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Abstract
By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model. In addition, the efficiency of the PV panel is established by the genetic algorithm under the standard test conditions (STC) and a comparison between the theoretical and experimental results is done to achieve maximum performance ranging from 0.15 to 0.16, particularly with an error of about - 0.333 for an experimental power of 30 Watts compared with the theoretical power of 30.1 Watts. The results obtained by the genetic algorithm give the best value for efficiency at the range of 16% to 17% of solar radiation, from 500–600 W/m2. These values are almost identical to the efficiency obtained from the results of the operation, where the best value for efficiency in the experimental results was seen to be 15.7%.
Highlights
Due to the increasing demand for clean and renewable energy applications, to avoid increasing CO2 release into the environment, there is a growing demand for electrical energy, in Iraq
The optimum efficiency of the solar panel was obtained and was found to be in the range of 0.16 to 0.17, when the solar radiation was in the range of 500 to 600 W/m2, such as is displayed in Figures 6 to 8
The modeling process was based on the genetic algorithm that had been proposed to obtain the optimal values for solar panel efficiency; a single-diode model was used
Summary
Due to the increasing demand for clean and renewable energy applications, to avoid increasing CO2 release into the environment, there is a growing demand for electrical energy, in Iraq. The results obtained from Matlab-Simulink were compared with the results processed by the manufacturer’s data sheet and were acceptable They employed the genetic algorithm to extract the optimal parameters from the photovoltaic module. Zagrouba et al (2010) studies, depend on the approach of the genetic algorithm to identify the parameters of the PV cell and PV module (Is, Iph, Rs, Rash, and n) [11] These parameters are used to find maximum power. The plan is to extract the optimum potency of the photovoltaic panel and to enhance the accuracy of the solar cell parameters, which can be gained by exploitation of direct techniques and an experimental study. The examination will give the efficiency gained from the genetic algorithmic program, along with the efficiency gained from experimental study
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