基于改进型量子遗传算法的储能系统容量配置与优化策略

doi:10.12028/j.issn.2095-4239.2018.0240

储能科学与技术 ›› 2019, Vol. 8 ›› Issue (3): 551-558.doi: 10.12028/j.issn.2095-4239.2018.0240

基于改进型量子遗传算法的储能系统容量配置与优化策略

夏新茂¹, 关洪浩¹, 丁鹏飞², 孟高军²

1 国网新疆电力有限公司经济技术研究院, 新疆乌鲁木齐 8300111;
2 江苏省配电网智能技术与装备协同创新中心, 江苏南京 210000

收稿日期:2018-12-10 修回日期:2019-01-04 出版日期:2019-05-01 发布日期:2019-01-14
通讯作者: 孟高军,副教授,E-mail:gjun_m@126.com
作者简介:夏新茂(1975-),男,工程师,从事电力系统规划设计等。
基金资助:
国家重点研发计划课题（2017YFB0903500），国家自然科学基金（51777197），国家电网公司科技项目（5230HQ26016U）。

Capacity allocation and optimization strategy of an energy storage system based on an improved quantum genetic algorithm

XIA Xinmao¹, GUAN Honghao¹, DING Pengfei², MENG Gaojun²

1 State Grid Xinjiang Electric Economy and Technology Research Institute, Urumqi 830011, Xinjiang, China;
2 Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing 210000, Jiangsu, China

Received:2018-12-10 Revised:2019-01-04 Online:2019-05-01 Published:2019-01-14

摘要/Abstract

摘要： 针对用于电网削峰填谷的储能系统容量配置经济性不足的问题，本文提出一种基于改进型量子遗传算法的储能系统容量经济性评估方法。首先，建立储能系统削峰填谷的数学模型，并在综合考虑充放电、荷电状态及潮流平衡等约束下进行储能系统的容量配置，在此基础上，采用内点法将约束问题转化为非约束问题进行求解，随后，应用改进型量子遗传算法优化储能系统容量配置方案，以缩短运算周期、提高算法计算效率与全局寻优能力，并使储能系统经济性成本最低。最后，通过算例证明了在约束条件下，所提方法使储能系统在满足对日负荷削峰填谷的前提下，实现最优经济成本的容量配置，为储能系统容量配置提供了有效参考。

关键词: 储能技术, 削峰填谷, 遗传算法, 容量配置, 经济成本

Abstract: This paper proposes a method for economic evaluation of energy storage system capacity using an improved quantum genetic algorithm. First, a mathematical model was established for the peak-filling valley of the energy storage system with the capacity allocation of the energy storage system carried out under the constraints of charge and discharge, state of charge and power balance. On this basis, an internal point method was used to transform the constrained the problem into a solvable unconstrained one. Then the improved quantum genetic algorithm was used to optimize the energy storage system capacity configuration for shortening the calculation time, improving the algorithm calculation efficiency and global optimization ability, meeting the technical requirements and engineering indexes of the energy storage system, and minimizing the cost of the energy storage system. Finally, an example analysis was performed to validate that the proposed method, enabling the energy storage system to realize its optimal economic cost capacity configuration while satisfying the peak load and valley filling of the daily load.

Key words: energy storage technology, peak clipping and valley filling, genetic algorithm, capacity onfiguration, economic cost

中图分类号:

TK912.9

夏新茂, 关洪浩, 丁鹏飞, 孟高军. 基于改进型量子遗传算法的储能系统容量配置与优化策略[J]. 储能科学与技术, 2019, 8(3): 551-558.

XIA Xinmao, GUAN Honghao, DING Pengfei, MENG Gaojun. Capacity allocation and optimization strategy of an energy storage system based on an improved quantum genetic algorithm[J]. Energy Storage Science and Technology, 2019, 8(3): 551-558.

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基于改进型量子遗传算法的储能系统容量配置与优化策略

Capacity allocation and optimization strategy of an energy storage system based on an improved quantum genetic algorithm

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