ALBERT

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.

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.

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.

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.

Description: Provides a listing of the editors, board members, and current staff for this issue of the publication.

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.

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.

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.

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%.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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%.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Description: The objective of this research was to develop and compare various airfoil precomputational parameterization and analysis techniques for aerostructural optimization of wind turbine blades. The airfoils along the blade were added as optimization design variables through precomputational parameterization methods using thickness-to-chord ratios and blended airfoil family factors. The airfoils’ aerodynamic performance was analyzed with three methods of increasing fidelity: a panel method (XFOIL), Navier–Stokes-based computational fluid dynamics (RANS CFD), and wind tunnel data. The optimizations minimized mass over annual energy production ( $m/AEP$ ) and thereby approximated the minimization of cost of energy. The results were compared to the NREL 5-MW reference turbine and a conventional optimization where the airfoils were fixed. Results showed an average $m/AEP$ reduction of 1.7% over conventional optimization methods. The primary benefit in adding the airfoil shape was through an increase in annual energy production (1.6%) with a similar decrease in turbine mass (1.8%). Using the precomputational airfoil parameterization methods provided significant reductions in the cost of energy with relatively minor additional computational cost.

Description: This paper proposes a co-ordinated four-loop switching controller (SC) for the doubly fed induction generator (DFIG) to improve the transient stability of wind power penetrated power systems. A short-term resilience index is introduced, and it reflects the dynamics of both system frequency and load bus voltage. A four-loop SC is driven by the four outputs of a DFIG, namely, the rotor speed deviation, the reactive power output of stator winding, the reactive power transferred through grid-side converter, and the DC-link voltage, respectively. Referring to a state-dependent switching strategy, the four-loop SC switches between a logic-based bang–bang constant funnel controller (LBCFC) and a vector control theory-based conventional controller (CC) in each control loop. The LBCFC is robust to system nonlinearities, uncertainties, and external disturbances. The control signal of the LBCFC is bang–bang with the upper and lower limits of control variables. Simulation studies are undertaken in a modified IEEE 16-generator 68-bus power system, in which four DFIG-based wind farms are penetrated to provide 9.94% power supply. The performance of the four-loop SC is evaluated in aspects of the integral control of the DFIG and the resilience enhancement of the multimachine power system, respectively.

Description: This paper investigates a control strategy for a wind farm with the direct-driven permanent-magnet synchronous generators (PMSG)-based wind turbines and the fixed speed induction generators (FSIG)-based wind turbines under unbalanced grid voltage condition. By controlling the PMSG-based wind farm to inject negative-sequence current for decreasing voltage unbalance factor (VUF) at point of common coupling (PCC), the double grid frequency oscillations in electromagnetic torque, active, and reactive power output from the FSIG-based wind farm can be suppressed. In this paper, the maximum amplitude of the negative-sequence current provided by the PMSG-based wind farm under different average active power output and different VUF conditions is deduced, and the impacts of its phase angle on the VUF mitigation control effect are further studied. The improved control strategy of injecting negative-sequence current from the PMSG-based wind farm by the modified negative-sequence voltage and current double closed-loop control system is then developed. Finally, the correctness of theoretical analysis and the effectiveness of the proposed control strategy are validated by the experimental results.

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 experiments. When the wave amplitude and the WEC displacement are not negligible with respect to the WEC dimensions, nonlinear hydrodynamic effects may appear, and the accuracy of linear hydrodynamic models is reduced, leading to the necessity of introducing some nonlinearities in the model structure. This paper proposes, for WEC modelling, the use of discrete-time nonlinear autoregressive with exogenous input (NARX) models, as an alternative to continuous-time models. Techniques of model identification are also explained and applied to a case study.

Description: Wind turbine power curves do not consider specific weather conditions, wind shear, turbulence effects of the location where the turbine is going to be installed, or its age. A true power curve is obtained by analyzing data from an installed wind turbine over a year. Here, a model for a true power curve is proposed, considering a normal distribution for each range of wind speed data. Furthermore, a Monte Carlo-based simulation technique is proposed to reproduce data following the normal-based model. The main use of the model is to simulate data to complete lacking real data or to perform long-term assessments. The model was checked with data from two wind turbines at the Sotavento experimental wind farm in the northwest of Spain.

Description: This paper discusses the control of large-scale grid-connected photovoltaic power plant (GCPPP) operating under unbalanced grid voltages. The positive and negative sequences of the grid currents need to be controlled to regulate the power injected into the grid during unbalanced grid voltages. This paper shows that the use of conventional proportional-integral-based controllers compromises stability and dynamic performance of the inverter. The reason is the delays introduced by the filters needed to extract the sequences of the transformed grid currents. Because of such delays, there is a strong restriction on choosing the parameters for the current and voltage controllers, which forces the GCPPP to perform slowly. This can be improved by using resonant controllers instead, which avoid the need for filtering the transformed grid currents. Additionally, a new overcurrent protection is proposed for the GCPPP when it is providing grid voltage support during voltage sags. Simulation and experimental results are presented to evaluate and compare the performance of the GCPPP when operating with the different controllers.

Description: This paper proposes a novel probabilistic transient stability constrained optimal power flow (P-TSCOPF) model to simultaneously consider uncertainties and transient stability for power system preventive control. While detailed wind generator model with rotor flux magnitude and angle control strategy is used to describe the dynamic behaviors of wind generators, uncertain factors with correlations, such as probabilistic load injections, stochastic fault clearing time, and multiple correlated wind generations, are also included to form a representative P-TSCOPF model. A new GSO-PE approach, consisting of an improved group search optimization (GSO) and $2m + 1$ point estimated (PE) method with Cholesky decomposition, is then designed to effectively solve this challenging P-TSCOPF problem. The proposed P-TSCOPF model and GSO-PE solution approach have been thoroughly tested on a modified New England 39-bus system with correlated uncertain wind generations. Comparative results with Monte Carlo (MC) simulations have confirmed the validity of the P-TSCOPF model and demonstrated the effectiveness of GSO-PE method.

