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《工程(英文)》 >> 2020年 第6卷 第7期 doi: 10.1016/j.eng.2020.06.004

基于Jaya学习的独立光伏、风机和电池系统的最佳容量优化

COMSATS University Islamabad, Islamabad 44000, Pakistan

收稿日期: 2018-11-03 修回日期: 2020-03-26 录用日期: 2020-06-12 发布日期: 2020-06-19

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摘要

可再生能源(renewable energy source, RES)被认为是可靠的、绿色的发电资源。光伏(photovoltaic, PV)和风力涡轮机(wind turbine, WT)被用来为偏远地区提供电力。在独立环境中,确定混合型RES的最佳容量是一个非常重要的挑战。过去提出的元启发式算法依赖于特定算法的参数来获得最优解。本文提出了一种Jaya混合算法和一种基于“教与学”的优化算法(teaching–learning-based optimization, TLBO),称为JLBO算法,其用于确定PV-WT-电池混合系统的最优单位容量,从而以最小的年度总成本(total annual cost, TAC)满足消费者的负载需求。系统的可靠性由最大允许的供电损失率(maximum allowable loss of power supply probability, LPSPmax)来衡量。比较JLBO算法与原Jaya、TLBO和遗传算法的结果,结果表明,在TAC方面,PV-WT-电池混合系统是最经济的方案。与PV-电池和WT-电池系统相比,该系统可以为所有提出的LPSPmax值都提供一个经济有效的解决方案。

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