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首页> 外文期刊>Applied artificial intelligence >A New Approach for Optimal Sizing of a Grid Connected PV System Using PSO and GA Algorithms: Case of Tunisia
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A New Approach for Optimal Sizing of a Grid Connected PV System Using PSO and GA Algorithms: Case of Tunisia

机译：A New Approach for Optimal Sizing of a Grid Connected PV System Using PSO and GA Algorithms: Case of Tunisia

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Due to the excessive use of photovoltaic (PV) systems as a grid connected or standalone micro-grid, and high installation cost of these systems, it is recommended and required to properly size them. This research paper presents and offers a new approach for determining the optimum grid connected PV size, feeding a typical house in Tunisia, as well as the efficient power flow management, in order to improve its profitability, reliability and feasibility under a 20-year study period. A multiobjective function is proposed and formulated to be optimized using two optimization algorithms, which are the particle swarm optimization (PSO) and the genetic algorithm (GA). In fact, the objectives consider the economic aspect in terms of maximizing the net present value (NPV) and a non-economic concern, including minimizing the lost of power supply probability (LPSP). Simulation results showed that the PSO algorithm is faster than the GA and presents better performance in terms of speed convergence toward the optimal solution. Then, it proved that a PV system comprising 56 PV modules, 7 batteries and 2 inverters based on maximizing the NPV can sustainably augment its profitability, while a PV system comprising 66 PV modules, 10 batteries and 2 inverters can guarantee its reliability and feasibility, based on minimizing the LPSP.

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