Description: Frequency regulation is critical to the successful operation of remote wind–diesel electrical grids. When the grid is in ‘wind–diesel’ mode, frequency regulation is (classically) the sole duty of the diesel electric generator (DEG). An alternative approach is proposed whereby responsibility for frequency regulation is shared by the DEG and a network of autonomous distributed secondary loads (DSLs) consisting of electric thermal storage (ETS) devices. This allows surplus wind to be distributed to residential consumers (as space heat) without the need for a centralized communication network. Numerical modeling of system dynamics with active DSLs is conducted using a SIMULINK wind–diesel hybrid test bed model. The effects of controller gain, installed capacity, switching time and unit coordination timing on frequency and voltage regulation is explored. It is shown that the DSLs can improve frequency regulation in wind–diesel mode while providing storable thermal energy to distributed consumers.

Description: Appropriate wind speed modeling for generating synthetic wind speed data is crucial in microgrid reliability evaluation studies. This paper proposes a 2-D wind speed statistical model based on historical wind speed data. The first dimension of the proposed wind model focuses on the probability distribution on the time duration of different wind speed scales, while the second dimension focuses on the probability distribution of wind speed in each wind speed scale. Unlike traditional wind speed models, the proposed model can simultaneously deal with the probabilistic characteristics of wind speed and wind time duration. This paper also presents a 2-D wind model-based data sampling method, and incorporates it into the microgrid reliability assessment algorithm. Using historical wind speed data in Tianjin, China, it shows that the proposed 2-D wind speed statistical model helps to fully simulate the volatility of wind energy. Furthermore, the proposed wind speed model is applied on the microgrid reliability evaluation study, which shows that the proposed model can be effectively utilized by planners to conduct reliability evaluation for microgrid.

Description: Wind generation is growing fast worldwide. The stochastic variation of large-scale wind generation may impact the power systems in almost every aspect. Probabilistic analysis method is an effective tool to study power systems with random factors. In this paper, a systematic nonlinear analytical probabilistic method is proposed to evaluate the possible effect of random wind power generation on power system small signal stability. A second-order polynomial is proposed to approximate the nonlinear relationship between the wind generation and the damping of a particular dynamic mode, such as the dominant mode. Gaussian mixture model formulates wind uncertainty in a uniform way. Spectral theorem is adopted to reshape the second-order polynomial into a form without cross-product terms. Cholesky decomposition is used to eliminate correlations among outputs of different wind farms. Thereafter the cumulative distribution function (CDF) of the damping ratio with respect to random wind power is consequently constructed. Numerical simulations are carried out in the IEEE standard test system. The proposed method is verified with higher accuracy than the traditional linearized method. Meanwhile, it is much more time-saving in calculation than Monte Carlo simulation.

Description: In this paper, a distributed local control scheme for dc microgrid is proposed along with the basic droop control. It eliminates the limitations of droop control when the distributed generators are geographically distributed, for which, the line resistances cannot be neglected. Effects of line inductance and constant power loading (CPL) are investigated by analyzing the voltage tracking transfer function for single source system. Stability of two sources single load microgrid with proposed controller is investigated. Simulated responses are presented for two sources single load microgrid (for the sake of simplicity) to depict the proper load sharing and voltage improvement capability of the proposed control method with the consideration of line resistances. However, this can be extended to multiple-source multiple-load configuration connected to the dc bus. A comparison of the result is presented to show the better performance of the proposed control scheme as compared to the conventional droop control and hierarchical secondary control. The interconnected operation of the microgrid is also investigated to show the applicability of the proposed control in the interconnected mode. A centralized controller in each area is used to make the tie-line power flow zero at steady state.

Description: There has been an increasing interest in transformerless inverter for grid-tied photovoltaic (PV) system due to low cost, high efficiency, light weight, etc. Therefore, many transformerless topologies have been proposed and verified with real power injection only. Recently, almost every international regulation has imposed that a definite amount of reactive power should be handled by the grid-tied PV inverter. According to the standard VDE-AR-N 4105, grid-tied PV inverter of power rating below 3.68KVA, should attain power factor (PF) from 0.95 leading to 0.95 lagging. In this paper, a new high efficiency transformerless topology is proposed for grid-tied PV system with reactive power control. The new topology structure and detail operation principle with reactive power flow is described. The high frequency common-mode (CM) model and the control of the proposed topology are analyzed. The inherent circuit structure of the proposed topology does not lead itself to the reverse recovery issues even when inject reactive power which allow utilizing MOSFET switches to boost the overall efficiency. The CM voltage is kept constant at mid-point of dc input voltage, results low leakage current. Finally, to validate the proposed topology, a 1 kW laboratory prototype is built and tested. The experimental results show that the proposed topology can inject reactive power into the utility grid without any additional current distortion and leakage current. The maximum efficiency and European efficiency of the proposed topology are measured and found to be 98.54% and 98.29%, respectively.

Description: Wave energy farms may cause voltage flicker on the local grid to which they will be connected due to the strong fluctuations that their output power may present. IEC standard 61400-21 describes methods for estimating the flicker level for different short-circuit ratios as well as for different numbers of devices composing the farm. This method was initially developed for wind farms but is applicable to wave energy farms as well. However, besides the short-circuit ratio and the number of devices composing the farm, the grid impedance angle has also a strong influence on flicker. Despite this, no method exists in the literature for estimating flicker as a function of this variable. This paper presents the results of a study intended to fill this gap by focusing on developing a simplified method for estimating the flicker level induced by a wave energy farm as a function of the grid impedance angle. The results obtained through this method are compared with those obtained from numerical load flow simulations performed with PowerFactory. These simulations were based on experimental power output time series of a wave energy prototype deployed at sea as part of the European CORES project. The voltage profiles thus generated were then processed by means of a flickermeter compliant with IEC standard 61000-4-15.

