Use of Wiener- Hammerstein (WH) Model Optimized with Genetic ‎Algorithm in Identification of Photovoltaic System

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

System identification is a method of identification or measuring a mathematical model of a system by measuring the inputs and outputs of the system. In this paper we apply the Genetic Algorithm (GA) approach to model a photovoltaic (PV) ‎systems with a Wiener-Hammerstein structure. Non-linear dynamic systems have both ‎dynamic elements (energy storage elements) and in these types of systems there are non-linear ‎relationships between some variables. If in such systems it can be assumed that dynamic parts ‎and non-linear parts are separable, they can be modeled with the structures of block-oriented ‎models. These types of models are composed of a combination of linear dynamic block(s) and ‎static nonlinear block(s). This approach is concerned with the ‎estimation of a photovoltaic ‎‎(PV) system based on observed data. The nonlinear input and output ‎are taken from the ‎irradiance and DC output current data of the real system, respectively. The ‎simulation results ‎revealed the effectiveness and robustness of the proposed ‎model using a genetic algorithm. ‎The simulation results show an MSE value of ‎0.000774‎ for ‎normal operation of the PV ‎system‎ and ‎0.009863‎ for the shading effect‎ between the estimated ‎and reference information ‎rates.

Language:
Persian
Published:
Journal of Southern Communication Engineering, Volume:14 Issue: 54, 2025
Pages:
35 to 46
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