the main protection mechanism for the magnetic coils, and it is written entirely in C++11 running on Concurrent Computer Corporation’s real-time operating system, RedHawk Linux. It runs over 600 algorithms in a 5 kHz control loop that determine whether or not to shut down operations before physical damage occurs. To accomplish this, NSTX-U engineers developed software tools that do not currently exist elsewhere, including real-time atomic synchronization, real-time containers, and a real-time logging framework. Together with a recent (and carefully configured) version of the GCC compiler, these tools enable data acquisition, processing, and output using a conventional operating system to meet a hard real-time deadline (that is, missing one periodic is a failure) of 200 microseconds.
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  • 3
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Description: Thallium-bromide (TlBr) is currently under investigation as an alternative room-temperature semiconductor gamma-ray spectrometer due to its favorable material properties (large bandgap, high atomic numbers, and high density). Previous work has shown that 5 mm thick pixelated TlBr detectors can achieve sub-1% FWHM energy resolution at 662 keV for single-pixel events. These results are limited to $ - 20{^ circ }{rm C}$ operation where detector performance is stable. During the first one to five days of applied bias at $ - 20{^ circ }{rm C}$ , many TlBr detectors undergo a conditioning phase, where the energy resolution improves and the depth-dependent electron drift velocity stabilizes. In this work, the spectroscopic performance, drift velocity, and freed electron concentrations of multiple 5 mm thick pixelated TlBr detectors are monitored throughout the conditioning phase. Additionally, conditioning is performed twice on the same detector at different times to show that improvement mechanisms relax when the detector is stored without bias. We conclude that the improved spectroscopy results from internal electric field stabilization and uniformity caused by fewer trapped electrons.
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  • 4
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Description: Silicon Photomultipliers (SiPMs) are attractive candidates for light detectors for next generation liquid xenon double-beta decay experiments, like nEXO (next Enriched Xenon Observatory). In this paper we discuss the requirements that the SiPMs must satisfy in order to be suitable for nEXO and similar experiments, describe the two test setups operated by the nEXO collaboration, and present the results of characterization of SiPMs from several vendors. In particular, we find that the photon detection efficiency at the peak of xenon scintillation light emission (175-178 nm) approaches the nEXO requirements for tested FBK and Hamamatsu devices. Additionally, the nEXO collaboration performed radio-assay of several grams of bare FBK devices using neutron activation analysis, indicating levels of $^{40}{rm K}$ , $^{232}{rm Th}$ , and $^{238}{rm U}$ of the order of $ 〈 0.15$ , ( $ 6.9cdot 10^{ - 4} - 1.3 cdot 10^{ - 2}$ ), and $ 〈 0.11 ~hbox{mBq}/hbox{kg}$ , respectively.
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  • 5
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Description: It is very important for plant operators to be informed of the departure from nucleate boiling ratio (DNBR) to prevent the fuel cladding from melting and a boiling crisis in a nuclear reactor. The reactor core monitoring and protection systems require a minimum DNBR value to monitor reactor coolant conditions. In this study, in order to estimate the minimum DNBR value, a cascaded fuzzy neural network (CFNN) method was used. The CFNN model can be used to estimate the minimum DNBR value through the process of adding fuzzy neural networks (FNNs) repeatedly. The proposed DNBR estimation algorithm was verified by applying the nuclear and thermal data acquired from many numerical simulations of the optimized power reactor 1000 (OPR1000). The CFNN model was compared to previously developed models and was found to be superior to them. Therefore, this model can be used to effectively monitor and predict the minimum DNBR in the reactor core.
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  • 6
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-08-18
    Print ISSN: 0018-9499
    Electronic ISSN: 1558-1578
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Physics
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  • 7
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 8
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Nowadays, clean renewable energy extraction solutions are becoming a crucial practice in society. Many different sources are being developed including ocean energy and in specific, ocean waves. In deep water conditions, ocean waves can become very power dense, continuous, and forecastable. Wave height, velocity, and frequency are all variable wave characteristics making it challenging to capture wave power economically. The RTI F2 is a promising wave energy conversion device that is currently under research. Its method of power capture is a buoyant vessel oriented normal to oncoming waves. This paper discusses known control methods implemented on the RTI F2, the experimental setup used for control of the device, and wave tank testing done at the University of New Hampshire's Chase Laboratory. Experimental data was obtained across various wave conditions, plate angles, vessel weights, and control strategies. The results of these tests are presented in the subject matter.
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  • 9
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Many existing solar irradiance monitoring networks were built particularly for resource assessment purposes; they are often spatially sparse. In order for the networks to handle other increasingly important tasks, such as irradiance forecasting for grid integration, their spatial sparsity must be addressed by adding in new monitoring stations. Optimally expanding these networks using historical information thus becomes an important research topic for engineers. Variability of solar irradiance in space and time can be quantified using statistics such as entropy and covariance. The deployment of the additional monitoring stations should, therefore, utilize these statistics to reduce the variability. More specifically, we aim at maximizing the entropy of the network. A practical difficulty in statistical modeling of solar irradiance is that the data are not ideal. Properties such as stationarity and isotropy are not observed in irradiance random field. We, therefore, focus on hypothesis testing and transformation of the irradiance data, so that the design procedure is statistically justified. We propose the redesign framework in a solar engineering context, using data from 24 irradiance monitoring stations on a tropical island. In the case study, we demonstrate how to find three optimal stations from a pool of 100 potential future monitoring sites.
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  • 10
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: This paper proposes a novel forecasting model based on a mean trend detector (MTD) and a mathematical morphology-based local predictor (MMLP) to undertake short-term forecast of wind power generation. In the proposed MTD/MMLP model, the nonstationary time series describing wind power generation is first decomposed by the MTD, which employs some new notions and conventional morphological operators. The decomposition yields two componentsthe mean trend, which reveals the tendency of the time series, and the stochastic component, which depicts the fluctuations caused by high frequency of the variability. Subsequently, the $p$ -step forecast is conducted for these two components separately. The mean trend is forecasted on the basis of the least-square support vector machine (LS-SVM) model, while the $p$ -step forecast for the stochastic component is carried out by the MMLP, which involves performing morphological operations employing a novel structuring element (SE) in the phase space. Finally, the forecast of wind power generation is achieved by combining the separate forecasts of two components. In order to evaluate the accuracy and stability of the MTD/MMLP model, simulation studies are carried out using the data obtained from three widely used databases sampled in different periods. The results demonstrate that the MTD/MMLP model provides a more accurate and stable forecast compared to the traditional methods.
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  • 11
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: The distribution network planning under active network management (ANM) schemes is becoming of interest due to substantial benefits in facilitating the increasing integration of renewable energy sources. This paper presents various potential ANM schemes based on the photovoltaic inverter control (PVIC) considering enhanced utilization of the inverter reactive power capability. Depending on the active power generation of PV arrays, inverter size and desired reactive power settings, several PVIC schemes are proposed. The PVIC schemes are incorporated in the optimal power flow (OPF) and formulated as a nonlinear programming (NLP) problem. In this study, the PVIC schemes are applied to maximize the total wind-distributed generation (DG) penetration on a typical U.K. distribution system. Various case studies are presented and compared to evaluate the performance. The results show that the proposed schemes can significantly increase the wind penetration levels by 45.4% and up to 92.3%.
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  • 12
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: In this paper, a health monitoring method for photovoltaic (PV) systems based on probabilistic neural network (PNN) is proposed that detects and classifies short- and open-circuit faults in real time. To implement and validate the proposed method in computer programs, a new approach for modeling PV systems is proposed that only requires information from manufacturers datasheet reported under normal-operating cell temperature (NOCT) conditions and standard-operating test conditions (STCs). The proposed model precisely represents characteristics of PV systems at different temperatures, as the temperature dependency of parameters such as ideality factor, series resistance, and thermal voltage is considered in the proposed model. Although this model can be applied to a variety of applications, it is specifically used to test and validate the performance of the proposed fault detection and classification method.
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  • 13
    Publication Date: 2015-09-18
    Description: Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.
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  • 14
    Publication Date: 2015-09-18
    Description: This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.
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  • 15
    Publication Date: 2015-09-18
    Description: With the increasing size of wind farms, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of locations of the wind turbines (WTs) will influence the capital investment and contribute to the wake losses, which incur the reduction of energy production. As a consequence, the optimized placement of the WTs may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using levelized production cost (LPC) as the objective function. The optimization procedure is performed by a particle swarm optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective to find the optimized layout, which minimizes the LPC. The optimization procedure is applicable for optimized placement of WTs within wind farms and extendible for different wind conditions and capacity of wind farms.
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  • 16
    Publication Date: 2015-09-18
    Description: This paper proposes a novel short-term wind power forecasting approach by mining the bad data of numerical weather prediction (NWP). Today's short-term wind power forecast (WPF) highly depends on the NWP, which contributes the most in the WPF error. This paper first introduces a bad data analyzer to fully study the relationship between the WPF error with several new extracted features from the raw NWP. Second, a hierarchical structure is proposed, which is composed of a K -means clustering-based bad data detection module and a neural network (NN)-based forecasting module. In the NN module, the WPF is fully adjusted based on the output of the bad data analyzer. Simulations are performed comparing with two other different methods. It proves that the proposed approach can improve the short-term wind power forecasting by effectively identifying and adjusting the errors from NWP.