Description: A novel monotonic strategy following a consistent charging/discharging direction for each individual battery connected in parallel to form a large-scale battery energy storage system (BESS) is proposed in this paper. The BESS is coordinated with a large wind farm to smooth out the intermittent nature of the farm’s output fed to an electricity grid. The strategy is used to optimize the capacity of each battery reducing the system’s capital cost. The strategy also prolongs the battery’s lifetime and consequently minimizes the system’s operating cost. It is shown that the optimal capacity of the battery decreases as their number increases. Moreover, the optimal capacity of the BESS tends to some positive limit as the number of batteries approaches infinity. A rigorous proof of the mathematical theory underlying the proposed strategy and associated optimization are given in the paper. The effectiveness of the strategy is confirmed with data analysis taken from an actual wind farm. The strategy is generic enough to be applicable to other intermittent generation sources such as solar PV farms.

Description: In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS)-based distributed control model for droop-controlled MGs is proposed. The proposed control model consists of two layers, where the bottom layer is the electrical distribution MG, while the top layer is a communication network composed of agents. Moreover, agents on the communication network exchange the information acquired from DGs with neighbors, and calculate set points for DGs they connect to, according to the control laws. Furthermore, a theorem is demonstrated, which yields a systematic method to derive the control laws from a given communication network. Finally, three cases are carried out to test the performance of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the effectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model is also verified.

Description: Wind power generation is to play an important role in supplying electric power demand, and will certainly impact the design of future energy and reserve markets. Operators of wind power plants will consequently develop adequate offering strategies, accounting for the market rules and the operational capabilities of the turbines, e.g., to participate in primary reserve markets. We consider two different offering strategies for joint participation of wind power in energy and primary reserve markets, based on the idea of proportional and constant splitting of potentially available power generation from the turbines. These offering strategies aim at maximizing expected revenues from both market floors using probabilistic forecasts for wind power generation, complemented with estimated regulation costs and penalties for failing to provide primary reserve. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of these offering strategies. An important conclusion is that, even though technically possible, it may not always make sense for wind power to aim at providing system services in a market environment.

Description: In addition to energy, a concentrating solar power (CSP) plant with thermal energy storage (TES) could also provide ancillary service (AS) in the reserve and regulation markets. On one hand, providing AS contributes to the flexibility of the power systems and increases the revenue of CSP plants. On the other hand, the flexibility of CSP plants to accommodate solar energy, which is of great uncertainty, might be significantly weakened by an inappropriate offering strategy, e.g., offering excessive AS. Insufficient flexibility might cause massive solar energy curtailment and reduce the potential revenue. This paper develops a general model framework on the optimal offering strategy for CSP plants in joint day-ahead energy, reserve and regulation markets, which is robust for solar energy uncertainty and stochastic for market price uncertainty. On this basis, given the optimal day-ahead offering strategy, the offering curves to provide incremental AS capacities in the supplemental AS markets are further derived considering the opportunity cost. A new index, the maximum acceptable curtailment rate, is introduced to formulate the tradeoff of CSP plants between supplying AS to the system and reserving the flexibility for solar energy accommodation. The case study results demonstrate the validity of the proposed model.

Description: This paper presents two methods for online rolling horizon optimal control of an energy storage unit in a grid-connected microgrid, subject to uncertainty in demand and electricity pricing. The proposed methods are based on the concept of rolling horizon control, where battery charge/discharge activities are determined by repeatedly solving a linear optimization problem over a moving control window. The predicted values of the microgrid net electricity demand and electricity prices over the control horizon are assumed to be uncertain. The first formulation of the control is based on the scenario-based stochastic conditional value at risk (CVaR) optimization, where the cost function includes electricity usage cost, battery operation costs, and grid signal smoothing objectives. Multivariate Gaussian distribution is used to model the variations of electricity prices and net demand power around their predicted nominal values. The second formulation of the control reduces the computations by taking a worst-case CVaR stochastic optimization approach. In this case, the uncertainty in demand is still stochastic but the problem constraints are made robust with respect to price variations in a range. Simulation results under different scenarios are presented to demonstrate the effectiveness of the proposed methods.

Description: This paper shows how the power quality issues can be resolved in wind-diesel microgrids by means of a fuel cell/electrolyzer (FC/ELZ) system. In this regard, an autonomous hybrid power system, including a diesel generator and a fixed-speed wind turbine (FSWT) equipped with a FC/ELZ system, has been investigated. The main aim of employing the FC/ELZ system is to reduce fuel consumption and mitigate the aerodynamic effects of wind turbine (i.e., tower shadow, wind shears, yaw error, and turbulence) on power quality in the microgrid. To conduct a comprehensive study, the detailed models of the devices are used. The aerodynamic and mechanical aspects of WT are simulated using AeroDyn and FAST, and the thermodynamic and electrochemical aspects of FC/ELZ are simulated using models validated by experimental data. Furthermore, control of power electronic interfaces for the FC/ELZ system, including a bidirectional dc/ac voltage source converter (VSC), a dc/dc converter to boost the FC output voltage, and a dc/dc converter to reduce input voltage to the ELZ, is presented. The studied system was implemented in a MATLAB/Simulink software environment. The simulation results demonstrate the efficacy of the FC/ELZ system in reducing the flicker level and suppressing the voltage fluctuations induced by yaw error and turbulence.

