Multi-objective design of PV-wind-batteries hybrid systems by minimizing the annualized cost system and the loss of power supply probability (LPSP)

B. Bilal, V. Sambou, P. Ndiaye, C. F. Kébé, M. Ndongo
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引用次数: 43

Abstract

This paper deals with a methodology of sizing hybrid systems solar/wind/battery optimized by minimizing the annualized cost system (ACS) and the loss of power supply probability (LPSP) using multi-objective genetic algorithm. The developed methodology was applied using the hourly solar, temperature and the wind speed data collected for one year on the site of Potou located in the northwestern coast of Senegal. The annual average hourly load profile of a typical remote village located in the northwestern coast of Senegal which energy is of 94 kWh/day has been used. The obtained results show that the cost of the optimal configuration strongly depends on the loss of power supply probability (LPSP). For example, the cost of the optimal configuration decreases by 25 % when the loss of power supply probability (LPSP) grows to 1% from 0%.
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最小化年化成本系统和供电损失概率(LPSP)的光伏-风电池混合系统多目标设计
本文研究了利用多目标遗传算法,以最小化年化成本系统(ACS)和电力供应损失概率(LPSP)为优化目标,对太阳能/风能/电池混合系统进行优化的方法。所开发的方法是利用在塞内加尔西北海岸的Potou地点收集的一年每小时的太阳、温度和风速数据来应用的。位于塞内加尔西北海岸的一个典型偏远村庄的年平均小时负荷概况,其能源为94千瓦时/天。计算结果表明,最优配置的成本很大程度上取决于电源损耗概率(LPSP)。例如,当电源丢失概率(LPSP)从0%增加到1%时,最优配置的成本降低了25%。
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