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  • 17
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: The objective of this study was to develop a reduced-order small-signal model of a microgrid system capable of operating in both the grid-tied and the islanded conditions. The nonlinear equations of the proposed system were derived in the $dq$ reference frame and then linearized around stable operating points to construct a small-signal model. The high-order state matrix was then reduced using the singular perturbation technique. The dynamic equations were divided into two groups based on the small-signal model parameters $varepsilon$ . The slow states, which dominated the systems dynamics, were preserved, whereas the fast states were eliminated. Step responses of the model were compared to the experimental results from a hardware test to assess their accuracy and similarity to the full-order system. The proposed reduced-order model was applied to a modified IEEE-37 bus grid-tied microgrid system to evaluate systems dynamic response in grid-tied mode, islanded mode, and transition from grid-tied to islanded mode.
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  • 18
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Many benefits can be achieved through the implementation of a Microgrid controller, such as minimized cost, reduction in peak power, power smoothing, greenhouse gas emission reduction, and increased reliability of service. However, most Microgrid controllers found in the literature and in the industry optimize a single objective, which either exacerbates or does not solve the problems with integrating a high penetration of renewable energy. This paper presents a methodology of formulating a multiobjective optimization (MOO) so that each objective is quantified through valuation functions that can be specific to every Microgrid. The proposed approach attains a Pareto-optimal solution by directly comparing the quantified valuation functions and solving as if it were a single-objective optimization (SOO) problem. Three cases of controllers are presented and compared: 1)a base case system with no controller; 2)an SOO that optimizes the cost of energy; and 3)an MOO that optimizes five identified benefits. Results show that the proposed controller can mitigate the negative impacts of volatile generation to levels below that of the system load.
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  • 19
    Publication Date: 2015-09-18
    Description: Variable over voltage, excessive tap counts, and voltage regulator (VR) runaway condition are major operational challenges in distribution network while accommodating generation from photovoltaics (PVs). The conventional approach to achieve voltage control based on offline simulation for voltage set point calculation does not consider forecast errors. In this work, a stochastic optimal voltage control strategy is proposed while considering load and irradiance forecast errors. Stochastic operational risks such as overvoltage and VR runaway are defined through a chance constrained optimization (CCO) problem. This classical formulation to mitigate runaway is further improved by introducing a stochastic index called the Tap Tail Expectation . Operational objectives such as power losses and excessive tap count minimization are considered in the formulation. A sampling approach is proposed to solve the CCO. Along with other voltage control devices, the PV inverter voltage support features are coordinated. The simulation study is performed using a realistic distribution system model and practically measured irradiance to demonstrate the effectiveness of the proposed technique. The proposed approach is a useful operational procedure for distribution system operators. The approach can minimize feeder power losses, avoid voltage violations, and alleviate VR runaway.
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  • 20
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: The electromagnetic stability issues of the grid-connected doubly fed induction generator (DFIG) system are usually overlooked. This paper presents a reduced order small-signal model that can be used to analyze the stability of DFIGs dc-link voltage control system, especially under weak ac grid conditions. This model neglects DFIG flux and fast current control dynamics. However, the effects of operating points, grid strengths and control loops interactions on system dynamic performance are taken into account. An eigenvalue comparison shows the proposed model holds dominant oscillation mode featured by the detailed model and is suitable for stability analysis of dc-link voltage control system of DFIG. Influence coefficients reflecting control loops interactions are also presented. Application studies of the proposed model show it is suitable for illustrating the effect of grid strength on dynamic performance of the DFIGs dc-link voltage control system. Meanwhile, phase-locked loop (PLL) and rotor-side converter (RSC) active power control (APC)/reactive power controls (RPC) effect on system stability are also explored.
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  • 21
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: Photovoltaic (PV) generation is increasingly popular in power systems. The nonlinear dependence associated with a large number of distributed PV sources adds the complexity to construct an accurate probability model and negatively affects confidence levels and reliability, thereby resulting in a more challenging operation of the systems. Most probability models have many restrictions when constructing multiple PV sources with complex dependence. This paper proposes a versatile probability model of PV generation on the basis of pair copula construction. In order to tackle the computational burden required to construct pair copula in high-dimensional cases, a systematic simplification technique is utilized that can significantly reduce the computational effort while preserving satisfactory precision. The proposed method can simplify the modeling procedure and provide a flexible and optimal probability model for the PV generation with complex dependence. The proposed model is tested using a set of historical data from colocated PV sites. It is then applied to the probabilistic load flow (PLF) study of the IEEE 118-bus system. The results demonstrate the effectiveness and accuracy of the proposed model.
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  • 22
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: It is important to forecast the wind speed for managing operations in wind power plants. However, wind speed prediction is extremely complex and difficult due to the volatility and deviation of the wind. As existing forecasting methods directly model the raw wind speed data, it is difficult for them to provide higher inference accuracy. Differently, this paper presents a sophisticated deep-learning technique for short-term and long-term wind speed forecast, i.e., the predictive deep Boltzmann machine (PDBM) and corresponding learning algorithm. The proposed deep model forecasts wind speed by analyzing the higher level features abstracted from lower level features of the wind speed data. These automatically learnt features are very informative and appropriate for the prediction. The proposed PDBM is a deep stochastic model that can represent the wind speed very well, and is inspired by two aspects. 1)The stochastic model is suitable to capture the probabilistic characteristics of wind speed. 2)Recent developments in neural networks with deep architectures show that deep generative models have competitive capability to approximate nonlinear and nonsmooth functions. The evaluation of the proposed PDBM model is depicted by both hour-ahead and day-ahead prediction experiments based on real wind speed datasets. The prediction accuracy of the PDBM model outperforms existing methods by more than 10%.
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  • 23
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: This paper presents a new maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The proposed method improves the working of the conventional perturb and observe (P&O) method in changing environmental conditions by using the fractional short-circuit current (FSCC) method. It takes the initial operating point of a PV system by using the short-circuit current method and later shifts to the conventional P&O technique. The advantage of having this two-stage algorithm is rapid tracking under changing environmental conditions. In addition, this scheme offers low-power oscillations around MPP and, therefore, more power harvesting compared with the common P&O method. The proposed MPPT decides intelligently about the moment of measuring short-circuit current and is, therefore, an irradiance sensorless scheme. The proposed method is validated with computer software simulation followed by a dSPACE DS1104-based experimental setup. A buck-boost dc-dc converter is used for simulation and experimental confirmation. Furthermore, the reliability of the proposed method is also calculated. The results show that the proposed MPPT technique works satisfactorily under given environmental scenarios.
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  • 24
    Publication Date: 2015-09-18
    Description: In this paper, hardware-in-the-loop (HIL) implementation of solar photovoltaic (PV) array feeding autonomous load, without dump load, is investigated. Two control algorithms based on the sliding mode approach are designed to guarantee a fast and finite-time convergence without adjustment of the system parameters. The dc-dc boost converter and the current controlled-voltage source converter (CC-VSC) are controlled to maximize the power from the PV, to protect the battery energy storage system (BESS) from overcharging, and to regulate the voltage and frequency at the point of common coupling (PCC). An accurate stability analysis of the system is presented and discussed in this work. The effectiveness and the robustness of the developed controllers are validated by simulation and experimental results during the load perturbation and varying climate conditions.
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  • 25
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: This paper proposes to use discrete Fourier transform (DFT) and discrete wavelet transform (DWT) methods to schedule grid-scale energy storage systems to mitigate wind power forecast error impacts while considering energy storage properties. This is accomplished by decomposing the wind forecast error signal to different time-varying periodic components to schedule sodium sulfur (NaS) batteries, compressed air energy storage (CAES), and conventional generators. The advantage of signal processing techniques is that the resultant decomposed components are appropriate for cycling of each energy storage technology. It is also beneficial for conventional generators, which are more efficient to operate close to rated capacity. The tradeoff between installing more energy storage units and decreasing the wind spillage, back-up energy, and the standard deviation of residual forecast error signal is analyzed. The NaS battery life cycle analysis and CAES contribution on increasing NaS battery lifetime are studied. The impact of considering the frequency bias constant to allow small frequency deviations is also investigated. To showcase the applicability of the proposed approach, a simulation case study based on a real-world 5-min interval wind data from Bonneville Power Administration (BPA) in 2013 is presented.
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  • 26
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: One role of grid operators is to identify potential problems before they occur and, if necessary, take preemptive actions. As wind generation becomes increasingly widespread, there is the potential for credible, simultaneous fluctuations of output at different locations to result in limit violations. Existing analysis methods that consider forecast errors either inadequately model the control responses available to system operators (e.g., using participation factors) or ignore network constraints, which limits their utility in identifying situations that would require operator action. An alternative method of handling forecast errors, utilizing bilevel programming, is proposed here to identify situations that may result in branch overloads. What distinguishes this method from prior approaches is that it only identifies overloads that can occur despite optimal operator reaction to forecast errors--i.e., when the overload is unavoidable, given current control capabilities. Studies conducted on 37- and 118-bus test systems demonstrate both the utility and feasibility of using this method for online operations.