Description: This paper presents a two-stage stochastic centralized dispatch scheme for AC/DC hybrid smart grids. The developed dispatch scheme coordinates the operations of a variety of distributed energy resources (DERs), such as distributed generators (DGs) and energy storage systems (ESSs). It also ensures the coordinated charging of electric vehicles (EVs) and models the degradation of their batteries that occurs due to vehicle-to-grid (V2G). The energy coordination problem has been formulated as a two-stage day-ahead resource scheduling problem, with the intermittent supply; the variable demand, which includes EVs; and the fluctuating real-time energy price modeled as random variables. The first stage produces day-ahead dispatch decisions for the dispatchable DG units. For a set of possible scenarios over the next 24 h, the second stage determines appropriate corrective decisions with respect to the import/export schedule, storage charging/discharging cycles, and EV charging/discharging patterns. The objective is to minimize the expected total operating cost while satisfying operational and technical constraints. The new two-stage stochastic centralized dispatch model has been tested on a 38-bus AC/DC hybrid distribution system. The simulation results demonstrate the effectiveness of the developed scheme for optimally coordinating the various components of future AC/DC hybrid smart grids. To demonstrate the necessity for uncertainty modeling, the value of the stochastic solution (VSS) and the expected value of perfect information (EVPI) have been applied for comparing the stochastic solution obtained and the deterministic one.

Description: This paper attempts to contribute to the development of a new concept focused on a cooperative control scheme for a smart network of residential buildings (SNRB) and to demonstrate advantages of interconnections and coordination among a set of smart residential buildings (SRBs), by taking advantages of fluctuations of stochastic renewable sources and loads, and exploiting the operational flexibilities of thermal loads defined as the required hot water and desired buildings temperature. A comprehensive finite-horizon scheduling optimization problem is formulated to optimally control a SNRB using model predictive control (MPC) method, which integrates both forecasts and newly updated information. The cooperation is reached through a bidirectional communication infrastructure in the SNRB, where the master controller (MC) is available at the network level and in charge of coordinating and managing power in the SNRB. A MPC-based algorithm is used for the future scheduling of power exchanges, charge/discharge state of each energy storage device (ESD), the state of each micro-CHP and the charging state of each plug-in electric vehicle (PEV) available in the network. The MPC strategy is tested through case studies where the influences of both network topology and thermal loads on the operation of each SRB are analyzed via numerical results.

Description: The present evolution of fuel prices together with the reduction of premiums for renewable energies make it of vital importance to improve renewable production management. This paper proposes a model of a single renewable power producer to compete more efficiently against other generators. The single unit is composed of a wind power producer and a hydro-pump storage power producer. The synergies between both renewable producers make relevant the possibility of mitigating wind power uncertainty, and due to this, the imbalances of the wind power producer will be reduced. The reduction of wind imbalances can come from deviating part of the excess of wind generation through a physical connection toward the pumping system or by increasing hydro generation to mitigate the lack of wind generation. To evaluate the problem, stochastic mixed integer linear programming is proposed to address the problem of selling the energy from the single renewable unit through a bilateral contract and in the day-ahead market, as a new contribution to earlier studies. Furthermore, a balancing market is considered to penalize the imbalances. The decision is made to maximize the profit, considering risk-hedging through the Conditional Value at Risk. The model is tested and analyzed for a case study and relevant conclusions are presented.

Description: Cascading trip faults in large-scale wind power centralized integration areas bring new challenges to the secure operation of power systems. In order to deal with the complexity of voltage security regions and the computation difficulty, this paper proposes an autonomous voltage security region (AVSR) for each wind farm and the point of common coupling (PCC) substation, whose voltage can be controlled in a decoupled way. The computation of the AVSR can be completed using a stepwise search method exchanging voltage and power information between the control center and the wind farms. At each wind farm, an AVSR is determined to guarantee the normal operation of each wind turbine generator (WTG), while in the control center, each region is designed in order to guarantee secure operation both under normal conditions and after an N -1 contingency. A real system in Northern China was used to carry out case studies to verify the effectiveness of the AVSRs proposed, and good performance was demonstrated using the Monte Carlo method.

Description: Evaluating the impact related to stochastic wind generation and generic storage on economic dispatch in distribution system operation is an important issue in power systems. This paper presents the analysis of the impacts of high wind power and storage participation on a distribution system over a period of 24 h using grid reconfiguration for electrical distribution system (EDS) radial operation. In order to meet this objective, a stochastic mixed integer linear programming (SMILP) is proposed, where the balance between load and generation has to be satisfied minimizing the expected cost during the operation period. The model also considers distributed generation (DG) represented by wind scenarios and conventional generation, bus loads represented through a typical demand profile, and generic storage. A case study provides results for a weakly meshed distribution network with 70 buses, describing in a comprehensive manner the effects of stochastic wind scenarios and storage location on distribution network parameters, voltage, substation behavior as well as power losses, and the expected cost of the system.

Description: This paper presents a second order sliding mode control strategy to control the generator and the grid sides of a variable speed experimental wind energy conversion system. At the generator side, the rotational speed is controlled to track a profile generated from the power curve of the wind turbine for maximum power extraction. At the grid side, the dc-link voltage is regulated for a proper transfer of power. The control strategy is based on a disturbed single input-single output error model and a second order sliding mode control algorithm. The proposed second order sliding mode control strategy offers interesting characteristics such as robustness to parametric uncertainties in the turbine and the generator as well as external disturbances. The proposed strategy, for speed and dc-link voltage control in wind energy conversion system, is validated on an emulated wind turbine driven by the OPAL-RT real-time simulator (OP5600). Experimental results show that the proposed control strategy is effective in terms of speed and dc-link voltage control. The sliding mode control approach is robust against unknown disturbances, parametric variations, and uncertainties in the system. Furthermore, it produces no chattering in the generated torque, which reduces the mechanical stress on the wind turbine.

