Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV

This paper presents optimal parameters selection of particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking of photovoltaic array under partially shaded conditions. Under partial shading, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. The two proposed controllers include dynamic Particle Swarm Optimization, and constant particle swarm optimization. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. The results indicate that the dynamic particle swarm optimization algorithm can very fast track the GMPP within 128 ms for different shading conditions. In addition, the average tracking efficiency of the proposed algorithm is higher than 99.89%, which provides good prospects to apply this algorithm in the control search unit for the global maximum power point in stations

Optimal parameters selection of particle swarm optimization based global maximum power point tracking of partially shaded PV

This paper presents optimal parameters selection of particle swarm optimization (PSO) algorithm for determining the global maximum power point tracking of photovoltaic array under partially shaded conditions. Under partial shading, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. The two proposed controllers include dynamic Particle Swarm Optimization, and constant particle swarm optimization. The developed algorithms are implemented in MATLAB/Simulink platform, and their performances are evaluated. The results indicate that the dynamic particle swarm optimization algorithm can very fast track the GMPP within 128 ms for different shading conditions. In addition, the average tracking efficiency of the proposed algorithm is higher than 99.89%, which provides good prospects to apply this algorithm in the control search unit for the global maximum power point in stations

An Efficient Scheme for Determining the Power Loss in Wind-PV Based on Deep Learning

Power loss is a bottleneck in every power system and it has been in focus of majority of the researchers and industry. This paper proposes a new method for determining the power loss in wind-solar power system based on deep learning. The main idea of the proposed scheme is to freeze the feature extraction layer of the deep Boltzmann network and deploy deep learning training model as the source model. The sample data with closer distribution with the data under consideration is selected by defining the maximum mean discrepancy contribution coefficient. The power loss calculation model is developed by configuring the deep neural network through the sample data. The deep learning model is deployed to simulate the non-linear mapping relationship between the load data, power supply data, bus voltage data and the grid loss rate during power grid operation. The proposed algorithm is applied to an actual power grid to evaluate its effectiveness. Simulation results show that the proposed algorithm effectively improved the system performance in terms of accuracy, fault tolerance, nonlinear fitting and timeliness as compared with existing schemes.publishedVersio

Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function

This paper proposes a new approach based on Lambert W-function to extract the electrical parameters of photovoltaic (PV) panels. This approach can extract the optimal electrical characteristics of the PV panel under variable conditions of irradiation and temperature. Three benchmarking panels (shell SP70 monocrystalline silicon, shell ST40 thin film, and KC200GT Polycrystalline Silicon) are demonstrated and analyzed considering the electrical characteristics provided by the manufacturers. A comprehensive assessment is carried out under different weather condition to validate the capability and the robustness of the proposed approach. Furthermore, the simulated output characteristics of the three modules Photovoltaic are almost comparable and reproduce faithfully the manufacturer’s experimental data The novelty of this study is the using a new hybrid analytical and numerical method that straight forward and effective given value of Root mean square error less than those obtained by others methods that indicate the estimated results are very close to the experimental values provided by the manufacturers

Optimal Performance of Dynamic Particle Swarm Optimization Based Maximum Power Trackers for Stand-Alone PV System Under Partial Shading Conditions

One of the important tasks for increasing the efficiency of photovoltaic (PV) system is the development and improvement of the maximum power point tracking algorithms (MPPT). These MPPT algorithms lead to the ability to catch efficiently the global maximum power point of the partially shaded PV array. One of these trackers is the particle swarm optimization (PSO) algorithm which is one of the Soft computing techniques. The conventional PSO based trackers have many advantages such as the simplicity of hardware implementation and independence from the installed system. The actual problem of the practical application of PSO is the determination of its parameters to ensure high effectiveness of extracting the global MPP. Analysis of scientific papers devoted to the PSO algorithm has shown that there is currently no methodology for the optimal parameters' selection of PSO algorithm based maximum power trackers for the PV system. This paper aims to create a convenient and reasonable method for choosing the optimal parameters of the PSO algorithm, taking into account the topology and parameters of the DC-DC converter and the configuration of solar panels. A new method for selecting the parameters of a buck converter connected to a battery has been presented. The optimal value of the sampling time for the digital MPP controllers, providing their maximum performance; has been determined based on a new methodology. Matlab/Simulink software package is used as the main research tool. The prominent outcomes identify that the modified PSO and its designed parameters best meet the requirements of the MPPT controller for the PV system

Comprehensive validation of transient stability calculations in electric power systems and hardware-software tool for its implementation

