Multi-objective capacity optimisation method for renewable energy generation systems based on artificial bee colony algorithm

Hongwei Dong, Zhuoyu Jiang, Tao Han and Jingyuan Yin

International Journal of Energy Technology and Policy, 2024, vol. 19, issue 1/2, 35-49

Abstract: In order to reduce energy loss and improve charging and discharging efficiency, a multi-objective capacity optimisation method for renewable energy power generation systems based on artificial bee colony algorithm is proposed. Firstly, build models for wind power, optoelectronics, and batteries. Secondly, a multi-objective capacity optimisation objective function for renewable energy generation systems is constructed from three aspects: the daily cost borne by power users, the volatility of wind and solar energy, and the energy loss of storage batteries, and constraint conditions are set. Finally, artificial bee colony algorithm is used to continuously search for new honey sources, in order to obtain the optimal solution of the optimisation objective function and achieve multi-objective capacity optimisation of the power generation system. The experimental results show that this method can effectively reduce the energy loss, the daily energy loss is about 0.1 kWh, and the charging and discharging efficiency is always above 91%.

Keywords: artificial bee colony algorithm; renewable energy; power generation system; multiple objectives; capacity planning. (search for similar items in EconPapers)
Date: 2024
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