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  • 27
    Publication Date: 2015-09-18
    Description: In this paper, a control strategy for the participation of photovoltaic (PV) systems in frequency regulation is suggested. A number of strings from every inverter of a PV system are kept as reserve by disconnecting them through dc-relays. Hence, as the control algorithm monitors the grid frequency, it reconnects or disconnects strings, according to the occurring frequency deviations (negative and positive, respectively). Contrary to previous approaches, the suggested methodology here avoids the use of storage devices, which implies additional investment costs, and/or the manipulation of the maximum power point tracking (MPPT) algorithm of the inverter, which represents higher control complexity and special considerations depending on each algorithm. Simulation results from frequency phenomena and solar irradiation changes on a two-bus system in MATLAB Simulink are presented to show the favorable behavior and effective performance of the proposed control strategy. The design concept is also experimentally tested under various operating conditions and on different devices; the results also confirm the feasibility and simplicity of the method.
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  • 28
    Publication Date: 2015-09-18
    Description: In case of abnormal conditions, distribution systems should be reconfigured to overcome the impacts of outages such as overloads of network components and increased power losses. For this purpose, energy storage systems (ESS) and renewable energy sources (RES) can be applied to improve operating conditions. An optimal contingency assessment model using two-stage stochastic linear programming including wind power generation and a generic ESS is presented. The optimization model is applied to find the best radial topology by determining the best switching sequence to solve contingencies. The proposed model is applied to a 69-node distribution system and the results of all possible contingencies in the network are examined considering three different case studies with several scenarios. In addition, a reconfiguration analysis including all the contingencies is presented for the case studies.
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  • 29
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    Publication Date: 2015-09-18
    Description: Ocean energy is a promising resource for renewable electricity generation that presents many advantages, such as being more predictable than wind energy, but also some disadvantages such as large and slow amplitude variations in the generated power. This paper presents a hardware-in-the-loop prototype that allows the study of the electric power profile generated by a wave power plant based on the oscillating water column (OWC) principle. In particular, it facilitates the development of new solutions to improve the intermittent profile of the power fed into the grid or the test of the OWC behavior when facing a voltage dip. Also, to obtain a more realistic model behavior, statistical models of real waves have been implemented.
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  • 30
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: With the significant penetration of wind generation, the variability and uncertainty of wind energy poses new challenges to power system operations. In particular, more rapid reserve is required, which may result in the scarcity of balancing services. With the increasing penetration of renewable generation, it is envisaged that renewable resources will be required to partake in the system balancing tasks. In this paper, a combined flexible dispatch and reserve scheduling policy is proposed by determining a flexible wind dispatch margin. In order to provide a flexible dispatch margin, wind generators underschedule in the hour-ahead energy market, so as to hold some expected output for reserves. Additional wind energy is then available for mitigating forecast errors and other system uncertainties. This paper presents a framework to find the optimal policy to incorporate the flexible wind dispatch margin into the hour-ahead market. A finite-state Markov chain wind power forecast model, based on spatio-temporal analysis, is utilized. The presented framework is used to find the appropriate level of wind dispatch margin. The proposed approach is tested and the wind generation data are used to analyze the effectiveness of the presented model in coping with forecast errors and achieving a more secure system operation.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 31
    Publication Date: 2015-09-18
    Description: A megawatt (MW)-scale hydro-viscous transmission-based continuously variable speed wind turbine is proposed to guarantee a smooth transition among different operating regions and hence to improve power efficiency and quality. This turbine is achieved by highly integrating a hydro-viscous element into the turbine drive-train to mitigate the upstream wind-loading fluctuations. This element allows the turbine speed to be directly regulated by continuously changing the oil film thickness in this element. Three important operating modes of this turbine system are proposed. The control-oriented drive-train model is also established and validated based on experimental data. A cooperative control strategy over the full operating range is then proposed based on such modes. A series of comparative cosimulations are carried out to evaluate the stability and effectiveness of the proposed turbine system in speed and power regulations. This proposed system holds several advantages such as large power capacity, high efficiency, downsized power converters, and low cost. Such advantages make this turbine system particularly attractive and promising for medium-to-large-scale wind power applications.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 32
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-18
    Description: In this paper, a novel ensemble method consisting of neural networks, wavelet transform, feature selection, and partial least-squares regression (PLSR) is proposed for the generation forecasting of a wind farm. Based on the conditional mutual information, a feature selection technique is developed to choose a compact set of input features for the forecasting model. In order to overcome the nonstationarity of wind power series and improve the forecasting accuracy, a new wavelet-based ensemble scheme is integrated into the model. The individual forecasters are featured with different mixtures of the mother wavelet and the number of decomposition levels. The individual outputs are combined to form the ensemble forecast output using the PLSR method. To confirm the effectiveness, the proposed method is examined on real-world datasets and compared with other forecasting methods.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 33
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper considers the problem of emitter location in the presence of an adversary able to inject false information, where both the viewpoints of the adversary and locating network are considered. We begin by developing adversary strategies, which focus on degrading and redirecting the locating network. The locating network uses the time difference of arrival (TDOA) method and estimates the emitter location using both nonlinear least squares (LS) and the robust least median squares (LMS). Specifically, we determine the false sensor position the adversary should inject that maximally impacts the locating network by 1) minimizing the network???s accuracy, and 2) redirecting the network???s emitter location estimate. Similarly, we formulate a network???s strategy for detecting the adversary???s injection and develop a detector able to determine its presence under both adversary strategies. We present both theoretical and numerical results illustrating the effectiveness of the developed strategies.
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  • 34
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Delay/disruption tolerant networking (DTN) offers a solution to communications in ???challenged??? networks. Some work has been seen in evaluating the performance of DTN protocols based on simulated or emulated file transfer experiments. However, there is a need for a model of the performance of the DTN Licklider transmission protocol (LTP), which particularly targets reliable data transmission in deep space. In this paper, we present a performance model of LTP-based DTN data transmission in challenging communications characterized by extremely long signal propagation delay, lengthy link disruptions, and highly lossy channels that are typical of deep-space links. The model is verified by file-transfer experiments using a PC-based testbed.
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  • 35
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Modeling of the dynamics and disturbances and designing of the precise formation controller are two major problems for the inner-formation flying system (IFFS). This paper introduces a nonlinear, nonautonomous formation dynamics model for IFFS in a general elliptic orbit. This model integrates the newly developed formation dynamics and the detailed disturbance models, including atmospheric drag, solar radiation pressure, and J2 effects. Furthermore, this paper establishes a coupled self-gravitational attraction model for IFFS. After considering such a comprehensive dynamics model, the precise formation control problem of IFFS is researched in detail. By referring to the averaging system, Hurwitz matrix, Lyapunov stability theorem, Matrosov???s theory, and Barbalat???s lemma as preliminaries, four possible controllers are designed, i.e., feedback-linearization plus proportional-derivative (PD) controller, Lyapunov-based controller, virtual potential-based controller, and velocity-free virtual potential-based controller. These controllers are all analyzed by the corresponding stability theories. Some simulations are carried out to testify these controllers, and the results show the effectiveness. By comparing the convergence time and fuel consumption, the velocity-free virtual potential-based controller is proven to be a more advantageous controller.
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  • 36
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The fuel-optimal control problem of soft landing becomes a significant challenge due to the highly irregular gravitational field of an asteroid. An indirect method is used to deal with this fuel-optimal control problem. The difficult bang-bang control problem caused by the indirect method is solved through an improved fast homotopic approach. To validate the advanced homotopic method, the landing site is selected in a region where the gravitational field is especially irregular. The results show that this method is effective for the fuel-optimal control problem in an irregular gravitational field. Moreover, the trajectory designed with the fuel-optimal control is taken as a nominal descent trajectory for a sliding mode control. Monte Carlo simulations show that the desired soft landing can be achieved by tracking the fuel-optimal trajectory.
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  • 37
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In this paper, a novel framework of sparse kernel learning for support vector data description (SVDD) based anomaly detection is presented. By introducing 0-1 control variables to original features in the input space, sparse feature selection for anomaly detection is modeled as a mixed integer programming problem. Due to the prohibitively high computational complexity, it is relaxed into a quadratically constrained linear programming (QCLP) problem. The QCLP problem can then be practically solved by using an iterative optimization method, in which multiple subsets of features are iteratively found as opposed to a single subset. However, when a nonlinear kernel such as Gaussian radial basis function kernel, associated with an infinite-dimensional reproducing kernel Hilbert space (RKHS) is used in the QCLP-based iterative optimization, it is impractical to find optimal subsets of features due to a large number of possible combinations of the original features. To tackle this issue, a feature map called the empirical kernel map, which maps data points in the input space into a finite space called the empirical kernel feature space (EKFS), is used in the proposed work. The QCLP-based iterative optimization problem is solved in the EKFS instead of in the input space or the RKHS. This is possible because the geometrical properties of the EKFS and the corresponding RKHS remain the same. Now, an explicit nonlinear exploitation of the data in a finite EKFS is achievable, which results in optimal feature ranking. Comprehensive experimental results on three hyperspectral images and several machine learning datasets show that our proposed method can provide improved performance over the current state-of-the-art techniques.
