Journal
SOLAR ENERGY
Volume 202, Issue -, Pages 210-226Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2020.03.109
Keywords
Grid-connected photovoltaic plants; Modeling; Optimization; Genetic algorithm
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Funding
- National Research, Development and Innovation Fund (NKFIH) of Hungary [FIEK 16-1-2016-0007]
- National Research, Development and Innovation Fund [TUDFO/51757/2019-ITM]
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The increasing penetration of photovoltaic (PV) technology calls for the development of an effective method for optimization of grid-connected photovoltaic power plants. This paper presents a simultaneous optimization method of ten important design parameters of a PV plant, including the module power, inverter sizing, support structure dimensions, cable losses, module orientation and row spacing. A mathematical PV performance model taking into account the important effects and losses and an economic cost model were developed and presented in detail. The objective function is the internal rate of return and the optimization is performed by a genetic algorithm. The results show that the proposed models and method are capable to optimize the grid-connected PV plant and provide reliable results after a 6-7 min calculation time. The method was demonstrated in detail for a Hungarian location, including the losses and cost structure of the optimal plant configuration. The optimization was also performed for 5 additional sites around the world to assess the effect of location and meteorology. The impact of the decreasing PV module prices on the optimal design is calculated to identify the expected future trends in PV plant design. The presented optimization method can be utilized to facilitate the optimal design of commercial PV plants and for research purposes.
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