Global maximum operating point tracking for PV system using fast convergence Firefly algorithm

Madhusmita Mohanty ,Sankar Selvakumar ,Chandrasekaran Koodalsamy ,Sishaj P Simon

doi:10.3906/elk-1805-108

Abstract

Global maximum operating point (GMOP) tracking is an important requirement of solar photovoltaic (PV) systems under partial shading conditions (PSCs). Though the perturb and observe algorithm is simple and effective, it fails to recognize the GMOP. This paper explores the application of the firefly algorithm (FA) to the maximum power point tracking (MPPT) problem of PV systems. In order to determine the shortest path to reach the GMOP under various PSCs, a new fast convergence firefly algorithm (FA) is proposed. Additionally, the change in firefly position is limited to a maximum value identified based on the characteristics of the PSC. The fast convergence method is guaranteed to find the GMOP, avoiding the local operating point obstacle through a repeated space search technique. Using MATLAB, the algorithm is implemented on a model PV system. An experimental 300-W PV system is developed to validate the operating point of the PV system under various PSCs. The proposed method is tested on a 5-kW solar power plant. The results demonstrate that the proposed MPPT algorithm outperforms particle swarm optimization, FA-based MPPTs, and other methods available in the literature.

Highlights

Harvesting solar energy is efficient and sustainable, presenting a possible solution to the global energy crisis
One of the works on partial shading of PV systems reported an efficient manner by which partial shading conditions (PSCs) can be detected and how the global maximum power point (GMPP) can be tracked [7]
This paper has presented fast convergence firefly algorithm (FCFA), a new maximum power point tracking (MPPT) algorithm based on firefly behavior, for fast tracking of the Global maximum operating point (GMOP) of partially shaded PV arrays

Summary

Introduction

Harvesting solar energy is efficient and sustainable, presenting a possible solution to the global energy crisis. In PV systems, maximum power point tracking (MPPT) methods such as perturb and observe (P&O) and incremental conductance [3] can be implemented to track the optimal operating point They suffer from the steady-state oscillations that occur around the peak and failure during rapid change in insolation, which reduces the efficiency of the PV system [4]. One of the works on partial shading of PV systems reported an efficient manner by which PSCs can be detected and how the global maximum power point (GMPP) can be tracked [7]. Following the interest in this algorithm, this paper transforms the FF method for designing an intelligent MPPT scheme to determine GMOP, maintaining inheritance of firefly behavior while adding fast convergence properties In this context, the fast convergence firefly algorithm is proposed to track the GMOP under normal irradiance and in various PSCs of PV systems, which improves all the performance aspects in real time. Where Ppv is the output power of the PV panel; dmin and dmax are respectively the minimum and maximum values of the duty ratio, taken to be 10% and 90%, respectively; and d is the duty ratio of the boost converter

Firefly algorithm

Results and discussion

Conclusion