Implementation of FPGA Based MPPT Techniques for Grid-Connected PV System

Global energy demand is growing rapidly owing to industrial growth and urbanization.Alternative energy sources are driven by limited reserves and rapid depletion of conventional energy sources(e.g.,fossil fuels).Solar photovol-taic(PV),as a source of electricity,has grown in popularity over the last few dec-ades because of their clean,noise-free,low-maintenance,and abundant availability of solar energy.There are two types of maximum power point track-ing(MPPT)techniques:classical and evolutionary algorithm-based techniques.Precise and less complex perturb and observe(P&O)and incremental conduc-tance(INC)approaches are extensively employed among classical techniques.This study used afield-programmable gate array(FPGA)-based hardware arrange-ment for a grid-connected photovoltaic(PV)system.The PV panels,MPPT con-trollers,and battery management systems are all components of the proposed system.In the developed hardware prototype,various modes of operation of the grid-connected PV system were examined using P&O and incremental con-ductance MPPT approaches.

Soft-switching Grid-connected PV Inverter With Interleaved Flyback Topology

提出一种应用于单个光伏组件的软开关交错反激并网逆变器拓扑及其软开关控制策略。针对反激变压器漏感问题，提出漏感能量吸收回馈电路，实现了漏感能量吸收再利用，并实现了开关管漏源电压的钳位，提高了变换效率同时降低了开关管关断电压尖峰；提出基于数字处理器的反激变换器变开关频率谐振软开关控制策略，实现了开关管的零电压开通，同时改善了逆变器的电磁兼容特性；提出的交错并联反激逆变器有助于减小变压器和滤波器的体积，提高功率密度。详细分析变换器的工作原理，分析变开关频率谐振软开关控制方式的原理和实现条件，最后进行实验验证。

H6 Non-isolated Full Bridge Grid-connected PV Inverters With Low Leakage Currents

为满足非隔离光伏并网发电系统对共模漏电流的限制，提出一种六开关逆变器拓朴（H6拓扑）。所提出的H6拓扑在功率传输模态时，进网电流半个工频周期流过3支开关管，而另半个工频周期流过2支开关管，故相对于H5拓扑，降低了通态损耗，有利于热应力均衡，且仍满足续流阶段光伏电池输出端与电网脱离的要求。详细分析拓扑的工作原理，并推论给出H6非隔离光伏并网逆变器的其它3种拓扑结构；比较分析了H5拓扑、Heric拓扑和H6拓扑的损耗和成本。通过1kW通用样机平台对比验证了上述3种拓扑的效率和共模特性。实验结果表明，H6拓扑的变换效率高于H5拓扑、但略低于Heric拓扑，共模特性优于Heric拓扑、但略劣于H5拓扑。

A Modified-Simplified MPPT Technique for Three-Phase Single-State Grid-Connected PV Systems

Nowadays,the single state inverter for the grid-connected photovoltaic(PV)systems is becoming more and more popular as they can reduce circuit complexity resulting in less power losses of the inverter.This paper focuses on the use of model predictive control(MPC)to control a 3-phase and 2-level single-state grid-connected inverter in order to regulate the PV maximum power point(MPP).The algorithm of MPC scheme was done to measure the simultaneous current signal including predicting the next sampling current flow.The reference current(Id∗)was used to control the distribution of electrical power from the solar cell to the grid.To be able to control the maximum power point tracking(MPPT)when the sunlight suddenly changes,so that a developing MPPT based on estimation current perturbation and observation(ECP&O-MPPT)technique was used to control the reference current.This concept was experimented by using MATLAB/Simulink software package.The proposed technique was tested and compared with the old technique.The simulation results showed that the developed MPPT technique can track the MPP faster when the light changes rapidly under 1,000W/m2,25℃ standard climatic conditions.The MPPT time was 0.015 s.The total harmonic distortion(THD)was 2.17%and the power factor was 1.

Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

Performance Assessment of a Real PV System Connected to a Low-Voltage Grid

The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Therefore,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,Egypt.The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering(PSS/E)software.Where the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered system.The results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power factor.Decreasing total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 microseconds.The connection between solar stations and the national grid makes the system more efficient.

