An Optimized PV Control System Based on the Emperor Penguin Optimizer

Mariam A Sameh,Mahmoud A Attia,Mostafa I Marei,M A Badr

doi:10.3390/en14030751

Mariam A Sameh, Mahmoud A Attia + Show 2 more

Open Access

https://doi.org/10.3390/en14030751

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Journal: Energies	Publication Date: Feb 1, 2021
Citations: 24	License type: CC BY 4.0

Affiliation: Future University in Egypt, Ain Shams University

Abstract

During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm (CFA). Moreover, particle swarm optimization (PSO) algorithm is used as a reference algorithm to compare results with both EPO and CFA. PSO is chosen since it is an old, well-tested, and effective algorithm. For the evaluation of performance of the proposed PV system using the proposed algorithms under different PS conditions, results are recorded and introduced.

Highlights

Worldwide, the increased awareness of the drawbacks of fossil fuels raised up the interest in developing renewable energy-based power plants
This study is defined to be multi-constrained and single objected. It aims to tune the initial settings of duty cycle of the boost converter, in addition to the gains of the second order amplifier (SOA) and the gains of the PI controller used for the DC-link voltage regulation
The irradiance of one PV array is set at the maximum value of 1000 W/m2, while the irradiance of the second PV array is set to a specific profile according to the case under study

Summary

Introduction

The increased awareness of the drawbacks of fossil fuels raised up the interest in developing renewable energy-based power plants. Solar energy had a lot of research interest globally since it depends on ever-lasting resource, which is the sun. Because it is power electronic based, it is dependent on the speedy electronics field development. Several maximum power point tracking (MPPT) approaches are proposed [1,4]. Having multiple peaks means that there are several local maximum power points This can confuse the MPPT control unit in its search for the global MPP, where it may be trapped in a local MPP region, not the global one. Most of the optimization algorithms would reach an optimum solution in a relatively short time with minimum complexity With their continuous improvement in the last few years, a fitting solution is always expected. The performance of the proposed EPO algorithm is compared with the particle swarm optimization (PSO) [32] and cuttlefish algorithm (CFA) under different PS patterns and dynamic changes in irradiance levels

PV System under Study

Objective Function

Results and Comparison

Conclusions