Implementation of repowering optimization for an existing photovoltaic‐pumped hydro storage hybrid system: A case study in Sichuan, China
Implementation of repowering optimization for an existing photovoltaic‐pumped hydro storage hybrid system: A case study in Sichuan, China
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DOI：
10.1002/er.4846
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发表时间：
2019-09
影响因子：
4.6
通讯作者：
Xiao Xu;Weihao Hu;Di Cao;Wen Liu;Zhe Chen;H. Lund
中科院分区：
文献类型：
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作者：
Xiao Xu;Weihao Hu;Di Cao;Wen Liu;Zhe Chen;H. Lund
对于电网尚未延伸的偏远地区或孤岛，独立的混合能源系统可以为当地用户提供廉价且充足的电力。然而，随着社会的发展，负载需求将会增加，原有系统无法完全满足负载需求。这种情况发生在中国四川小金。该地区现有的光伏抽水蓄能（PV-PHS）混合系统作为原有系统，目前还不能完全满足负荷要求。 “重新供电”一词旨在最大限度地提高供电的可靠性和PV-PHS混合能源系统的利用率，这不同于传统的规划优化来构建所有组件。重新供电策略是将风力涡轮机（WT）和电池集成到原始系统中。对于重新供电系统，提出了一种电源管理策略来确定 PHS 和电池的工作模式。优化模型考虑了三个目标，即最小化未满足需求的百分比、能源平准化成本和可再生能源弃风率。模拟是通过单目标、双目标和三目标粒子群优化（PSO）技术进行的。对于单目标优化，对 PSO 和遗传算法（GA）进行了比较。对于双目标优化，将多目标粒子群算法（MOPSO）与加权和法（WSA）进行比较，并利用模糊满足方法来寻找双赢的解决方案。结果表明，在负载需求显着增加后，重新供电策略有助于实现供电的最大可靠性，而电池在这种混合系统中发挥着重要作用。
For a remote area or an isolated island, where the grid has not extended, a standalone hybrid energy system can provide cheap and adequate power for local users. However, with the development of society, the load demand will increase and the original system cannot completely meet the load demand. This situation occurs in Xiaojin, Sichuan, China. The existing photovoltaic‐pumped hydro storage (PV‐PHS) hybrid system in this area as the original system cannot completely meet the load requirements at present. The term “repowering” aims to maximize the reliability of power supply and the utilization of the PV‐PHS hybrid energy system that differs from traditional planning optimization to build all components. The repowering strategy is to integrate wind turbines (WTs) and battery into the original system. For the repowering system, a power management strategy is proposed to determine the operating modes of the PHS and battery. Three objectives, which are minimizing percentage of the demand not supplied, levelized cost of energy, and curtailment rate of renewable energy, are considered in the optimization model. Simulation is conducted by single‐objective, biobjective, and triobjective particle swarm optimization (PSO) techniques. For the single‐objective optimization, the comparison of PSO and genetic algorithm (GA) is made. For the double‐objective optimization, multiobjective PSO (MOPSO) is compared with weighted sum approach (WSA), and fuzzy satisfying method is utilized to find the win‐win solution. The results reveal that the repowering strategy can help to achieve maximum reliability of power supply after load demand increases significantly, and the battery plays an important role in such a hybrid system.