Description: A program was started in 1999 in the Portuguese Research Reactor to test electronics components and circuits for the LHC facility at CERN, initially with a dedicated in-pool irradiation container used at a reactor power of 2 kW and later an irradiation chamber outside the pool, with tailored neutron and gamma filters that could be used at 1 MW. Practice has shown the need to introduce several improvements to the irradiation procedures and infrastructures over the years. In this paper, we review the lessons learned and the major improvements introduced.

Description: During irradiation UO 2 nuclear fuel experiences the development of a non-uniform distribution of porosity which contributes to establish varying mechanical properties along the radius of the pellet. Radial variations of both porosity and elastic properties in high burnup UO 2 pellet can be investigated via high frequency acoustic microscopy. For this purpose ultrasound waves are generated by a piezoelectric transducer and focused on the sample, after having travelled through a coupling liquid. The elastic properties of the material are related to the velocity of the generated Rayleigh surface wave ( $ mathrm {V}_{ mathrm {R}}$ ). A UO 2 pellet with a burnup of 67 GWd/tU was characterized using the acoustic microscope installed in the hot cells of the JRC-ITU at a 90 MHz frequency, with methanol as coupling liquid. $ mathrm {V}_{ mathrm {R}}$ was measured at different radial positions. A good agreement was found, when comparing the porosity values obtained via acoustic microscopy with those determined using SEM image analysis, especially in the areas close to the centre. In addition, Young’s modulus was calculated and its radial profile was correlated to the corresponding burnup profile and to the hardness radial profile data obtained by Vickers micro-indentation

Description: In the framework of the European I-Smart project, optimal 4H-SiC based diode geometries were developed for high temperature neutron detection. Irradiation tests were conducted with 14 MeV fast neutrons supplied by a deuterium-tritium neutron generator with an average neutron yield of $4.04 times {10^{10}} - 5.25 times {10^{10}};hbox{n/s}$ at Neutron Laboratory of the Technical University of Dresden in Germany. In this paper, we interpret the first measurements and results with 4H-SiC detector irradiated with fast neutrons from room temperature up to 500 °C. These experiments are serving also the first simulation of the harsh environmental condition measurements in the tritium breeding blanket of the ITER fusion reactor, which is one of the most prominent planned location of high temperature neutron flux characterization studies in the near future.

Description: A proposal for an autonomous and flexible ship container inspection system is presented. This could be accomplished by the incorporation of an inspection system on various container transportation devices (straddle carriers, yard gentry cranes, automated guided vehicles, trailers). The configuration is terminal specific and it should be defined by the container terminal operator. This enables that no part of the port operational area is used for inspection. The inspection scenario includes container transfer from ship to transportation device with the inspection unit mounted on it. The inspection is performed during actual container movement to the container location. A neutron generator without associated alpha particle detection is used. This allows the use of higher neutron intensities ( $5times {10^9} - {10^{10}} text{n/s}$ in $4pi $ ). The inspected container is stationary in the “inspection position” on the transportation device while the “inspection unit” moves along its side. The following analytical methods will be used simultaneously: neutron radiography, X-ray radiography, neutron activation analysis, (n, $gamma $ ) and (n,n’ $gamma $ ) reactions, neutron absorption. and scattering, X-ray backscattering. The neutron techniques will utilize “smart collimators” for neutrons and gamma rays, both emitted and detected. The inspected voxel is defined by the intersection of the neutron generator and the detectors solid angles. The container inspection protocol is based on identification of discrepancies between the cargo manifest, elemental “fingerprint” and radiography profiles. In addition, the information on contain- r weight is obtained during the container transport and screening by measuring of density of material in the container.

Description: It was demonstrated in the previous work that various threat materials could be detected inside the sea going cargo container by measuring the three variables, carbon and oxygen concentration and density of investigated material. Density was determined by measuring transmitted neutrons, which is not always practical in terms of setting up the instrument geometry. In order to enable more geometry flexibility, we have investigated the possibility of using the scattered neutrons in cargo material identification. For that purpose, the densities of different materials were measured depending on the position of neutron detectors and neutron generator with respect to the target position. One neutron detector was put above the target, one behind and one in front of the target, above the neutron generator. It was shown that all three positions of neutron detectors can be successfully used to measure the target density, but only if the detected neutrons are successfully discriminated from the gamma rays.

Description: Determination of photon heating by calculation is an important issue for the Jules Horowitz Reactor (JHR), the next international Material-Testing Reactor (MTR) under construction at the CEA Cadarache research center in the south of France. Accurate knowledge of photon heating in structure materials and irradiation devices is necessary for JHR design and safety studies. In this paper, we quantify the impact of different photon-heating calculation routes by comparing absorbed dose and Kinetic Energy Released per MAss (KERMA) calculations from two different Monte Carlo codes, TRIPOLI-4.9 and Monte Carlo N-Particle transport code (MCNP). These calculations are carried out in JHR-representative geometries with the nuclear-data library JEFF3.1.1 and the photon-data library EPDL97. Discrepancies amounting to up to 18% between absorbed dose and KERMA are found in JHR irradiation devices and are linked to charged-particle transport effects taking place in heterogeneous materials of small dimensions. In a JHR-assembly cell, discrepancies of about 1% on photon KERMA and of about 3% on absorbed dose are highlighted between the two Monte Carlo codes. These latter discrepancies are small compared to typical sources of uncertainty for Monte Carlo calculation (for instance, nuclear data uncertainty) and are supposed to be due to differences in the processing of gamma-production data by neutron interactions and to differences in electromagnetic-shower models and implementation between the two codes.