Reliability and survivability of electric power systems (EPS) depend on transient stability assessment (TSA). One of the most effective way to TSA is time-domain simulation. However, large-scale EPS mathematical model contains a stiff nonlinear system of high-order differential equations. Such system cannot be solved analytically. At the same time, numerical methods are imperfectly applied for such system due to limitation conditions. To make it appropriate, the EPS mathematical model is simplified and additional limitations are used. These simplifications and limitations reduce reliability of simulation results. Consequently, their validation is needed. The most reliable approach to provide it is to compare the simulation results with the field data. However, in practice, there are not enough data for such validation. This paper proposes an alternative approach for validation - the application of a reference model instead of field data. A hardware-software system HRTSim was used as a reference model. This power system simulator has all the necessary properties and capabilities to obtain reliable information required for comprehensive validation of transient stability calculations in EPSs. Main disturbances leading to instability in EPSs are investigated to conduct the validation (processes in cases of faults, single-phase auto-reclosing operation and power system interconnection). Fragments of corresponding experimental studies illustrate the efficiency of the proposed approach. Obtained results confirmed the possibility of the developed approach to identify the causes of numerical calculation errors and to determine disturbances calculated with the significant error. In addition, experimental studies have revealed that numerical calculations error depends on disturbances intensity

Research, Development and Application of Hybrid Model of Back-to-Back HVDC Link

Recent hybrid simulators (or co-simulators) of the electric power system are focused on scientific and research features to propose and develop novel and more accurate simulators. The present paper demonstrates one more hybrid modelling approach based on application and combination of three modeling approaches all together: physical, analog and digital. The primary focus of the proposed approach is to develop the simulation tool ensuring such vital characteristics as three-phase simulation and modeling of a single spectrum of processes in electric power system, without separation of the electromagnetic and electromechanical transient stages. Moreover, unlimited scalability of the electric power system model and real-time simulation to ensure the opportunity of data exchange with external devices have been considered. The description of the development of the hybrid model of back-to-back HVDC link based on the proposed approach is discussed and analyzed. To confirm properties of the mentioned hybrid simulation approach and hybrid model of back-to-back HVDC link, the simulation results of the interconnection of non-synchronously operating parts of the electric power system; power flow regulation; dynamic response to external fault and damping of power oscillation in electric power system are presented and examined. Moreover, to confirm the adequacy of the obtained results, the comparison with a detailed voltage source converter HVDC model (Simulink Matlab) and Eurostag software are introduced

Управление током Z-инвертора с четвертой стойкой для автономной фотоэлектрической системы на основе прогнозирующего управления

Возобновляемые источники для производства электроэнергии вызывают больший интерес у ученых и исследователей по сравнению с традиционными источниками, работающими на основе использования углеводородного топлива. Одним из типов возобновляемых источников энергии, отвечающих реализации концепции «зеленая энергетика», являются фотоэлектрические системы, способные эффективно использоваться в качестве автономной системы электроснабжения для потребителей, географически расположенных в отдаленных, труднодоступных районах. Производительность автономной системы электроснабжения во многом определяется системой преобразования и ее алгоритмами управления. В статье рассмотрена новая и альтернативная система управления автономных фотоэлектрических станций, основанная на стратегии прогнозирующего управления напряжением и током нагрузки Z-инвертора с четвертой стойкой. Цель: разработка алгоритма, основанного на стратегии прогнозирующего управления, для регулирования токов нагрузки автономной фотоэлектрической системы электроснабжения. Методы: математическое и компьютерное моделирование с использованием программной среды MatLab/Simulink. Результаты. Благодаря использованию Z-инвертора система преобразования энергии для фотоэлектрических систем генерации сокращается до одноступенчатой структуры. Результаты показывают, что предложенный алгоритм управления может эффективно регулировать ток нагрузки при сбалансированных и несбалансированных нагрузках с высокой эффективностью управления. Предлагаемый алгоритм управления имеет отличные характеристики в установившихся и переходных режимах.The relevance. Renewable energy resources for electrical power generation have gained higher interest over the traditional underground fuels due to geo-reasons, such as the low generation cost and clean energy resources. Moreover, renewable energy resources, especially photovoltaic generation system, can efficiently be used as an autonomous power supply for consumers geographically located in remote, inaccessible areas. The performance of autonomous power supply depends mainly on the conversion system and its control technique. Therefore, this paper uses a new and alternative control system based on the finite control set model predictive control strategy to control the load current of the Z-source four-leg inverter employed for the autonomous photovoltaic generation system. The main aim of the research is the development of a control algorithm based on finite control set model predictive control strategy to regulate the load currents of Z-source four-leg inverter for a geographical stand-alone photovoltaic generation system. Methods: mathematical and computer modeling using the MatLab/Simulink software environment. Results. Due to using Z-source four-leg inverter, the power conversion system for the photovoltaic generation systems is reduced to be single-stage, instead of two-stage power conversion. The results show that the proposed control algorithm can effectively regulate load current under balanced/unbalanced issues with high controllability. The proposed control algorithm has excellent steady-state and transient performances