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  • 38
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper deals with the swath acquisition planning problem for multisatellite Earth observation missions. Given a set of satellites and a mission time frame, the problem we solve consists of selecting a set of acquisitions from the satellites in order to cover a given region of interest during the requested time frame, optimizing a certain objective function.We show that the planning problem can be modeled as a set covering problem, using basic tools of mathematical programming. The formulation of the model requires the solution of a complex computational geometry problem, and therefore the use of heuristics and metaheuristics applies. In this paper, we discuss the efficiency of the constructive phase of a greedy randomized adaptive search procedure algorithm. Computational results comparing the heuristic algorithms with the exact approach are presented.
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  • 39
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper proposes an efficient method to classify inverse synthetic aperture radar (ISAR) images. The proposed method achieves invariance to translation and rotation of ISAR images by using two-dimensional (2D) Fourier transform (FT) of ISAR images, polar mapping of the 2D FT image, and a simple nearest-neighbor classifier. In simulations using ISAR images measured in a compact range, the proposed method yielded high classification ratios with small-sized data regardless of the location of the rotation center, whereas the existing method was very sensitive to the location of it.
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  • 40
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: A method for fusing synthetic aperture radar (SAR) images with optical aerial images is presented. This is done in a navigation framework, in which the absolute position and orientation of the flying platform, as computed from the inertial navigation system, is corrected based on the aerial image coordinates taken as ground truth. The method is suitable for new low-price SAR systems for small unmanned vehicles. The primary application is surveillance, and to some extent it can be applied to remote sensing, where the SAR image provides complementary information by revealing reflectivity to microwave frequencies. The method is based on first applying an edge detection algorithm to the images and then optimising the most important navigation states by matching the two binary images. To get a measure of the estimation uncertainty, we embed the optimisation in a least squares framework, in which an explicit method to estimate the (relative) size of the errors is presented. The performance is demonstrated on real SAR and aerial images, leading to an error of only a few pixels (around 4 m in our case), which is a quite satisfactory performance for applications like surveillance and navigation.
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  • 41
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper presents a sensor-control method for choosing the best next state of the sensors that provide accurate estimation results in a multitarget tracking application. The proposed solution is formulated for a multi-Bernoulli filter and works via minimization of a new estimation-error-based cost function. Simulation results demonstrate that the proposed method can outperform the state-of-the-art methods in terms of computation time and robustness to clutter while delivering similar accuracy.
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  • 42
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The Kalman filter has always been applied to enhance the estimation of inertial measurement unit errors and to improve estimation accuracy of navigation states under practical conditions. Therefore, understanding the behaviors and limitations of optimal estimation of the navigation states is instructive and of great importance. In order to provide comprehensive information about the observability and convergence rapidity of the navigation states when implementing a Kalman filter, the basic properties of intuitive linear-algebraic characterizations of stochastic observability will be intensively investigated in this study. We have extended the utilization of the analytic stochastic observability approach for analytic optimization of strapdown inertial navigation systems multiposition stationary alignment. The advantage of analytic explicit formulation of convergence rapidity of the implemented Kalman filter by stochastic observability approach is demonstrated. Compared to numerical simulation methods, the proposed stochastic observability approach can provide analysts with much more analytic information.
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  • 43
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Localization of persons that are hidden behind a corner is important in various security situations when the first responders should not be exposed to any threat. This article demonstrates the feasibility of an ultrawideband multipath-exploitation radar for localization in such scenarios. The approach utilizes multibounce echoes of electromagnetic waves that are scattered by the closest person situated behind a corner. We assume that the person does not carry any tag and does not cooperate with the localization system. The multibounce echoes are reflected and diffracted by the surroundings and make the hidden person visible to an operator that is behind the corner. The location estimation relies only on single-channel time-of-arrival data. Measured data are first processed by a background subtraction algorithm, which reveals the multipath evoked by the person. The multipath echoes are detected by a parallel threshold-based detector. A simple global nearest-neighbor algorithm is used for tracking detected echoes and improving their range estimates. The obtained range estimates are assigned to different physical propagation paths of the electromagnetic waves. The location of the person is estimated by fusing the information of the antenna location with respect to its surroundings and the assigned range estimates. The proposed approach is experimentally verified in a scenario where data are measured in real time by an ultrawideband sensor. Experimental results demonstrate that, depending on the scenario geometry, a walking or calmly standing person can be localized up to several meters behind the corner.
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  • 44
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting???terrestrial (DVB-T)???based passive radars. However, television broadcast???transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.
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  • 45
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Mechanically steered scanning radars receive measurements continuously while sweeping the surveillance region. However, most target tracking algorithms, like the multiple hypothesis tracker (MHT) and the joint probabilistic data association (JPDA) techniques, wait for the end of a scan in order to process the measurements and to estimate targets states. This is due to the fundamental assumption of one-to-one association between tracks and measurements and the 360° physical limit of a scan. Associating measurements to initialized tracks and filtering at the end of a complete scan may cause significant delays in target state update. In addition, association may become imperfect due to longer intervals between updates. This issue becomes significant when tracking high-speed targets with low scan rate sensors as in the airborne early warning (AEW) system. In this paper, we present a new dynamic sector processing algorithm using two-dimensional (2-D) assignment for scanning radars that report measurements within the duration of a scan. The full scan is dynamically and adaptively divided into sectors, which could be as small as a single detection, depending on the scanning rate, sparsity of targets, and required target state update speed. Measurement-to-track association, filtering, and target state update are done dynamically while sweeping from one region to another, i.e., continuous track update, limited only by the intermeasurement interval, becomes possible. The proposed algorithm offers low latency while maintaining estimation accuracy in track updates as well as efficient utilization of computational resources compared with standard frame-based tracking algorithms. Experimental results based on rotating radars demonstrate the advantages of the proposed technique.
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  • 46
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: An iterative ESPRIT-like algorithm is devised for direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in multiple-input multiple-output radar. Our proposal can handle identical DODs and DOAs, and provides autopairing of the angle parameters. Furthermore, it is proved that the multiple signal classification methodology cannot identify (MN ??? 1) targets, where M and N are the element numbers in the transmit and receive antennas, respectively. Simulation results are included to evaluate the performance of the proposed algorithm.
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  • 47
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Multiple-input multiple-output (MIMO) radar imaging suffers from performance degradation under carrier offsets across transmitters and receivers. This paper analyzes the impact of carrier offsets on imaging a sparse target, from the perspective of the MIMO point spread function (PSF). Conditions are established for successful support recovery using orthogonal matching pursuit (OMP), and the performance loss is characterized in terms of l2 distance. A sparse imaging algorithm taking into account the perturbation due to carrier offsets is also proposed, which improves upon the OMP algorithm. Numerical experiments corroborate this analysis.
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  • 48
    Publication Date: 2015-09-29
    Description: Ambiguity functions (AFs) are obtained for a radar using matched illumination (MI) transmit signals for the detection of range-spread targets in the presence of clutter. The transmit signals are adapted to target and interference spectra and are filtered optimally in the receiver; they are designed to maximize signal-to-interference-and-noise ratio (SINR) power ratios at receiver output. In this paper, expressions for processing gains, spread AFs, and Cramer-Rao bounds on range and Doppler estimates are derived based on likelihood functions. Here, for extended targets, AFs resulting from using optimal MI constant envelope waveforms obtained via phase retrieval techniques demonstrate superior resolution characteristics compared with classic linear frequency-modulated (LFM) signals employing optimal pulse compression. For various target and clutter spectral models, simulation results show that optimally filtered MI signals provide significantly enhanced SINR behavior compared with LFM radar signals. Hopefully, these results set the stage for the induction of MI signaling and receive techniques into conventional radar signal processing and pave the way for realization of one methodology for achieving cognition in radar systems.
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  • 49
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In an effort to improve the channel utilization of a warship combat system (WCS), it is necessary to control and manage the large volume of video traffic by considering a strong self-similarity characteristic. We propose a new video traffic management method for the WCS that smooths the traffic of the closed-circuit television surveillance system (CSS) video and encodes the electro-optical tracking system (EOTS) video with low complexity in real time. First, to achieve global and local traffic smoothing for the CSS video traffic, a proper bandwidth allocation interval and a minimum bandwidth for the CSS video traffic must be determined. Second, due to the increased available bandwidth after traffic smoothing, more elaborate low-delay encoding is accomplished by selecting encoding modes adaptively to compress the EOTS video efficiently with high visual quality. The experimental results demonstrate that the proposed method is able to control the WCS traffic to be as flat as possible and to encode the EOTS video with low delay, even in combat and emergency scenarios. Hence, we show that to migrate to network-centric warfare successfully, the proposed method is much more suitable for the WCS than conventional video traffic management.
