A Forensic-Based Investigation Algorithm for Parameter Extraction of Solar Cell Models

Abdullah M Shaheen,Sherif S M Ghoneim,Ragab A El-Sehiemy,Ahmed Rabie Ginidi

doi:10.1109/access.2020.3046536

Abstract

The accurate parameter extraction of photovoltaic (PV) module is pivotal for determining and optimizing the energy output of PV systems into electric power networks. Consequently, a Photovoltaic Single-Diode Model (PVSDM), Double Diode Model (PVDDM), and Triple- Diode Model (PVTDM) is demonstrated to consider the PV losses. This article introduces a new application of the Forensic-Based Investigation Algorithm (FBIA), which is a new meta-heuristic optimization technique, to accurately extract the electrical parameters of different PV models. The FBIA is inspired by the suspect investigation, location, and pursuit processes that are used by police officers. The FBIA has two phases, which are the investigation phase applying by the investigators team, and the pursuit phase employing by the police agents team. The validity of the FBIA for PVSDM, PVDDM, and PVTDM is commonly considered by the numerical analysis executing under diverse values of solar irradiations and temperatures. The optimal five, seven, and nine parameters of PVSDM, PVDDM, and PVTDM, respectively, are accomplished using the FBIA and compared with those manifested by various optimization techniques. The numerical results are compared for the marketable Photowatt-PWP 201 polycrystalline and Kyocera KC200GT modules. The efficacy of the FBIA for the three models is properly carried out checking its standard deviation error with that obtained from various recently proposed optimization techniques in 2020 which are Jellyfish search (JFS) optimizer, Manta Ray Foraging optimizer (MRFO), Marine Predators Algorithm(MPA), Equilibrium Optimizer (EO), Heap Based Optimizer (HBO). The standard deviations of the fitness values over 30 runs are developed to be less than $1 \times 10^{-6}$ for the three models, which make the FBIA results are extremely consistent. Therefore, FBIA is foreseen to be a competitive technique for PV module parameter extraction.

Highlights

Myriads of efforts have been developed to adjust the energy structure and increase renewable energy research in order to cope with the dramatically increasing of energy shortage and environment issues
The quality of Forensic-Based Investigation Algorithm (FBIA) is assessed measuring the experimental datasets under diverse environmental conditions of temperature and radiation values with handling the parameters of Photovoltaic Single-Diode Model (PVSDM), PVDDM and PVTDM models
SIMULATION RESULTS FBIA is employed on the Photowatt-PWP 201 polycrystalline module and Kyocera KC200GT module to extract the electrical PVSDM, PVDDM, and PVTDM parameters accurately

Summary

INTRODUCTION

Myriads of efforts have been developed to adjust the energy structure and increase renewable energy research in order to cope with the dramatically increasing of energy shortage and environment issues. The quality of FBIA is assessed measuring the experimental datasets under diverse environmental conditions of temperature and radiation values with handling the parameters of PVSDM, PVDDM and PVTDM models. These three models are utilized with, two sets of I-V data— namely, the measurements attained from the Photowatt-PWP 201 polycrystalline module and the KC200 [34]. A novel optimization technique called FBIA is introduced and tested for estimating the parameters for single, double and triple models of PV cells with two different PV modules. The FBIA is assessed with the measured experimental datasets under diverse environmental conditions of temperature and radiation values with handling the parameters of PVSDM, PVDDM and PVTDM models. In this article, the nine parameters of PVTDM have been examined with different recently developed optimization techniques to augment the accuracy of the model

4) OBJECTIVE FUNCTION FORMULATION

SIMULATION RESULTS

CONCLUSION