基于改进人工蜂群算法的区域电网储能系统能量管理优化策略

doi:10.11930/j.issn.1004-9649.202101055

中国电力 ›› 2022, Vol. 55 ›› Issue (9): 16-22,55.DOI: 10.11930/j.issn.1004-9649.202101055

• 面向“双高”电力系统的电、热、氢储能应用与协同 • 上一篇下一篇

基于改进人工蜂群算法的区域电网储能系统能量管理优化策略

王子琪, 张慧媛, 许军, 程杰慧

华北电力大学电气与电子工程学院，北京 102206

收稿日期:2022-01-12 修回日期:2022-08-04 出版日期:2022-09-28 发布日期:2022-09-20
作者简介:王子琪（1996—），女，通信作者，硕士，从事储能技术研究，E-mail：wangziqi72@163.com;张慧媛（1963—），女，硕士，副教授，从事直流微电网与储能技术研究，E-mail：zhyseunj@aliyun.com;许军（1980—），男，博士，讲师，从事直流电网与储能技术研究，E-mail：xujun11@ncepu.edu.cn;程杰慧（1996—），女，硕士，从事电网调度优化研究，E-mail：huijiu19965@foxmail.com
基金资助:
国网新疆电力有限公司科技项目（5230DK180018）

An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm

WANG Ziqi, ZHANG Huiyuan, XU Jun, CHENG Jiehui

School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China

Received:2022-01-12 Revised:2022-08-04 Online:2022-09-28 Published:2022-09-20
Supported by:
This work is supported by Science and Technology Project of State Grid Xinjiang Electric Power Co., Ltd. (No.5230DK180018)

摘要/Abstract

摘要： 为提高新能源消纳水平及系统运行效率，需对储能系统充放电功率进行优化，以平抑功率波动，降低网络损耗，提高经济效益。基于源荷状态判断储能各时段充放电状态，以区域日网损降低收益、日高储低放套利收益及日环境效益最大为目标，综合考虑储能自身约束及网架潮流状态约束等条件，建立了区域电网储能能量管理优化模型。求解过程中提出了一种改进人工蜂群算法（improved artificial bee colony，IABC），并针对吐鲁番区域网架结构及运行特点进行了建模仿真。结果表明，对储能进行能量管理优化可提升整体经济效益，且改进人工蜂群算法具有很好的全局搜索能力及收敛性。

关键词: 储能, 源荷状态, 有功网损, 能量管理, 改进人工蜂群算法

Abstract: In order to improve the new energy consumption level and system operation efficiency, it is necessary to optimize the charging and discharging power of energy storage system, so as to stabilize power fluctuation, reduce network loss and improve economic benefits. In this paper, the charging and discharging of energy storage is selected for each period based on the source and load status, and an energy storage management optimization model is established for regional power grid with the objectives of reducing the daily network loss, maximizing the daily arbitrage of energy storage and the daily environmental benefits, which comprehensively considers the constraints of energy storage itself and grid power flow state. In the process of solving the model, an improved artificial bee colony (IABC) algorithm is proposed, and simulation is designed out according to the structure and operation characteristics of the Turpan regional grid. Simulation results show that the energy management optimization of energy storage can improve the overall economic benefits, and the improved artificial bee colony algorithm has good global search ability and convergence.

Key words: energy storage, source and load status, active power loss, energy management, improved artificial bee colony

王子琪, 张慧媛, 许军, 程杰慧. 基于改进人工蜂群算法的区域电网储能系统能量管理优化策略[J]. 中国电力, 2022, 55(9): 16-22,55.

WANG Ziqi, ZHANG Huiyuan, XU Jun, CHENG Jiehui. An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm[J]. Electric Power, 2022, 55(9): 16-22,55.

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基于改进人工蜂群算法的区域电网储能系统能量管理优化策略

An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm

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基于改进人工蜂群算法的区域电网储能系统能量管理优化策略

An Energy Management Optimization Strategy for Regional Power Grid Energy Storage System Based on Improved Artificial Bee Colony Algorithm

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