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  • 50
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: In this paper, we propose multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) radar with sufficient cyclic prefix (CP), where all OFDM pulses transmitted from different transmitters share the same frequency band and are orthogonal to each other for every subcarrier in the discrete frequency domain. The orthogonality is not affected by time delays from transmitters. Thus, our proposed MIMO OFDM radar has the same range resolution as single transmitter radar and achieves full spatial diversity. Orthogonal designs are used to achieve this orthogonality across the transmitters, with which it is only needed to design OFDM pulses for the first transmitter. We also propose a joint pulse compression and pulse coherent integration for range reconstruction. In order to achieve the optimal signal-to-noise ratio (SNR) for the range reconstruction, we apply the paraunitary filterbank theory to design the OFDM pulses. We then propose a modified iterative clipping and filtering (MICF) algorithm for the designs of OFDM pulses jointly, when other important factors, such as peak-to-average power ratio (PAPR) in time domain, are also considered.With our proposed MIMO OFDM radar, there is no interference for the range reconstruction not only across the transmitters but also across the range cells in a swath called inter-range-cell interference (IRCI) free that is similar to our previously proposed CP-based OFDM radar for single transmitter. Simulations are presented to illustrate our proposed theory and show that the CP-based MIMO OFDM radar outperforms the existing frequency-band shared MIMO radar with polyphase codes and also frequency division MIMO radar.
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  • 51
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: The minimum-variance filter and smoother are generalized to include Poisson-distributed measurement noise components. It is shown that the resulting filtered and smoothed estimates are unbiased. The use of the filter and smoother within expectation-maximization algorithms are described for joint estimation of the signal and Poisson noise intensity. Conditions for the monotonicity and asymptotic convergence of the Poisson intensity iterates are also established. An image restoration example is presented that demonstrates improved estimation performance at low signal-to-noise ratios.
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  • 52
    Publication Date: 2015-09-29
    Description: This paper proposes a new radar/sonar processing architecture that enables a low-rate time-sampling rate while still producing a high-resolution range profile over a narrow range-window. This new architecture generalizes the conventional ???stretch processing??? architecture (which employs linear frequency modulated (LFM) waveforms that suffer from high range-sidelobes), to nonlinear frequency modulated (NLFM) waveforms, which can lower the range-sidelobes without tapering. Computational results demonstrate both the estimation efficacy and the time-sampling efficiency of the proposed scheme.
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  • 53
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: Free-floating manipulators are subject to dynamic singularities that complicate their Cartesian motions and restrict their workspace. In this work, the Cartesian trajectory planning of free-floating manipulators is studied. A methodology is developed in which, for given end-effector trajectories, appropriate initial system configurations are found that result in singularity avoidance during end-effector motion. The method applies to both planar and spatial systems, with and without initial angular momentum, and to any desired end-effector position and attitude trajectories.
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  • 54
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-09-29
    Description: This paper investigates the problem of fusion filtering for a class of networked multisensor fusion systems with multiple uncertainties, including sensor failures, stochastic parameter uncertainties, random observation delays, and packet dropouts. A novel model is proposed to describe the random observation delays and packet dropouts, and a robust optimal fusion filter for the addressed networked multisensor fusion systems is designed using the innovation analysis method. The dimension of the designed filter is the same as that of the original system, which helps to reduce computation cost compared with the augmentation method. Moreover, robust reduced-dimension observation-fusion Kalman filters are proposed to further reduce the computation burden. Note that the designed fusion filter gain matrices can be computed off-line, as they depend only on the upper bounds of random delays and on the occurrence probabilities of delays and sensor failures. Some sufficient conditions are presented for stability and optimality of the designed fusion filters, and a steady-state fusion filter is also given for the networked multisensor fusion systems. Simulations show the effectiveness of the proposed fusion filters.
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  • 55
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2015-06-13
    Description: Presents the back cover of this issue of the periodical.
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
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  • 56
    Publication Date: 2015-06-13
    Description: Nonmilitary applications of unmanned air vehicles (UAVs), especially as rescue vehicles to obtain information have increased in recent years. Small UAVs (SUAV) were used in nonmilitary projects, where the focus was on autonomous vehicles; however, microaerial vehicles (MAVs), such as Samarai, make use of radio control, and they were not autonomous vehicles [1]. Autonomous UAVs need sophisticated guidance, control, and navigation systems with conventional aircraft flying processes. Most of current UAVs use ground-station commands for guidance purposes, although autonomous UAVs tend to reduce dependency on ground-station command via autonomous algorithms, such as intelligent methods. Therefore, ground-based air control may not suffice to cover every flying mission. Thus, self-contained, onboard guidance via intelligent methods, such as fuzzy logic, has been considered to achieve this goal. Lockheed Martin???s Intelligent Robotics Laboratory has spent the last 5 years developing an unmanned craft to replicate the air vehicle motion. The idea was based on the motion of maple seed, which whirls softly to the ground after dropping from maple tree. This motion, which is similar to a one-winged helicopter, inspired Lockheed Martin to design a new type of flying vehicles, beneficial in military and nonmilitary surveillance. Maple seeds disperse themselves by auto-rotating passively by using a single wing as they descend from trees, thereby ensuring they are widely scattered. Inspired by these flight concepts, Lockheed Martin Advanced Technology Laboratories developed the Samarai MAV, a 30-cm-radius maple seedlike aircraft that can take off and land vertically and fly laterally, like a helicopter, due to the intrinsic stability of the maple seeds??? nature [2] (Figure 1).
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    Publication Date: 2015-06-13
    Description: Presents the message from the Associate Editor-in-Chief.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: This paper presents a method to estimate steady wind and a maneuvering strategy for loitering under a strong, steady wind. The wind estimation uses Global Positioning System velocity only through a novel filter design without airspeed measurement. The wind estimate is then used to guide the aircraft to crab in a direction perpendicular to the wind, thereby avoiding large changes in flight variables if an orbit-type maneuver is attempted. The proposed method is demonstrated through flight tests.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: We propose biased estimators to find the direction of arrival of emitters present in the mainlobe of a spinning antenna-based electronic intelligence system. The proposed estimators were constructed by using Bayesian techniques and by performing a linear transformation and an affine transformation on the maximum likelihood estimator. From a Monte Carlo simulation and experimental results, we demonstrate that the proposed estimators outperform the limit set by the popular performance benchmark, the Cramer-Rao lower bound.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: A new method was proposed for chirp signal detection and estimation built on the frame-based fast Fourier transform (FFT). The proposed method uses the peak frequency difference between FFT frames to detect a chirp signal and estimate chirp rate. This approach differs from conventional methods and is easy to implement. It generates more accurate chirp rate estimation especially under a low signal-to-noise ratio. Simulation and experimental data are used to verify the proposed methods.
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  • 62
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    Publication Date: 2016-07-19
    Description: The quasimaximum likelihood (QML) estimator of polynomial-phase signals (PPSs) is based on the maximization of the short-time Fourier transform and suffers from aliasing when signals are sampled below the Nyquist sampling rate. In this paper, a phase unwrapping procedure has been proposed as an additional step in the QML to estimate parameters of such signals. Statistical study has shown excellent performance of the proposed approach.
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    Publication Date: 2016-07-19
    Description: In this paper, a direct approach of designing robust weighted fusion steady-state Kalman predictors with uncertain noise variances is presented. Based on the steady-state Kalman filtering theory, using the minimax robust estimation principle, the local and six weighted fusion robust steady-state Kalman predictors are proposed based on the worst case systems with the conservative upper bounds of noise variances. They include the three robust weighted state fusers, two robust weighted measurement fusers, and a modified robust covariance intersection (CI) fuser. Their actual prediction error variances are guaranteed to have the corresponding minimal upper bounds for all admissible uncertainties. A Lyapunov equation approach for robustness analysis and the concept of the robust accuracy are presented and their robust accuracy relations are proved. A simulation example verifies the accuracy relations and robustness.
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  • 64
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: In multitarget tracking, the problem of track labeling (assigning labels to tracks) is an ongoing research topic. The existing literature, however, lacks an appropriate measure of uncertainty related to the assigned labels that has a sound mathematical basis as well as clear practical meaning to the user. This is especially important in a situation where well separated targets move in close proximity with each other and thereafter separate again; in such a situation, it is well known that there will be confusion on target identities, also known as "mixed labeling." In this paper, we specify comprehensively the necessary assumptions for a Bayesian formulation of the multitarget tracking and labeling (MTTL) problem to be meaningful.We provide a mathematical characterization of the labeling uncertainties with clear physical interpretation.We also propose a novel labeling procedure that can be used in combination with any existing (unlabeled)MTT algorithm to obtain a Bayesian solution to the MTTL problem. One advantage of the resulting solution is that it readily provides the labeling uncertainty measures. Using the mixed labeling phenomenon in the presence of two targets as our test bed, we show with simulation results that an unlabeled multitarget sequential Monte Carlo (M-SMC) algorithm that employs sequential importance resampling (SIR) augmented with our labeling procedure performs much better than its "naive" extension, the labeled SIR M-SMC filter.
