Query: GWO MPPT

title: An efficient GWO MPPT for a PV system using impedance information acceleration
abstract: This paper presents a novel maximum power point tracking (MPPT) method based on the grey wolf optimisation (GWO) technique for photovoltaic (PV) power generation systems. The proposed method utilises previous working duty cycles and their corresponding voltage and current data to compute the instantaneous DC impedance of a PV string. To determine the peak power characteristics of any PV string, the impedance variation of that PV string is used as an efficient shading factor. This shading factor simplifies the calculation of the GWO MPPT algorithm to obtain multiple peak targets under partial shading conditions. Thus, the efficiency of the proposed power tracking technique can be improved considerably. The effectiveness of this method was validated through both simulation and hardware implementations. Results revealed that the search performance of five iterations of the proposed method was similar to that of ten iterations of a traditional GWO MPPT method under normal conditions without shading. These results confirm the practicability of the proposed method in various applications.

title: A Fast Converging MPPT Control Technique (GWO) for PV Systems Adaptive to Fast Changing Irradiation and Partial Shading Conditions
abstract: 1M Tech. Scholar, EEE Department, REC Bhopal. 2Assistant Professor, EEE Department, REC Bhopal.  This document presents an implementation of the Dc Dc converter with an MPPT design (Power Point Tracking) for a photovoltaic (PV) system with a new optimization technique. The new optimization method that overcomes the limitations, such as the lower tracking efficiency, the steady state oscillations and the transients found in the perturbation and observation (P&O) and PSO techniques. The problem of tracking the global peak (GP) of a photovoltaic array in partial shadowing conditions is intended to be used to improve the MPPT technique. The proposed scheme is called gray wolf optimization, which has used the study studied for a multi peak PSC array and the tracking performance is compared to that of two MPPT algorithms, P&O MPPT and PSO MPPT. The GWO MPPT algorithm implemented in a photovoltaic system using MATLAB. In addition, an experimental configuration has been developed to verify the efficiency of the proposed system. The simulation obtained and the experimental results show that the proposed converter with the MPPT algorithm exceeds the MPPT of P&O and PSO.

title: A Novel Nature Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA GWO Algorithm for Partially Shaded Photovoltaic Systems
abstract: To overcome the real time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The proposed MPPT controller is achieved by combining salp swarm algorithm (SSA) with grey wolf optimizer (GWO) (namely, SSA GWO) The leader structure of the GWO algorithm is introduced into the basic SSA algorithm to enhance the global search capability. Numerical simulation on 13 benchmark functions was done to evaluate the proposed SSA GWO algorithm. Finally, the MPPT performance on PV system with the proposed SSA GWO algorithm under static and dynamic partial shading conditions was investigated and compared with conventional MPPT algorithms. The quantitative and simulation results validated the effectiveness and superiority of the proposed method.

title: A Novel dPdI feedback based control scheme using GWO tuned PID controller for efficient MPPT of PEM fuel cell.
abstract: At any operating condition, there is only one maximum power point (MPP) where proton exchange membrane fuel cell (PEMFC) is desired to operate. For this task, a maximum power point tracking (MPPT) controller is generally employed. In this paper, a novel and simple dPdI feedback based control scheme, employing Grey wolf optimizer (GWO) tuned PID controller, is proposed for efficient MPPT of PEMFC. The performance of the GWO tuned PID is controller is compared with two classical techniques namely, P&O and INC and for a fair comparison of choice of optimization method, the former was also compared with PSO tuned PID Performance of the proposed MPPT scheme is assessed under varying operating conditions using root mean square power ripple and maximum power ripple as performance metrics. Presented simulation results clearly indicate superiority of the proposed technique. Therefore, it is concluded that dPdI feedback scheme based GWO tuned PID controller is a more effective MPPT technique for PEMFC.

title: Comparative Analysis of ABC, Bat, GWO and PSO Algorithms for MPPT in PV Systems
abstract: Traditional algorithms used to perform the maximum power point tracking (MPPT) may not reach the global maximum power point (GMPP) when the photovoltaic (PV) modules are subjected to partial shading condition. Therefore, this paper presents a comparative analysis involving four MPPT algorithms employed in a PV system subject to partial shading condition, being these four MPPT techniques based on artificial bee colony, bat, grey wolf optimization and particle swarm optimization algorithms, respectively. These algorithms are always able to track the GMPP, presenting lower power oscillations in steady state. In addition, these algorithms are evaluated and compared to each other taking into account three different cases: (i) PV array operating at standard test condition with uniform solar irradiation; (ii) and (iii) PV array under different cases of partial shading. By means of computational simulation results, the performances of the presented MPPT algorithm are evaluated and compared to each other considering the power oscillations in steady state, the tracking factor, as well as the convergence time to reach the GMPP.

