Survey and Classification of Hybrid GMPPT Techniques for Photovoltaic System under Partial Shading Conditions

A maximum power point tracking process is a very important task to harvest the maximum power available from a photovoltaic generator. For this reason, resorting to the development of new and more effective methods is an absolute necessity. Numerous advanced methods have been successfully employed to extract the real maximum point, such as neural networks and metaheuristic techniques. These techniques deal effectively in such conditions. However, the use of the algorithm alone has some limitations. In order to solve these drawbacks, the combination of two or more different techniques provides more advantages over single MPPT algorithms and improves the performance of the overall system. This paper mainly focus in reviewing the most important and recent hybrid global MPPT techniques proposed in the literature and proposes a classification of these methods with a comparison of their performances. All surveyed hybrid GMPPT methods are divided into four categories according to algorithms types involved in the MPPT method. This review study intends to make it easier for the user to make the convenient selection of which method to adopt especially in the presence of a variety of methods which are continuously developing in the literature. For this reason, resorting to the development of new and more effective methods is an absolute necessity to avoid the aforementioned problems. In the same context, numerous advanced methods have been successfully employed to extract the real maximum point, such as neural networks and metaheuristic techniques. These techniques deal effectively in such conditions. However, the use of the algorithm alone has some limitations. In order to solve these drawbacks, the combination of two or more different techniques provides more advantages over single MPPT algorithms and improves the performance of the overall system. This paper mainly focus in reviewing the recent hybrid global MPPT techniques proposed in the literature and proposes a classification of these methods with a comparison of their performances. All surveyed hybrid GMPPT methods are divided into four categories according to algorithms types involved in the MPPT method. This review study intends to make it easier for the user to make the convenient selection of which method to adopt especially in the presence of a variety of methods which are continuously developing in the literature

Study and simulation of photovoltaic systems with differences connecting topologies of microinverters configurations

International audienceThis paper focuses in the optimization of the efficiency of photovoltaic power conversion chain; we present the optimization of the efficiency of photovoltaic power conversion chain. In this way, we present a new alternative for improving both the performance of photovoltaic (PV) systems and the efficiency of the energy conversion by using different configuration of power converters. Different type's improvements have been proposed of architecture in order to choose the correct PV architecture for each PV installation on the efficiency improvement in all power conversion level stages between PV cells and loads. In this context, this work presents the study and adaptive simulation of photovoltaic systems with micro inverters configurations for applications of renewable energy. We performed comparative between a central and distribution connection of converter via an adaptation floor with Maximum Power Point Tracker (MPPT) control. For thisreason, it is important to know different types of architecture in order to choose the correct PV architecture for each PV installation. Simulation results are used to demonstrate the proposed topologies to provide improvement in efficiency over existing traditional PV systems

Intelligent maximum power point trackers for photovoltaic applications using FPGA chip: A comparative study

In this paper, various intelligent methods (IMs) used in tracking the maximum power point and their possible implementation into a reconfigurable field programmable gate array (FPGA) platform are presented and compared. The investigated IMs are neural networks (NN), fuzzy logic (FL), genetic algorithm (GA) and hybrid systems (e.g. neuro-fuzzy or ANFIS and fuzzy logic optimized by genetic algorithm). Initially, a complete simulation of the photovoltaic system with intelligent MPP tracking controllers using MATLAB/Simulink environment is given. Secondly, the different steps to design and implement the controllers into the FPGA are presented, and the best controller is tested in real-time co-simulation using FPGA Virtex 5. Finally, a comparative study has been carried out to show the effectiveness of the developed IMs in terms of accuracy, quick response (rapidity), flexibility, power consumption and simplicity of implementation. Results confirm the good tracking efficiency and rapid response of the different IMs under variable air temperature and solar irradiance conditions; however, the FL-GA controller outperforms the other ones. Furthermore, the possibility of implementation of the designed controllers into FPGA is demonstrated

Evaluation and Performance of Different topologies of converters with Efficient MPPT in a Photovoltaic System

International audienc