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  • 65
    Publication Date: 2016-07-19
    Description: Track-before-detect methods jointly detect and track one or several targets from raw sensor measurements. They often require the computation of the measurement likelihood conditional on the hidden state, which depends on the complex amplitudes of the targets. Since these amplitudes are unknown and fluctuate over time, this likelihood must be marginalized over the complex amplitude (i.e., phase and modulus). It has been demonstrated that this marginalization can be done analytically over the phase in the monotarget case. In this article, we first propose to extend the marginalization to the modulus in a monotarget setting, and we show that closed forms can be obtained for fluctuations of type Swerling 1 and 3. Second, we demonstrate that, in a multitarget setting, a closed form can be obtained for the Swerling 1 case. For Swerling 0 and 3 models, we propose some approximation to alleviate the computation. Since many articles consider the case of squared modulus measurements, we also consider this specific case in monoand multitarget settings with Swerling 0, 1, and 3 fluctuations. Finally, we compare the performance in estimation and detection for the different cases studied, and we show the gain, both in detection and estimation, of the complex measurement method over the squared modulus method, for any fluctuation model.
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  • 66
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    Publication Date: 2016-07-19
    Description: When a bistatic inverse synthetic aperture radar (ISAR) system fails to collect complete radar cross section (RCS) datasets, bistatic ISAR (Bi-ISAR) images are usually corrupted using the conventional Fourier transform (FT)-based imaging algorithm. To overcome this problem, this paper proposes a new Bi-ISAR image reconstruction method that includes three steps: suboptimal estimation of parameters regarding the bistatic angle in the Bi-ISAR signal model via an orthogonal matching pursuit-type group-searching scheme, Bi-ISAR signal reconstruction using the estimated parameters, and Bi-ISAR image generation using the FT-based imaging algorithm applied to the reconstructed Bi-ISAR signal. To validate the reconstruction capability of the proposed method, bistatic-scattered field data using the physical optics technique as well as the point-scatterer model are used for Bi-ISAR image reconstruction. The results show that the proposed sparse-recovery-interpolation approach based on the Bi-ISAR signal model reconstruction combined with the classical FT-based algorithm can yield high reconstruction accuracy for incomplete bistatic RCS data compared to conventional numerical interpolation methods and existing direct sparse reconstruction techniques.
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  • 67
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: Bistatic inverse synthetic aperture radar (ISAR) is an efficient geometric configuration of ISAR to image targets traveling along radar transmitter's line of sight, but it has the problem of defocusing and distortion because of the time-varying bistatic angle. In this paper, we derive the defocusing term and the distortion term by expanding the bistatic angle using first-order Taylor expansion. In addition, necessary constraints to neglect the defocusing term are provided via point spread function analysis, and a novel method to eliminate distortion based on linked scatterers is proposed. Simulation results validate our theoretical analysis and show the effectiveness of our method.
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  • 68
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: Micro-Doppler (MD)-based target classification capabilities of automotive radars can provide high reliability and short latency to future active safety automotive features. A large number of pedestrians surrounding a vehicle in practical urban scenarios mandate prioritization of their treatment level. Distinguishing between relevant pedestrians that are crossing the street or are within the vehicle path and those that are on the sidewalks and are moving along the vehicle route can significantly minimize the number of vehicle-to-pedestrian accidents. This work proposes a novel technique for estimating a pedestrian direction of motion that treats pedestrians as complex distributed targets and utilizes their MD radar signatures. The MD signatures are shown to be indicative of pedestrian direction of motion, and a supervised regression is used to estimate the mapping between the directions of motion and the corresponding MD signatures. In order to achieve higher regression performance, a state-of-the-art sparse dictionary learning-based feature extraction algorithm was adopted from the field of computer vision by drawing a parallel between the Doppler effect and the video temporal gradient. The performance of the proposed approach is evaluated in practical automotive scenario simulations, where a walking pedestrian is observed by a multiple-input/multiple-output automotive radar with a two-dimensional rectangular array. The simulated data was generated using the statistical Boulic-Thalman human locomotion model. Accurate direction of motion estimation was achieved by using support vector regression and multilayer perceptron-based regression algorithms. The results show that the direction estimation error is less than 10° in 95% of the tested cases for pedestrian at a range of 100 m from the radar.
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  • 69
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    Publication Date: 2016-07-19
    Description: This paper proposes a novel phase synchronization technique that enables beamforming with multiple resource-limited spacecraft in space and capitalizes on their spatial geometry. The proposed technique employs an external beacon to obviate the need for explicit time synchronization and reduces the accuracy requirements on localization. Results show that subcentimeter (subnanosecond)-level phase synchronization can be achieved with localization accuracy in the order of meters.
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  • 70
    Publication Date: 2016-07-19
    Description: The use of chirp signals in modern radar and ranging systems have numerous benefits. They are extensively used to improve signal-to-noise ratio and range resolution. The performance capabilities of these signals are directly related to their time-bandwidth product, i.e., the duration and bandwidth of the pulse. Ultra-wideband chirp signals are further desirable because they span a large bandwidth, making them resistant to narrowband environmental interference. The accurate detection and measurement of high chirp signals is difficult due to the necessity of a high-sampling analog-digital converter, a target measurement platform with high computational power, and a time-of-arrival (TOA) estimator with high temporal resolution. The difficulty of the problem is further compounded with the requirement that no a priori knowledge of the signal, noise, or operating environment is known. This paper presents a practical approach and implementation of a high linear chirp rate receiver and TOA estimator pair capable of detecting and measuring stationary radio frequency pulses as well as linear chirp rates up to 1.18 GHz in 400 ns. The high-resolution TOA algorithm and linear chirp receiver have been prototyped, synthesized, and placed and routed for a Virtex 6 SX475 FPGA.
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  • 71
    Publication Date: 2016-07-19
    Description: In this paper, an impact angle control guidance law, which considers simultaneously the impact angle and seeker's look angle constraints, is proposed for a constant speed missile against a stationary target. An optimal control theory with state variable inequality constraint is used to design the guidance law, for which a control energy performance index with the weighting function of the range-to-go is minimized. Various forms of guidance and trajectory shaping are possible by selecting a proper gain of the weighting function. To handle the seeker's look angle limits when the missile trajectory is highly curved by controlling the impact angle, the proposed guidance law generates three types of acceleration commands as the guidance phases: the first acceleration command for an initial guidance phase makes an initial seeker's look angle reach the maximum look angle; the second one for a midguidance phase maintains the maximum look angle; the final one for a terminal guidance phase intercepts the target with the desired impact angle. The performance of the proposed guidance law was investigated with nonlinear simulations for various engagement conditions.
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  • 72
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: This paper presents a means of near asteroid hovering of a rigid spacecraft in the asteroid body-fixed frame with parameter variations and external disturbances. An adaptive finite-time control scheme is proposed, where the upper bounds of the parametric uncertainties and disturbances are not required for controller design. The detailed design principles and a rigorous stability analysis are provided. Finally, a body-fixed hovering maneuver is employed in numerical simulation to verify the effectiveness of the proposed strategy.
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    Publication Date: 2016-07-19
    Description: In global navigation satellite system (GNSS) receivers, the acquisition process is the first stage of the signal processing module. It consists of assessing the presence of GNSS signals and providing a rough estimation of the incoming signal parameters: the Doppler frequency and the code delay. However, the presence of bit sign transitions affects receiver performance in signal acquisition detection. This article focuses on the bit transition and its impact on the acquisition performance by providing a general mathematical study and an illustration for two GNSS signals: the global positioning system legacy civil signal (GPS L1 C/A) and Galileo E1 open service (OS). This study is applicable to a terrestrial user in a constraint environment. Furthermore, the presented results are mathematical models of the probability of detection in the presence of bit sign transitions (only one potential bit sign transition per integration interval), and potential uncertainties on the Doppler frequency and code delay. These do not result from empirical acquisition of real signals.
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    Publication Date: 2016-07-19
    Description: This paper investigates the problem of ground vehicle tracking with ground-moving target indicator (GMTI) radar. In practice, the movement of ground vehicles may involve several different maneuvering types (acceleration, deceleration, standstill, etc.). Consequently, the GMTI radar may lose measurements when the radial velocity of the ground vehicle is below a threshold, i.e., falling into the Doppler blind region. In this paper, to incorporate the information gathered from normal measurements and knowledge on the Doppler blindness constraint, we develop an enhanced particle filtering method for which the importance distributions are inspired by a recent noise-related Doppler blind (NRDB) filtering algorithm for GMTI tracking. Specifically, when constructing the importance distributions, the proposed particle filter takes the advantages of the efficient NRDB algorithm by applying the extended Kalman filter and its generalization for interval-censored measurements. In addition, the linearization and Gaussian approximations in the NRDB algorithm are corrected by the weighting process of the developed filtering method to achieve a more accurate GMTI tracking performance. The simulation results show that the proposed method substantially outperforms the existing methods for the GMTI tracking problem.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: Sets that are defined either from closed contours or from a set of points are generic descriptors for several kinds of objects in binary images. In this paper, we derive a novel model in the space of sets and design an observer for the proposed model to estimate the depth and orientation of planar objects from a camera. This problem is well known as "structure from motion." When the objects are only partially projected on the image plane of the camera, our model makes object depth and orientation estimation possible without feature tracking and matching between distinct image frames (i.e., the so-called correspondence problem), which is an advantage over the image moments-based model. However, the proposed model fails in some situations (the failures can be seen as brief instabilities), and it is not always continuous. To compensate for these drawbacks, we designed a fast observer based on L 1 control theory with a binary signal for the proposed model. Stability analysis with respect to a certain asymptotic instability ratio is also presented in this paper. The effectiveness of the proposed model and observer is demonstrated through simulations and experimental results.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: Presents the front cover/table of contents for this issue of this publication.