Description: Plastic scintillator loading with gadolinium-rich organometallic complexes shows a high potential for the deployment of efficient and cost-effective neutron detectors. Due to the low-energy photon and electron signature of thermal neutron capture by Gd-155 and Gd-157, alternative treatment to pulse-shape discrimination has to be proposed in order to display a count rate. This paper discloses the principle of a compensation method applied to a two-scintillator system: a detection scintillator interacts with photon and fast neutron radiation and is loaded with gadolinium organometallic compound to become a thermal neutron absorber, while a not-gadolinium loaded compensation scintillator solely interacts with the fast neutron and photon part of incident radiation. After the nonlinear smoothing of the counting signals, a hypothesis test determines whether the resulting count rate post-background response compensation falls into statistical fluctuations or provides a robust indication of neutron activity. Laboratory samples are tested under both photon and neutron irradiations, allowing the authors to investigate the performance of the overall detection system in terms of sensitivity and detection limits, especially with regards to a similar-active volume He-3 based commercial counter. The study reveals satisfactory figures of merit in terms of sensitivity and directs future investigation toward promising paths.

Description: This paper presents a new code for the analysis of gamma spectra generated by an equipment for continuous measurement of gamma radioactivity in aerosols with paper filter. It is called pGamma and has been developed by the Nuclear Engineering Research Group at the Technical University of Catalonia - Barcelona Tech and by Raditel Serveis i Subministraments Tecnològics, Ltd. The code has been developed to identify the gamma emitters and to determine their activity concentration. It generates alarms depending on the activity of the emitters and elaborates reports. Therefore it includes a library with NORM and artificial emitters of interest. The code is being adapted to the monitors of the Environmental Radiological Surveillance Network of the local Catalan Government in Spain (Generalitat de Catalunya) and is used at three stations of the Network.

Description: Prosthetics treatments with total or partial reconstruction are highly recommended in order to investigate caries, fractures and for better aesthetic. The purpose of this study was to evaluated marginal and internal fit of infrastructures (ceramic and metal) by using a high resolution X-ray micro-computed tomography. Each framework was placed on the original model and scanned. Image processing analysis and statistical approaches were combined together to evaluated directly in 3D the gap between the crown and the dental, which makes it possible to have a realistic dental arcade model.

Description: Latest Fusion energy experiments envisage a quasi-continuous operation regime. In consequence, the largest experimental devices, currently in development, specify high-availability (HA) requirements for the whole plant infrastructure. Highly available systems operate seamlessly in the case of component failure, ensuring safety of equipment, people, environment and investment. Control and Data Acquisition (C&DA) systems for Fusion diagnostics are considered mission-critical and require high degrees of availability. IPFN developed a C&DA system for fast control of advanced Fusion devices, targeting HA. The hardware platform is based on in-house developed Advanced Telecommunication Computing Architecture (ATCA) instrumentation modules–digitizing and data switch blades using PCI Express (PCIe) over the ATCA backplane Fabric Channel Interface, connecting to an external PCIe host computer. At the hardware management level, the system architecture takes advantage of ATCA’s HA characteristics, such as its redundant hardware components, redundant backplane topologies and Field Replaceable Unit (FRU) “Hot Swap”. At the software level, PCIe supports “Hot Plug” graceful device insertion and removal. The implementation of PCIe Hot Plug for the ATCA form-factor is one of the major tasks involved and a solution for such implementation was also developed. The paper describes how IPFN C&DA system can be setup to take advantage of both ATCA and PCIe features to perform with the desired degree of availability, by implementing fail-over mechanisms based on the use of redundancy, thus being suitable for advanced C&DA systems in Fusion.

Description: The time response of a recently developed polysiloxane based liquid scintillator has been analyzed for the first time: a special focus on the pulse shape discrimination capability of this material, which is characterized by low toxicity and low volatility, has been addressed. Fluorescence lifetime and scintillation pulses have been studied at different primary dye concentrations, with the aim of optimizing the neutron/gamma discrimination, connecting the results to the energy transfer and to the formation of excimers inside the scintillating solution. Pulse shape analysis performed during the irradiation of the samples with a pulsed neutron beam allowed the definition of a figure of merit as an indicative parameter for the neutron/gamma discrimination. The dependence of this parameter from radiation energy and PPO concentration has been analyzed in order to optimize the performances of the material in view of its possible use in environments with high gamma-ray radiation background.

Description: The measurement of fusion power, i.e., total neutron emissivity, will play an important role for achieving the goals of ITER project, in particular the fusion gain factor Q related to the reactor performance. The article gives overview of the neutron diagnostics being developed for ITER. Particular attention is given also to the development of the neutron calibration strategy whose main scope is to achieve the required accuracy of 10% for the measurement of fusion power. Neutron Flux Monitors located in diagnostic ports and inside the vacuum vessel will measure ITER total neutron emissivity, expected to range from $10^{14}~mathrm {n}/mathrm {s}$ in Deuterium—Deuterium (DD) plasmas up to almost $10^{21}~mathrm {n}/mathrm {s}$ in DT plasmas. The neutron detection systems as well all other ITER diagnostics have to withstand high nuclear radiation and electromagnetic fields as well ultrahigh vacuum and thermal loads.