Research on large-scale dispatchable grid-connected PV systems

This paper describes the research on a largescale dispatchable grid-connected photovoltaic(PV)system for supplying power to the grid for dispatch instead of supplying the electricity to a local load.In order to maximise the value of the solar energy,a hybrid electricity storage consisting of batteries and supercapacitors is used with the PV system.This paper proposes a control strategy focusing on theDCpower at theDClink rather than at the grid-connected inverter.Two typical sets of real data,collected from existing sites,are used to demonstrate the practicality of the system.Finally,the simulation results are used to demonstrate the good performance and feasibility of the proposed system together with the proposed control strategy.

基于人工神经网络的PV/T热电联供系统性能预测

为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IGWO-BP)预测模型,在晴朗天气下进行试验,并采用该模型对系统电功率以及蓄热水箱内水温进行预测。结果显示,晴朗日系统的电效率8.7%~12.2%、热效率51.7%;预测结果与BP神经网络预测模型、基于粒子群优化的BP神经网络(back propagation neural network based on particle swarm optimization,PSO-BP)预测模型和卷积神经网络(convolutional neural network,CNN)预测模型预测结果进行比较,结果显示IGWO-BP预测模型电效率预测模型的绝对百分比误差(mean absolute percentage error,MAPE)、决定系数(determination coefficient,R^(2))、均方根误差(root mean square error,RMSE)、效率因子(efficient factor,EF)和Pearson相关系数(pearson related coefficient,r)分别为4.5E-05、0.99、0.24、0.99和1.00,在储热罐温度预测中,上述指标分别为8.90E-04、0.98、0.07、0.98、0.99,均优于其他预测模型,IGWO-BP神经网络预测模型具有更好的预测性能。研究结果可为太阳能PV/T热电联供系统性能预测与优化控制提供参考。

Dynamic phasor-based hybrid simulation for multi-inverter grid-connected system

To realize the efficient transient simulation of a grid-connected power generation system based on multiple inverters, this paper proposes a hybrid simulation method integrating the models of electromagnetic transient and dynamic phasors. Based on a demonstration of the concepts and properties of dynamic phasors, the models of single-phase and three-phase inverters described by dynamic phasors are established first. Considering the numerical compatibility problem between dynamic phasors and instantaneous values, an interface scheme between dynamic phasors and instantaneous values is designed, and the efficiency and precision differences of various transformation methods are compared in detail.Finally, by utilizing MATLAB/Simulink, a hybrid simulation platform of a multi-inverter grid-connected system is built, and the efficiency and accuracy of the hybrid simulation are validated via comparison with the full electromagnetic transient simulation.

A Survey of the Researches on Grid-Connected Solar Power Generation Systems and Power Forecasting Methods Based on Ground-Based Cloud Atlas

Photovoltaic power generating is one of the primary methods of utilizing solar energy resources,with large-scale photovoltaic grid-connected power generation being the most efficient way to fully utilize solar energy.In order to provide reference strategies for pertinent researchers as well as potential implementation,this paper tries to provide a survey investigation and technical analysis of machine learning-related approaches,statistical approaches and optimization techniques for solar power generation and forecasting.Deep learning-related methods,in particular,can theoretically handle arbitrary nonlinear transformations through proper model structural design,such as hidden layer topology optimization and objective function analysis to save information that can increase forecasting accuracy while filtering out irrelevant or less affected data for forecasting.The research’s results indicate that RBFNN-AG performed the best when applying the predetermined number of days,with an NRMSE value of 4.65%.RBFNN-AG performs better than sophisticated models like DenseNet(5.69%),SLFN-ELM(5.95%),and ANN-k-means-linear regression correction(6.11%).Additionally,scenario application and PV system investment techniques are provided to evaluate the current condition of new energy development and market trends both domestically and internationally.

Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

Due to nonlinear behavior of power production of photovoltaic(PV)systems,it is necessary to apply the maximum power point tracking(MPPT)techniques to generate the maximum power.The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions.In this study,a fuzzy logic controller(FLC)optimized by a combination of particle swarm optimization(PSO)and genetic algorithm(GA)is proposed to obtain the maximum power point(MPP).The proposed FLC uses the ratio of power variations to voltage variations and the derivative of power variations to voltage variations as inputs and uses the duty cycle as the output.The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem optimized by the PSO-GA.The proposed design is validated for MPPT of a PV system using MATLAB/Simulink software.The results indicate a better performance of the proposed FLC compared to the common methods.

应用PSO-RBF神经网络预测太阳能PV/T系统的热、电性能

为准确预测太阳能光伏光热(Solar Photovoltaic/Thermal,PV/T)系统的热、电性能,文章利用PSO(Particle Swarm Optimization)算法优化了RBF(Radial Basis Function)神经网络,并基于此方法建立了太阳能PV/T系统性能的仿真预测模型,与基于未优化RBF神经网络建立的预测模型进行了对比分析。同时,搭建了太阳能PV/T实验平台,通过云平台采集实验数据用于上述模型。研究结果表明:使用PSO算法优化后的RBF神经网络模型相较于未优化模型预测精度提高了20%,预测稳定性提高了30%,拟合优度R值有所提升。基于PSO-RBF神经网络建立的预测模型可精确预测太阳能PV/T系统的热、电性能。

Improved Interleaved Single-Ended Primary Inductor-Converter forSingle-Phase Grid-Connected System

The generation of electricity based on renewable energy sources,parti-cularly Photovoltaic(PV)system has been greatly increased and it is simply insti-gated for both domestic and commercial uses.The power generated from the PV system is erratic and hence there is a need for an efficient converter to perform the extraction of maximum power.An improved interleaved Single-ended Primary Inductor-Converter(SEPIC)converter is employed in proposed work to extricate most of power from renewable source.This proposed converter minimizes ripples,reduces electromagnetic interference due tofilter elements and the contin-uous input current improves the power output of PV panel.A Crow Search Algo-rithm(CSA)based Proportional Integral(PI)controller is utilized for controlling the converter switches effectively by optimizing the parameters of PI controller.The optimized PI controller reduces ripples present in Direct Current(DC)vol-tage,maintains constant voltage at proposed converter output and reduces over-shoots with minimum settling and rise time.This voltage is given to single phase grid via 1�Voltage Source Inverter(VSI).The command pulses of 1�VSI are produced by simple PI controller.The response of the proposed converter is thus improved with less input current.After implementing CSA based PI the efficiency of proposed converter obtained is 96%and the Total Harmonic Distor-tion(THD)is found to be 2:4%.The dynamics and closed loop operation is designed and modeled using MATLAB Simulink tool and its behavior is performed.

太阳能光伏光热PV/T组件在建筑设计中的应用

建筑领域“双碳”目标的提出,使得降低建筑能耗成为目前亟需解决的问题。可再生能源同建筑领域的有机结合被认为是解决建筑能耗的重要环节。通过对太阳能光伏光热技术的发展进行总结,研究太阳能光伏光热技术在建筑领域中的设计方法,提出了对未来光伏光热建筑一体化的设计思考,为以后太阳能光伏光热PV/T技术产业的发展提供参考。

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

基于TRNSYS的学校建筑PV/T跨季节蓄热供暖研究

PV/T耦合地源热泵系统在多能互补、提高可再生能源利用率方面受到广泛的关注,针对南京市某小学工程应用PV/T耦合地源热泵系统实现跨季节供暖做模拟分析。应用TRNSYS软件针对系统的运行温度、集热效率、设备工况、能源利用率进行模拟。发现PV/T电池通过地埋管放热的冷却水具有较好的集热冷却效果;土壤蓄热体平均温度仅下降0.23℃,实现土壤热平衡,且该系统的跨季节蓄热率约为60%;热泵机组实际COP平均COP在5以上,具有良好的节能效果;系统跨季节可以提供建筑热负荷的73.17%,发电量可以满足63.2%的热泵能耗。