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    Publication Date: 2016-07-19
    Description: A novel differential vector phase locked loop (DVPLL) is derived that takes global navigation satellite system (GNSS) code-phase and carrier-phase measurements from a base station and uses them to maintain a position with centimeter-level accuracy directly in the vector tracking loop of a rover receiver. The navigation filter uses five state variables, three position and two clock states, to create the replica code and carrier measurements for a static test. There are no individual channel states or feedback mechanisms. Closing the individual loops solely through the navigation filter makes this a purely vector method. For short baselines, where differential atmospheric errors are small, the DVPLL can be used on single-frequency data. An L1-only live-sky static test was performed using the method, resulting in a three-dimensional accuracy of 1.3 mm for a zero-baseline and 5.3 mm for an 18.5 m baseline.
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    Publication Date: 2016-07-19
    Description: An adaptive actuator failure and disturbance compensation scheme is developed for attitude tracking control of spacecraft. The proposed scheme consists of a composite parameter adaptation design that incorporates an adaptive backstepping feedback control law and an adaptive feedforward actuator failure compensator; it can guarantee the overall closed-loop system stability and asymptotic tracking. Illustrative simulation results of an application to a spacecraft model show that the designed actuator failure compensation controller ensures system stability and tracking performance.
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    Publication Date: 2016-07-19
    Description: Track-before-detect (TBD) is a popular incoherent energy integration technique aimed at improving detectability of weak targets. A number of studies are available in the literature demonstrating its efficacy against disturbance (whether noise or clutter), but most of them refer to synthetic data, i.e., relying on computer simulations. In this paper, we tackle the problem of assessing the TBD performance with real data and in a particularly severe clutter environment, i.e., sea-clutter. Precisely, using a set of real data from a ground-based sea-search radar, we implement TBD directly on the plot-lists coming from the radar plot extractor (this be can done with acceptable complexity by using an ad hoc dynamic programming algorithm), and demonstrate its effectiveness in reducing sea-clutter. As a further contribution, we also develop an improved decision logic for plot confirmation.
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    Publication Date: 2016-07-19
    Description: The concept of more electric aircraft leads to increases in the amount of electrical loads, as well as the power consumed in the aircraft of the future. To utilize the power feeders, more symmetric, load balancing methods can be applied to swap loads between different phases of an alternating current (AC) feeder, or even between different power feeders. If the load balancing system reacts to measurement data during the flight in real time, the cable power losses and return network power losses, too, are reduced. In addition, the rate of power management interventions decreases. The load balancing problem in three-phase systems is a mixed-integer nonlinear nondifferentiable optimization problem, which is typically solved by elaborate and time-consuming nonreal-time optimization algorithms. The AC loads in aircraft have different power factors, which result in currents described by complex numbers. To determine a load swapping scheme in real time starting from a given load allocation with sparse swapping, new heuristics are presented. One heuristic is specially designed to solve the phase swapping problem by shifting single-phase loads between phases of a feeder. Another heuristic, based on the first one, is enhanced to more than one three-phase feeder and considers the swapping of single-phase and three-phase loads. The heuristics are tested by simulations of a comprehensive case study based on real measurement data from a modern passenger aircraft. To prove the efficiency of the new concepts, a test bench has been built, and several experiments successfully conducted.
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    Publication Date: 2016-07-19
    Description: The probability hypothesis density (PHD) filter is an efficient algorithm for multitarget tracking in the presence of nonlinearities and/or non-Gaussian noise. The sequential Monte Carlo (SMC) and Gaussian mixture (GM) techniques are commonly used to implement the PHD filter. Recently, a new implementation of the PHD filter using B-splines with the capability to model any arbitrary density functions using only a few knots was proposed. The spline PHD (SPHD) filter was found to be more robust than the SMC-PHD filter because it does not suffer from degeneracy, and it was better than the GM-PHD implementation in terms of estimation accuracy, albeit with a higher computational complexity. In this paper, we propose a multiple model extension to the SPHD filter to track multiple maneuvering targets. Simulation results are presented to demonstrate the effectiveness of the new filter.
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  • 82
    Publication Date: 2016-07-19
    Description: This paper proposes an optimal control framework for the climb and descent economy modes of a flight management system (FMS) yielding a solution that can be implemented in real-time flights below the drag divergence Mach number. The problem is formulated as the optimization of a functional that trades off the fuel- and time-related costs of a flight as a function of a (crew-supplied) parameter called the cost index. The work builds on previous research of the authors for the cruise phase and extends it to the climb and descent phases of flight. More specifically, for both climb and descent, it is found that suboptimal solutions can be obtained as the positive real roots of a fifth-degree polynomial lying inside the flight envelope, which can be found using fast-converging algorithms such as Newton's method. The main contributions of this work are threefold. First, the proposed method gives physical insight because there is an analytical expression for each coefficient of the polynomial. Second, this approach eliminates the need to have a performance database in the system, thus making its implementation faster in real-time. Third, the solution exhibits the same behavior of airborne FMS units as a function of the cost index, which is justified in this paper based on Bellman's principle of optimality. This justification is an important theoretical contribution of the paper. A validation of the approximate solution is obtained using the shooting method to compute the optimal trajectories and compare them against the proposed suboptimal solution. Simulation results show that, for an Airbus A320 model and for a Gulfstream-IV aircraft model, the relative error of the suboptimal trajectories when compared to the optimal trajectories is small for climb and descent trajectories, respectively.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: An X-band, 15-W-class gallium nitride (GaN) solid-state power amplifier (SSPA) for the 50-kg-class ultrasmall deep-space probe PROCYON has been demonstrated in deep space for the first time. PROCYON was launched on December 3, 2014, as a subpayload of the Hayabusa 2 spacecraft. The GaN SSPA consists of three-stage, single-end amplifiers. The final-stage GaN high-power amplifier, which dominates the characteristics of the SSPA, achieves a maximum drain efficiency of 55.8% at 8.4 GHz. The fabricated SSPA using this GaN high-power amplifier has dimensions of 150 x 120 x 62 mm and weighs 1.5 kg, and its space applicability was confirmed through space environmental tests. For more than 2450 h of continuous operation in deep space, the GaN SSPA has achieved an average output power of 41.7 dBm (14.8 W), with standard deviation of 0.12 dB, maximum overall efficiency of 35.7%, and average efficiency of 33.8%. To the authors' knowledge, this is the highest efficiency of all proven X-band onboard SSPAs.
    Print ISSN: 0018-9251
    Electronic ISSN: 1557-9603
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 84
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: In this paper, an adaptive cubature Kalman filter (ACKF) is proposed to improve the performance of the conventional cubature Kalman filter. The ACKF uses a new cubature rule that combines a third-degree spherical rule with an adaptive higher degree radial rule along the directions of larger uncertainty. More accurate and robust results can be obtained with slightly more cubature points than the conventional third-degree cubature Kalman filter (CKF). Compared with other high-degree Gaussian filters, ACKF uses much fewer points but maintains very close performance. A target tracking problem is used to demonstrate the effectiveness of the proposed filter.
    Print ISSN: 0018-9251
    Electronic ISSN: 1557-9603
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 85
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-07-19
    Description: We propose a simple method for estimating crystal oscillator g-sensitivity in inertially aided Global Navigation Satellite System (GNSS) receivers. It does not require any specific equipment, like GNSS signal simulators or rate tables. The method is based on analyzing closed-loop phase tracking errors. This enables us to utilize the actual GNSS signal as the frequency reference, despite the presence of an unknown Doppler shift in it. The method has been successfully applied to the calibration of an oven-controlled crystal oscillator.
    Print ISSN: 0018-9251
    Electronic ISSN: 1557-9603
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 86
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: Presents the front cover for this issue of the publication.
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 87
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: Lists upcoming AESS society meetings and conferences.
    Print ISSN: 0885-8985
    Electronic ISSN: 1557-959X
    Topics: Electrical Engineering, Measurement and Control Technology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 88
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: An optimal reactive power dispatch strategy is proposed to minimize the total electrical losses of a wind farm (WF), including not only losses in the transmission cables and wind turbine (WT) transformers, but also losses inside wind energy generation systems. The reactive power dispatch inside a WT uses optimal splitting strategy over the stator and the grid side converter (GSC), which aims to minimize the total loss of the wind energy generation system, including the generator, the converters, and the filters. Optimization problems are formulated based on established loss models and WT reactive power limits. A WF is carefully designed and used for case studies. Wake effect is considered when calculating the active power at each WT. The total losses of the WF are calculated by implementing the proposed strategy at different wind speeds and reactive power references. The simulation results show the effectiveness of the proposed strategy.
