Research on MPPT of PV Systems Based on BP Neural Network

2012 ◽  
Vol 466-467 ◽  
pp. 930-934
Author(s):  
Wen Ying Chen ◽  
Yong Jun Lin ◽  
Wei Liang Liu ◽  
Shuang Sai Liu
Keyword(s):  
Control Structure ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Hardware Platform ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Power Point

In order to obtain more output power of photovoltaic (PV) array, which depends on solar irradiation and ambient temperature, maximum power point tracking (MPPT) techniques are employed. Among all the MPPT strategies, the Perturb and Observe (P&O) algorithm is more attractive due to the simple control structure. Nevertheless, steady-state oscillations always appear due to the perturbation. In this paper, a new MPPT method based on BP Neural Networks and P&O is proposed for searching maximum power point (MPP) fast and exactly, and its effectiveness is validated by experimental results using hardware platform based on microcomputer.

scholarly journals Efficient Perturb and Observe Algorithm for Photovoltaic Maximum Power Point Tracking and Drift Avoidance using SEPIC Converter

2019 ◽  
Vol 8 (10) ◽  
pp. 693-696
Keyword(s):  
Maximum Power Point Tracking ◽  
Sudden Change ◽  
Maximum Power ◽  
Atmospheric Conditions ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Power Point

Maximum power point tracking is a commonly used technique for extracting maximum possible power from solar photovoltaic (PV) systems under all conditions. Various methods used for implementation of MPPT algorithm, out of those methods, perturb and observe (P&O) is very popular and commonly using method owing to its simplicity, easy implementation and highly efficient nature. However, P&O algorithm has disadvantage that it suffers from drift phenomenon in which during sudden change in atmospheric conditions, the algorithm drifts away from the maximum power point (MPP). This paper proposes modifications in the conventional P&O algorithm to overcome the drifting of MPP during suddenly changing atmospheric conditions. This algorithm takes change in current into consideration along with change in voltage and power and is verified using MATLAB/Simulink. DC/DC control is achieved using SEPIC converter and simulation results of the proposed algorithm show that the system can track the MPP in transient whether conditions and drifting is avoided

scholarly journals A Novel Technique Based on Peafowl Optimization Algorithm for Maximum Power Point Tracking of PV Systems Under Partial Shading Condition

2021 ◽  
Vol 9 ◽  
Author(s):  
Dongrui Li ◽  
Jinjin Li ◽  
Ning Wang
Keyword(s):  
Optimization Algorithm ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

One of the most critical tasks during the application of photovoltaic (PV) systems is to harvest the optimal output power at various environmental scenarios, which is called maximum power point tracking (MPPT). Though plenty of advanced techniques are developed to achieve this purpose, most of them have corresponding prominent disadvantages, such as inefficient tracking ability, high computation burden, and complex convergence mechanism. Therefore, this work aims to propose a novel and powerful bio-inspired meta-heuristic optimization algorithm called peafowl optimization algorithm (POA), which is inspired by the group food searching behaviors of peafowl swarm. It can effectively achieve a suitable balance between local exploitation and global exploration thanks to its efficient exploratory and exploitative searching operators. Thus, a satisfactory MPPT performance for PV systems under partial shading condition (PSC) can be obtained based on POA. Moreover, two case studies, e.g., start-up test and step change in solar irradiation with constant temperature, are adopted to fairly and comprehensively validate the superiority and effectiveness of POA in contrast with particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO), respectively.

scholarly journals A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2521
Author(s):  
Alfredo Gil-Velasco ◽  
Carlos Aguilar-Castillo
Keyword(s):  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Computational Resources

There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.

scholarly journals A Novel DSP-Based MPPT Control Design for Photovoltaic Systems Using Neural Network Compensator

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3260
Author(s):  
Ming-Fa Tsai ◽  
Chung-Shi Tseng ◽  
Kuo-Tung Hung ◽  
Shih-Hua Lin
Keyword(s):  
Neural Network ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Irradiation Cell ◽  
Power Point ◽  
Neural Network Compensator

In this study, based on the slope of power versus voltage, a novel maximum-power-point tracking algorithm using a neural network compensator was proposed and implemented on a TI TMS320F28335 digital signal processing chip, which can easily process the input signals conversion and the complex floating-point computation on the neural network of the proposed control scheme. Because the output power of the photovoltaic system is a function of the solar irradiation, cell temperature, and characteristics of the photovoltaic array, the analytic solution for obtaining the maximum power is difficult to obtain due to its complexity, nonlinearity, and uncertainties of parameters. The innovation of this work is to obtain the maximum power of the photovoltaic system using a neural network with the idea of transferring the maximum-power-point tracking problem into a proportional-integral current control problem despite the variation in solar irradiation, cell temperature, and the electrical load characteristics. The current controller parameters are determined via a genetic algorithm for finding the controller parameters by the minimization of a complicatedly nonlinear performance index function. The experimental result shows the output power of the photovoltaic system, which consists of the series connection of two 155-W TYN-155S5 modules, is 267.42 W at certain solar irradiation and ambient temperature. From the simulation and experimental results, the validity of the proposed controller was verified.

Maximum Power Point Tracking (MPPT) for a Solar Photovoltaic System: A Review

2015 ◽  
Vol 787 ◽  
pp. 227-232 ◽  
Author(s):  
L.A. Arun Shravan ◽  
D. Ebenezer
Keyword(s):  
Solar Energy ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Nonlinear Behaviour ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In recent years there has been a growing attention towards use of solar energy. Advantages of photovoltaic (PV) systems employed for harnessing solar energy are reduction of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behaviour of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. This paper reviews various MPPT methods based on three categories: offline, online and hybrid methods. Design of a PV system in a encoding environment has also been reviewed here. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.

Maximum Power Point Tracking of Multi-String Photovoltaic Array via Simultaneous Perturbation Stochastic Approximation

2013 ◽  
Author(s):  
Yan Xiao ◽  
Yaoyu Li ◽  
John E. Seem ◽  
Kaushik Rajashekara
Keyword(s):  
Stochastic Approximation ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Simultaneous Perturbation Stochastic Approximation ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

This paper presents a Maximum Power Point Tracking (MPPT) strategy for multi-string photovoltaic (PV) systems using the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. The multi-string PV system considered is a decentralized control configuration, controlling the voltage reference to each PV module but based on the feedback of the total power at the DC bus. This requires only one pair of voltage and current measurements. The MPPT control problem for such topology of multi-string PV systems features a high input dimension, which can dramatically slow down the searching process for the real-time optimization process involved. The SPSA algorithm is considered in this study due to its remarkable capability of fast convergence for high dimensional search problems endorsed by various applications recently. Simulation study is performed for an 8-string PV system, and experimental study is performed for a 4-string PV system. Good performances are observed for both simulation and experimental results.

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