Open Access

ARTICLE

A Novel Hybrid MPPT Control Strategy for Isolated Solar PV Power System

D. Sabaripandiyan^1,*, H. Habeebullah Sait², G. Aarthi³

1 Department of EEE, Government Polytechnic College, Gandharvakottai, 613301, Tamil Nadu, India
2 Department of EEE, BIT Campus, Anna University, Tiruchirapalli, 620024, Tamil Nadu, India
3 Department of EEE, SRM TRP Engineering College, Tiruchirapalli, 621105, Tamil Nadu, India

* Corresponding Author: D. Sabaripandiyan. Email:

Intelligent Automation & Soft Computing 2022, 32(2), 1055-1070. https://doi.org/10.32604/iasc.2022.021950

Received 21 July 2021; Accepted 31 August 2021; Issue published 17 November 2021

Abstract

The main aspiration of this paper is to improve the efficiency of Solar Photovoltaic (SPV) power system with a new Hybrid controller for standalone/isolated Solar PV applications is proposed. This controller uses the merits of both Adapted Neuro-Fuzzy Inference System (ANFIS) and Perturbation & Observation (P&O) control techniques to concede rapid recovery at dynamic change of environment conditions such as solar irradiation and temperature. The ANFIS strategy itself has the merits over Fuzzy Logic and ANN methods. Conversely, P&O has its simplicity in implementation. Hence a case study for rapid recovery with the proposed controller and conventional P&O control strategy is carried out in this work. A SPV Module is associated to a load resistance with an interface of DC-DC step-up converter. A pattern of solar irradiation comprises of different static, dynamic, slow but sure increase with positive and negative slope are applied to the system and the response is observed. The proposed method is having the benefits of both P&O and ANFIS respectively to get better results on rapid change over conditions. The performance comparison of various MPPT algorithm of existing methods. The outcome demonstrates that the proposed hybrid-controller converges so rapid than the conventional P&O controller at dynamic situations and obeys at static and gradually varying environment conditions.

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Keywords

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