Description: This paper describes the development and testing of a neutron counter, spectrometer, and dosimeter that is compact, efficient, and accurate. The 1.3 liter detector head for this instrument is a composite detector with an organic scintillator containing uniformly distributed 6 Li 6 nat Gd 10 B 3 O 9 : Ce (LGB:Ce) microcrystals. Moderating neutrons that have slowed sufficiently in the plastic, capture in one of the Lithium-6, Boron-10, or Gadolinium-157/155 atoms in the LGB:Ce scintillator, which then releases the capture energy in a characteristic cerium emission pulse. The measured captured pulses indicate the presence of neutrons. When a scintillating fluor is present in the plastic, the light pulse resulting from the neutron moderating in the plastic is paired with the LGB:Ce capture pulse to identify the energy of the neutron. This data was used to assist in the unfolding of the neutron spectra. The unfolded spectra were then validated with known spectra, at both neutron emitting isotopes and fission/accelerator facilities, Los Alamos Neutron Science Center (LANSCE), Edwards Accelerator Laboratory (EAL) at Ohio University. The instrument can measure neutrons and their spectra over the range between 0.8 MeV and 150 MeV with an average uncertainty in neutron rate of only ±8%.

Description: Basic concepts and the development of a high counting rate digital spectrometry system based on efficient ADCs and latest available FPGA are presented with the aim of using such a system, coupled to fast scintillators, in plasma experiments. The prototype system is a 1 channel 12-bit 1 GSPS digitizer with $2~mathrm {V}_{mathrm {pp}}$ input voltage. Preliminary results tested with different radioactive sources are shown for low (0.03 Mcps) and high (2.2 Mcps) counting rates. A comparison of energy spectra and energy resolution with what obtained by a commercial device is also shown.

Description: The nuclear radiation energy deposition rate (unit usually employed: $mathrm {W.g}^{-1}$ ) is a key parameter for the thermal design of experiments on materials and nuclear fuel carried out in experimental channels of irradiation reactors, such as the French reactor in Saclay called OSIRIS or the Polish reactor named MARIA. In particular the quantification of nuclear heating allows the prediction of heat and thermal conditions induced in irradiated devices and/or structural materials. Various sensors are used to quantify this parameter, in particular radiometric calorimeters, also known as in-pile calorimeters. Two main kinds of in-pile calorimeter exist possessing two geometries and two measurement principles: the single-cell calorimeter and the differential calorimeter. The present work focuses on specific examples of these calorimeter types, from the step of their out-of-pile calibration (transient and steady experiments respectively) to the comparison between numerical and experimental results obtained from two irradiation campaigns (French and Polish reactors). The main aim of this paper is to propose a steady numerical approach to estimate the single-cell calorimeter response under irradiation conditions.

Description: In the perspective of reducing ITER risks, JET next DT campaign presents a unique potential, since the device can combine the right first wall material mix, the reactor fuel mixture and sufficient dimensions and fields to confine the alpha particles. An integrated diagnostic programme, to maximize the scientific output of this DT campaign, is under way and concentrates mainly on the diagnostic for the fusion products, on advanced measurements for instabilities and on testing diagnostic technologies in a 14 MeV neutron environment.

Description: Microgrids consisting of diesel generators, storage devices, and renewable sources present an effective approach for an economic energy supply to rural areas. Advanced control methods are needed to improve the energy dispatch, enable a cost-efficient operation and guarantee an uninterrupted power supply. In particular, sudden variations in load demand or additional power supply from renewable sources are often unpredictable and underline the need for enhanced control. This paper presents an advanced control strategy for the optimal microgrid operation using a two-layer model predictive method. The first optimization layer presents an optimal control problem, based on real-time predictions of future power profiles, for the calculation of the optimal energy dispatch. To improve the robustness of the control strategy toward prediction errors, a boundary value problem is solved to adjust the diesel generator power in the second stage. The model predictive control framework is further used to adapt the weights of the forecast algorithm. Simulation studies are carried out by using real-world data to illustrate the performance and economic benefits of the proposed method. Results show the effectiveness of the control strategy in terms of computational feasibility, accuracy, increased robustness, and reduced cost.

Description: This paper presents a solar power forecasting scheme, which uses spatial and temporal time series data along with a photovoltaic (PV) power conversion model. The PV conversion model uses the forecast of three different variables, namely, irradiance on the tilted plane, ambient temperature, and wind speed, in order to estimate the power produced by a PV plant at the grid connection terminals. The forecast values are obtained using a spatio-temporal method that uses the data recorded from a target meteorological station as well as data of its surrounding stations. The proposed forecasting method exploits the sparsity of correlations between time series data in a collection of stations. The performance of both the PV conversion model and the spatio-temporal algorithm is evaluated using high-resolution real data recorded in various locations in Italy. Comparison with other benchmark methods illustrates that the proposed method significantly improves the solar power forecasts, particularly over short-term horizons.

Description: A promising configuration for future smart grids is an AC/DC hybrid topology that enables the integration of AC/DC energy resources and modern loads, thus permitting the consequent formation of AC/DC hybrid microgrids (HMGs). An understanding of AC/DC HMGs and their operational premise during islanding will certainly pave the way toward the realization of a future smart grid that includes a plug-and-play feature. However, the planning and operation of such isolated and hybrid systems are reliant on a powerful and efficient power flow tool. To this end, this paper proposes a novel unified, generic, and flexible power flow algorithm for isolated AC/DC HMGs. The power flow subproblems related to AC and DC subgrids are described mathematically by a set of linear and nonlinear equations and are solved simultaneously using a Newton trust-region method. The proposed algorithm is generic in the sense that it includes consideration of the unique characteristics of islanded AC/DC HMGs: a variety of possible topologies, droop controllability of the distributed resources (DRs), and bidirectionality of the power flow in the interlinking converters (ICs). The new power flow formulation is flexible and permits the easy incorporation of any changes in DR operating modes and IC control strategies. The developed algorithm was tested and applied for analyzing selected operational and control aspects of isolated AC/DC HMGs, including inaccurate power sharing and interlinking converters characterized by differing control strategies. The proposed load flow program can form the basis of and provide direction for further studies of isolated AC/DC HMGs.

