Validation of an Improved Optimization Technique for Photovoltaic Modeling
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ORIGINAL PAPER
Validation of an Improved Optimization Technique for Photovoltaic Modeling H. M. A. Mageed1*, W. El Maguid Ahmed2, S. Mohamed1 and A. A. Saleh3 1
High Voltage Department, National Institute of Standards (NIS), Giza 12211, Egypt
2
Engineering Mathematics and Physics Department, Faculty of Engineering, Fayoum University, Zewail City of Science and Technology, Fayoum 63514, Egypt 3
Electrical Department, Faculty of Engineering, Fayoum University, Fayoum 12522, Egypt Received: 21 May 2020 / Accepted: 07 August 2020 Metrology Society of India 2020
Abstract: Particle Swarm Optimization technique has been improved by fractional order calculus to be used for photovoltaic (PV) modeling. The modified technique which is called Fractional Order Darwinian Particle Swarm Optimization (FODPSO) has been constructed to estimate the optimal electrical parameters of PV modules. Single and double diode models have been used to designate the PV modules. FODPSO and PSO algorithms have been designed and applied on two different PV modules at different irradiances and temperatures. In order to validate the proposed modeling technique, Root Mean Square Error (RMSE) of the current, RMSE of power and Summation of the Individual Absolute Error (SIAE) results obtained using FODPSO and traditional Particle Swarm Optimization (PSO) algorithms have been compared. Minimum RMSE and SIAE have been achieved using the FODPSO technique. To verify the FODPSO results accuracy, accurate measurements of short circuit current, open circuit voltage, and maximum power, voltage at maximum power and current at maximum power have been performed for both PV modules. FODPSO-estimated results show excellent agreement with the experimental ones at different irradiances and temperatures. Keywords: Photovoltaic; Algorithm; Fractional Order Darwinian Particle Swarm Optimization (FODPSO); Particle Swarm Optimization (PSO); Modeling 1. Introduction Photovoltaic is considered one of the optimal choices for energy generation [1]. Allowing comprehensive study and evaluation of PV system performance before being installed within the different applications is crucial [2]. Modeling of PV modules is highly demanded for multiple terrestrial and space applications. Precise PV modeling enables highly accurate quality control and efficiency assessment of PV systems. The characteristic of the PV power generation is nonlinear influenced by external effects such as environmental conditions [3]. Accordingly, the main challenge is that an accurate PV model can be achieved by estimating the optimal electrical parameters at different environments [4]. There are many techniques used to accurately estimate PV models’ parameters. These
*Corresponding author, E-mail: [email protected]
techniques are classified into deterministic and heuristic techniques. Deterministic technique is an iterative approach which is based on Newton’s method. Gauss– Seidel iterative technique, Lambert W Function, and modified nonlinear least error squares estimation approach are th
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