title: Improvement of maximum power point tracking (MPPT) efficiency using grey wolf optimization (GWO) algorithm in photovoltaic (PV) system

title: Maximum Power Extraction from Photo Voltaic Cell Based on MPPT System with GWO Algorithm

title: PENINGKATAN EFISIENSI MAXIMUM POWER POINT TRACKING (MPPT) MENGGUNAKAN ALGORITMA GREY WOLF OPTIMIZATION (GWO) PADA SISTEM PHOTOVOLTAIC (PV)
abstract: Indonesia merupakan salah satu Negara yang memiliki banyak sumber energi terbarukan, salah satunya adalah panas matahari. Panas matahari dapat dimanfaatkan menjadi sumber energi listrik, dengan menggunakan konsep photovoltaic. Photovoltaic menjadi sangat populer, karena sistem ini tidak menghasilkan polisi dan dapat dipasang dimana saja, termasuk pada daerah daerah terpencil. Tetapi, dalam penggunaan photovoltaic ditemukan beberapa masalah yang umum terjadi, adalah sulitnya mendapatkan daya maksimum dan setabil. Oleh karena itu untuk mengatasi permasalahan tersebut menggunakan metode Maximum Power Point Tracking. Pada sistem photovoltaic perlu menentukan converter yang akan digunakan untuk meningkatkan output daya dari photovoltaic.Dalam perancangan MPPT menggunakan algoritma grey wolf optimization yang dapat melacak daya output dengan cepat dan mengurangi osilasi pada sistem photovoltaic. Hasil dari pelacak daya maksimum dengan menggunakan algoritma grey wolf optimization lebih baik dari pada algoritma incremental conductance hingga 0,4 s. Converter yang digunakan menggunakan metode soft switching buck conveter utuk mengatasi losses daya yang sering timbul pada sistem photovotaic. Hasil dari output daya menggunakan soft switching buck conveter lebih besar dari pada menggunakan buck converter. Ketika membandingkan efisiensi pada sistem photovoltaic yang menggunakan algoritma grey wolf optimization meningkat dari pada menggunakan algoritma incremental conductance

title: Comparison method of MPSO, FPA, and GWO algorithm in MPPT SEPIC converter under dynamic partial shading condition
abstract: Solar energy can be utilized through photovoltaic (PV) into electrical energy. The output power of PV can reach maximum point when the irradiation of the sun is exposed to the surface without any object being obstructed. Unfortunately, In the actual implementation of irradiation received by PV it is often blocked by a moving object or a shadow of a non moving object. This problem resulted in the emergence of more than one maximum power point on the P V characteristic curve. The condition can't be solved by using the usual MPPT Algorithm so that MPPT Partial shading algorithm is required. Partial shading algorithm has been developed from conventional methods to artificial intelligence methods. Hence, in this paper proposed comparison method of MPSO, FPA, and GWO in MPPT SEPIC converter under dynamic partial shading condition. The level of accuracy of all three methods is validated through simulation. The simulation results show that the three methods are able to overcome the problem of partial shading very well with a high level of accuracy. The simulation results also show that the FPA method has advantages compared to other proposed methods. The simulation results also show that the MPSO method has more advantages compared to other proposed methods in tracking accuracy and the FPA method is faster to reach convergence situation by other proposed method.

title: Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO FLC
abstract: Maximum power point tracker (MPPT) techniques have been used to extract the maximum power available form photovoltaic (PV) energy systems. Conventional MPPT techniques like perturb and observe (PO one global maximum power point (GMPP) and many local maximum power points (LMPPs) Most of conventional MPPT techniques may stick to one of the LMPPs, which reduce the MPPT efficiency of PV systems. Soft computing techniques like particle swarm optimization (PSO) gray wolf optimization (GWO) and Cuckoo search optimization (CSO) etc. can catch the GMPP of PV system under the same PSC. These latter techniques suffer from two problems, the first problem is the high oscillations around the GMPP, the second problem is that, they cannot follow the new GMPP once it changed its position due to the searching agents will be busy around old GMPP caught. The solution of these two problems are the motivation of this research. GWO has been used to catch the GMPP and the problem of oscillations around the GMPP has been solved by hybridizing this technique with fuzzy logic controller (FLC) for soft tune the output generated power at the GMPP. The FLC characterizes by accurate GMPP catching with almost zero oscillations. The second problem is solved in this paper by reinitializing the GWO with two new initialization techniques. The results obtained from GWO FLC with two different re initialization techniques have been compared to the results of PSO without reinitializing its particles. The results obtained from this work prove the superior performance of the new proposed technique in terms of dynamic GMPP catching and MPPT power efficiency in case of time variant PSCs.