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考虑"风-荷"不确定性的海上"风-储"协同调峰优化模型

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海上"风-储"协同有利于提高电力系统运行稳定性,但其易受海况影响,运维难度较高.提出在电力物联网的环境下面向海上风电的储能集群协同调峰的控制方法.考虑了海上风电出力的模糊性,建立风电功率的模糊机会约束模型,并将模糊机会约束条件转化为等价清晰类,以最低运行成本和最小弃风量为目标,综合考虑系统以及各设备的运行约束条件,分别建立风-火、风-火-储调峰模型,使用布谷鸟搜索算法求出最优解.通过算例分析,结果表明,火-储联合调峰能够更好地消纳风能,并且减少系统运行成本,提高经济效益.
A Collaborative Peak Shaving Optimization Model for Offshore"Wind-Storage"Considering the Uncertainties of"Wind-Load"
The collaboration of offshore the"wind-storage"system helps to improve the stability of power system operation,but it is easily affected by sea conditions and has higher difficulty in operation and maintenance.This paper proposes a control method for collaborative peak shaving of energy storage clusters for offshore wind power in the context of the power Internet of Things.Considering the fuzziness of offshore wind power output,a fuzzy chance constraint model for wind power is established,and the fuzzy chance constraint conditions are transformed into equivalent clear classes.With the goal of minimum operating cost and minimum abandoned wind volume,the wind-thermal and wind-thermal-storage peak shaving models are established respectively by comprehensively considering the operating constraints of the system and various equipment.The cuckoo search algorithm is used to find the optimal solution.The results of the case analysis show that the collaborative peak shaving of the thermal-storage system can better absorb wind energy,reduce system operating costs,and improve economic benefits.

offshore wind powerenergy storage clustercollaborative peak shaving"wind-storage"collaboration"wind-load"uncertainties

刘国伟、吴杰康、马楠、王益军、辛立胜、唐文浩

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深圳供电局有限公司,广东深圳 518000

广东工业大学自动化学院,广东广州 510006

海上风电 储能集群 协同调峰 "风储"协同 "风-荷"不确定性

广东省基础与应用基础研究基金区域联合基金——粤港澳研究团队项目中国南方电网有限责任公司科技项目

2020B1515130001090000KK52222158

2024

电网与清洁能源
西北电网有限公司　西安理工大学水电土木建筑研究设计院

电网与清洁能源

CSTPCD北大核心
影响因子：1.122
ISSN：1674-3814
年,卷(期)：2024.40(7)