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 89
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 90
    Publication Date: 2016-06-21
    Description: Multibody wave energy converters are composed of several bodies interconnected by joints. Two different formulations are adopted to describe the dynamics of multibody systems: the differential and algebraic equations (DAEs) formulation, and the ordinary differential equations (ODEs) formulation. While the number of variables required for the description of the dynamics of a multibody system is greater in the DAE formulation than in the ODE formulation, the ODE formulation involves an extra computational effort in order to describe the dynamics of the system with a smaller number of variables. In this paper, pseudo-spectral (PS) methods are applied in order to solve the dynamics of multibody wave energy converters using both DAE and ODE formulations. Apart from providing a solution to the dynamics of multibody systems, pseudo-spectral methods provide an accurate and efficient formulation for the control of multibody wave energy converters. As an application example, this paper focuses on the dynamic modeling of a three-body hinge-barge device, where wave-tank tests are carried out in order to validate the DAE and ODE models against experimental data. Comparison of the ODE and DAE PS methods against a reference model based on the straightforward (Runge-Kutta) integration of the equations of motion shows that pseudo-spectral methods are computationally more stable and require less computational effort for short time steps.
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 91
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: Optimal and simultaneous siting and sizing of distributed generators and capacitor banks in distribution systems have attracted a lot of attention from distribution companies. The placement and capacity of these devices have direct effects on the system’s performance. This paper presents a model for the simultaneous allocation of capacitor banks and distributed generation, which takes into account the stochastic nature of distributed generation. To solve the model presented, we propose an efficient hybrid method based on Tabu search and genetic algorithms. The hybrid method is applied to a well-known system in literature.
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 92
    Publication Date: 2016-06-21
    Description: In this paper, distributed energy storage (DES) devices, like batteries and ultra-capacitors, are used to alleviate detrimental impacts of high penetration photovoltaic (PV) resources on distribution systems. The impacts are studied at mainly two time resolutions—one minute and one hour. To determine accurately the size of the required DES for the purpose of mitigating the impacts of large-scale distributed PV, sizing procedures based on OpenDSS are proposed. After determining the total size of the required DES, optimization techniques can be used to choose the optimal locations for the DES along the feeder, which is a continuous optimization problem taking into account equality constraints of the AC power flow. The continuity of the problem and the radial network structure make it possible to apply a convex optimization technique called second order cone programming (SOCP) relaxation to obtain the globally optimal solution and avoid the problem of NP-hardness. The exactness of the introduced SOCP relaxation is sensitive to the chosen objective function and additional quadratic equalities. The necessary and sufficient condition of exactness for the SOCP relaxation of the DES optimal allocation and operation in radial distribution systems is studied. The proposed methods are applied to an actual feeder in the southwestern US with high penetration of PV using actual measured data. The simulation results demonstrate the efficacy of the proposed approaches.
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  • 93
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: This paper proposes an integrated stochastic day-ahead scheduling model to dispatch hourly generation and load resources and deploy flexible ramping for managing the variability of renewable energy system. A comprehensive framework for the natural gas transportation network is considered to address the dispatchability of a fleet of fuel-constrained natural gas-fired units. System uncertainties include the day-ahead load and renewable generation forecast errors. Illustrative examples demonstrate that the real-time natural gas delivery can directly impact the hourly dispatch, flexible ramp deployment, and power system operation cost. Meanwhile, the demand side participation can mitigate the dependency of electricity on natural gas by providing a viable option for flexible ramp when the natural gas system is constrained.
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  • 94
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: If a large disturbance occurs in a power grid, two auxiliary loops for the inertial control of a wind turbine generator have been used: droop loop and rate of change of frequency (ROCOF) loop. Because their gains are fixed, difficulties arise in determining them suitable for all grid and wind conditions. This paper proposes a dynamic droop-based inertial control scheme of a doubly-fed induction generator (DFIG). The scheme aims to improve the frequency nadir (FN) and ensure stable operation of a DFIG. To achieve the first goal, the scheme uses a droop loop, but it dynamically changes its gain based on the ROCOF to release a large amount of kinetic energy during the initial stage of a disturbance. To do this, a shaping function that relates the droop to the ROCOF is used. To achieve the second goal, different shaping functions, which depend on rotor speeds, are used to give a large contribution in high wind conditions and prevent over-deceleration in low wind conditions during inertial control. The performance of the proposed scheme was investigated under various wind conditions using an EMTP-RV simulator. The results indicate that the scheme improves the FN and ensures stable operation of a DFIG.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 95
    Publication Date: 2016-06-21
    Description: In this paper, the two-level hierarchical scheme, which consists of wide area centralized and local controls of the power oscillation damper (POD) installed with the doubly-fed induction generator (DFIG) wind turbine and the power system stabilizer (PSS) has been proposed for robust power oscillation damping. In the wide area level, the centralized POD and PSS has received the input signals from synchronized phasor measurement units (PMUs). The geometric measures of controllability and observability have been applied to select the suitable DFIG and synchronous generator (SG) for stabilizing the target oscillation modes, the proper input signals of the centralized POD and PSS, and the location of PMUs. In the local level, the suitable DFIG and SG have been equipped with POD and PSS, respectively. In the parameters optimization of POD and PSS, the practical issues such as damping performance, controller structure, communication latency, and robustness against system uncertainties have been considered. The controller efficiency and resiliency of the proposed controller have been evaluated in comparison with other controllers by eigenvalue analysis and nonlinear simulation for a wide range of operating conditions, line outage contingencies, severe faults, and communication failure.
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  • 96
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: This paper describes a method for optimal scheduling of hydropower systems for a profit maximizing, price-taking, and risk neutral producer selling energy, and capacity to separate and sequentially cleared markets. The method is based on a combination of stochastic dynamic programming (SDP) and stochastic dual dynamic programming (SDDP), and treats inflow to reservoirs and prices for energy and capacity as stochastic variables. The proposed method is applied in a case study for a Norwegian watercourse, quantifying the expected changes in schedules, and water values when going from an energy-only market to a joint treatment of energy and reserve capacity markets.
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  • 97
    Publication Date: 2016-06-21
    Description: In this paper and its companion, the identification of mathematical models describing the behaviour of wave energy devices (WECs) in the ocean is investigated through the use of numerical wave tank (NWT) experiments. This paper deals with the identification tests used to produce the data for the model identification. NWTs, implemented using computational fluid dynamics (CFD), are shown as an effective platform to perform the identification tests. The design of the NWT experiments, to ensure the production of information-rich data for the model identification, is discussed. A case study is presented to illustrate the design and implementation of NWT experiments for the identification of WEC models.
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    Topics: Energy, Environment Protection, Nuclear Power Engineering
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  • 98
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: Optimum torque (OT)-based maximum power point tracking (MPPT) is widely used in high power turbines because of its simplicity. Several recent improvements claim better response speeds by augmenting the basic OT algorithm with a suitably scaled inertial torque. However, the underlying dynamic model for all these improved methods is premised on a rigid shaft, which ignores all torsional behavior. This lacuna is addressed in this paper, where a small-signal system description is developed considering a more accurate flexible shaft model. It is shown that the improvements have three possible forms, the third being proposed in this paper. Close-loop stability with each of these is analytically investigated using this accurate small-signal model. It is also proved that one of the reported approaches causes system instability while attempting even moderate improvement over the OT method. The problems in realization of the other two forms are highlighted and a realizable alternative proposed, which requires no additional sensor. Design of the proposed approach is presented in appropriate detail. It is analytically established that the proposed method ensures superior dynamic response. All analytical conclusions are validated by numerical simulations.
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  • 99
    Publication Date: 2016-06-21
    Description: Power generation uncertainty is an important characteristic of variable generation (VG) platforms, such as wind and solar power, which brings additional operational costs to the power systems. To manage this uncertainty, responsibilities should be properly allocated to encourage good behaviors of system participants, especially the VG producers. Currently, the imbalance-cost-based mechanism is most commonly used for uncertainty management. Based on this method, we consider a new mechanism in this paper for capturing the uncertainty, which may achieve a better mechanism performance. The basic idea is to allow producers to purchase generation intervals (GIs) for their potential production output. The analysis presented in this paper indicates that producers can be very responsive to this mechanism. With the proper pricing policies, producers can be encouraged to provide additional information on upcoming uncertainties to the system operators. Additionally, three strategies for pricing GIs are included in this paper. Case studies are used to demonstrate the application of the mechanism as well as its effectiveness.
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  • 100
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016-06-21
    Description: The paper proposes a gossip algorithm-based architecture for managing power flows on radial distribution grids applying decentralized management of demand. Demand flexibility is associated with a cost-like utility function expressing the inconvenience caused by curtailment. Every node of the distribution grid participates in power flow management by sending locally measured and calculated values to its neighboring nodes following a peer-to-peer architecture. The proposed algorithm is based on the application of gossip algorithms to estimate locally critical physical quantities by reaching a global consensus. More specifically, the solution implements gossip algorithms to achieve consensus in aggregated demand and in minimum cost for curtailment of flexible loads/increase of controllable distributed generators.
    Print ISSN: 1949-3029
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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