Hybrid photovoltaic maximum power point tracking of Seagull optimizer and modified perturb and observe for complex partial shading
Document Type
Article
Publication Date
1-1-2022
Abstract
Due to natural randomness, partial shading conditions (PSCs) to photovoltaic (PV) power generation significantly drop the power generation. Metaheuristic based maximum power point tracking (MPPT) can handle PSCs by searching PV panels' global maximum power point (GMPP). However, trapped at local maxima, sluggishness, continuous power oscillations around GMPP and inaccuracy are the main disadvantages of metaheuristic algorithm. Therefore, the development of algorithm under complex PSCs has been continuously attracting many researchers to yield more satisfying results. In this paper, several algorithms including conventional and metaheuristic are selected for candidate, such as perturb and observe (P&O), firefly (FF), differential evolution (DE), grey wolf optimizer (GWO) and Seagull optimizer (SO). From the preliminary study, SO has shown best performance among other candidates. Then, SO is improved for rapid global optimizer. Modified variable step sizes perturb and observe (MVSPO) is applied to enhance the accuracy tracking of SO. To evaluate the performances, high complexity multipeak partial shading is used to test the algorithms. Statistical results are also provided to analyze the trend of performances. The proposed method performances are shown better fast-tracking time and settling time, high accuracy, higher energy harvesting and low steady-state oscillations than other candidates © 2022 Institute of Advanced Engineering and Science. All rights reserved.
Keywords
Complex partial shading, High accuracy, Maximum power point tracker, Power oscillations, Rapid optimizer
Divisions
sch_ecs
Publication Title
International Journal of Electrical and Computer Engineering (IJECE)
Volume
12
Issue
5
Publisher
Institute of Advanced Engineering and Science