Description: With the rapidly increasing penetration of renewable distributed generation (DG), the maximum hosting capacity (MHC) of a distribution system has become a major concern. To effectively evaluate the ability of a distribution system to accommodate DGs, this paper proposes an MHC evaluation method while considering the robust optimal operation of on load tap changers (OLTCs) and static var compensators (SVCs) in the uncertain context of DG power outputs and load consumptions. The proposed method determines the DG hosting capacities corresponding to different conservative levels. Furthermore, this paper discusses how to find out the most critical technical constraint that may limit the MHC by adjusting parameters of the proposed robust formulation. The effectiveness of the proposed method is demonstrated using a modified IEEE 33-bus distribution system.

Description: This paper presents a numerical-based algorithm to solve the probabilistic power flow problem. Parzen window density estimator is used to efficiently estimate probabilistic characteristics of power flow outputs. Correlations between wind generation, load, and plug-in hybrid electric vehicle charging stations are taken into account. The proposed algorithm works properly for random variables with various probability distribution functions and is very useful when limited information is available for each random variable. The algorithm is tested on the IEEE 14-bus and IEEE 118-bus systems considering correlated and uncorrelated conditions. Comparison between the proposed algorithm with 2n, $text{2n} + 1$ point estimation methods as well as Monte Carlo simulation and linear diffusion method are provided. In addition, probability density and cumulative distribution functions are determined using the proposed algorithm, diffusion method, and the combined Cumulants and Gram-Charlier for $text{2n} + 1$ point estimation method. Error indices are introduced to evaluate all random variables in a single benchmark. Simulation results show the effectiveness of the proposed algorithm to provide complete statistical information for probabilistic power flow outputs.

Description: Penetration of solar energy into main grid has gradually increased in recent years due to a growing number of large-scale photovoltaic (PV) farms. The power output of these PV farms may fluctuate due to a wide variability of meteorological conditions, and, thus, we need to compensate for this effect in advance. In this paper, we propose a solar power prediction model based on various satellite images and a support vector machine (SVM) learning scheme. The motion vectors of clouds are forecasted by utilizing satellite images of atmospheric motion vectors (AMVs). We analyze 4 years’ historical satellite images and utilize them to configure a large number of input and output data sets for the SVM learning. We compare the performance of the proposed SVM-based model, the conventional time-series model, and an artificial neural network (ANN) model in terms of prediction accuracy.

Description: In this paper, the overvoltage protection module (OVP) for the power supply (PS) system of the Belle II pixel detector (PXD) is described. The aim of the OVP is to protect the detector and associated electronics against overvoltage conditions. These include failures of the PS itself, wrong settings of the output voltages, and also transients coming out of a noisy environment of the experiment. The OVP system works independently of any other protection of the PS system, increasing its overall reliability.

Description: In recent years there has been a growing interest to use reconfigurable modules, based on field-programmable gate array (FPGA) devices, in nuclear environments. One of the requirements for these types of modules, when operating in complex future nuclear power experiments, is their remote update capability. The operational needs of pulsed fusion reactors will lead to a large production of very high energy neutrons (MeV range). The current procurement policies for nuclear installations do not allow exposure of electronics to radiation, except following very strict rules. However, considering the “as low as (is) reasonably achievable” (ALARA) principle with respect to human exposure to radiation, the access to cubicles might be restricted, requiring the remote update of FPGA codes. FPGAs are volatile devices, and their programming code is usually stored in dedicated flash memories for proper configuration during module power-on. This paper presents an alternative method for FPGA remote update, capable to store new FPGA codes in inboard Serial Peripheral Interface (SPI) flash memories. The new method, based on the Xilinx Quick Boot application note and adapted to PCIe protocol, was developed with the KC705 Evaluation Kit from Xilinx and successfully tested in the in-house Advanced Mezzanine Card (AMC) prototype, installed on the ATCA-PTSW-AMC4 carrier module from the ITER Fast Plant System Controller catalogue.

Description: Environmental scientific research requires a detector that has sensitivity low enough to reveal the radiological content for the presence of potential contaminants in the sample at a reasonable counting time. CANBERRA developed a germanium detector geometry called Small Anode Germanium (SAGe) Well detector. The SAGe Well detector is a new type of low capacitance device manufactured using small anode technology capable of advancing many environmental scientific research applications. The performance of this detector has been evaluated for a range of sample sizes and geometries counted inside the well, and on the end cap of the detector. The detector has energy resolution performance similar to semi-planar detectors, and offers significant improvement over the existing coaxial and Well detectors. Energy resolution performance of 750 eV Full Width at Half Maximum (FWHM) at 122 keV $gamma$ -ray energy and resolution of 2.0–2.3 keV FWHM at 1332 keV $gamma$ -ray energy are guaranteed for detector volumes up to $425 ~hbox{cm}^{3}$ . The SAGe Well detector offers an optional 28 mm well diameter with the same energy resolution performance as the standard 16 mm well. Such outstanding performance will benefit environmental applications in revealing the detailed radionuclide content of samples, particularly at low energy. The detector is compatible with electric coolers without any sacrifice in performance and supports the CANBERRA Mathematical efficiency calibration method (In situ Object Calibration Software or ISOCS, and Laboratory SOurceless Calibration Software or LabSOCS). In addition, the SAGe Well detector supports true coincidence summing available in the ISOCS/LabSOCS framework. The improved resolution performance of this new device gr- atly enhances its detection sensitivity for a range of sample sizes and geometries counted inside the well. This results in lower minimum detectable concentrations (MDC) compared to Traditional Well detectors. The SAGe Well detectors are compatible with Marinelli beakers and compete very well with semi-planar and coaxial detectors for large samples in many applications.