面向风电场的主动支撑电网型分散式储能控制策略与优化配置

doi:10.11930/j.issn.1004-9649.202305132

摘要/Abstract

摘要：

面向新能源场站的分散式储能具有容量小、分散广、部署灵活、方便扩容等特点，降低了电池聚集所导致的事故危害隐患、规避了征地费用与配套建设成本高的问题，既可以针对节点进行精细化管理，又可以集群化控制，帮助新能源场站改善涉网性能、减少考核成本、提升发电效能。首先，基于“分散布置，集中控制”原则提出一种分散式储能集群化控制策略，将分散式储能虚拟成为集中式储能的形式，并根据储能荷电状态与健康状态对功率指令进行合理分配。其次，根据并网要求，设计了基于调频优先制定的风储协同控制策略。进一步参考江苏省考核细则，提出了主动支撑电网型的分散式储能配置优化模型。算例结果表明，配置一定规模储能可以减少考核成本、改善涉网性能。

关键词: 风储联合, 分散式储能, 涉网性能, 两个细则, 容量配置

Abstract:

A decentralized energy storage system for renewable energy stations has the characteristics of small capacity, wide dispersion, flexible deployment, and convenient expansion, which reduces the hidden dangers of accidents caused by battery aggregation and avoids the problem of high land acquisition and supporting construction costs. It can not only ensure refined management for nodes but also achieve cluster control, helping renewable energy stations improve grid-related operation performance, reduce assessment costs, and improve power generation efficiency. First of all, based on the principle of "decentralized layout and centralized control", a decentralized energy storage cluster control strategy is proposed, which virtualizes the decentralized energy storage into a centralized energy storage form and reasonably distributes power instructions according to the state of charge and state of health of energy storage. Secondly, according to the grid interconnection requirements, a coordinated control strategy for wind-storage systems based on frequency modulation priority is designed. By referring to the detailed rules of Jiangsu Province, a decentralized energy storage configuration optimization model is proposed to actively support the grid. The calculation example shows that the allocation of a certain scale of the energy storage system can reduce the assessment cost and improve the grid-related operation performance.

Key words: wind-storage system, decentralized energy storage system, grid-related operation performance, two detailed rules, capacity configuration

李成, 张婕, 石轲, 薛明华, 冯波. 面向风电场的主动支撑电网型分散式储能控制策略与优化配置[J]. 中国电力, 2023, 56(12): 238-247.

Cheng LI, Jie ZHANG, Ke SHI, Minghua XUE, Bo FENG. Control Strategy and Optimal Configuration of Active-Support-Grid Type Decentralized Energy Storage System for Wind Farms[J]. Electric Power, 2023, 56(12): 238-247.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305132

https://www.electricpower.com.cn/CN/Y2023/V56/I12/238

图/表 11

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项目	类别	要求	考核
功率预测	中短期	次日96点合格率不小于90%；第10日96点合格率不小于70%	超过月度总点数2%的每个不合格点按额定容量考核1元/MW
功率预测	超短期	第15 min点合格率不小于97%；第4 h点合格率不小于87%	每个不合格点按额定容量考核0.4元/MW
AGC	调节范围	20%~100%额定容量范围内连续可调	下限达不到20%，每超1%，考核15元/(MW·月)
	调节速度	10%额定容量/min	每降低0.1%额定容量/min，考核5元/(MW·月)
	调节精度	min{1.5%额定容量，0.05 MW}以内	每超0.1%额定容量，考核5元/(MW·月)
一次调频	投运率	达到98%	每低1%，考核0.1元/(MW·天)
一次调频	响应指数	风电场0.7	每低0.01，考核0.4元/(MW·天)

项目	类别	要求	考核
功率预测	中短期	次日96点合格率不小于90%；第10日96点合格率不小于70%	超过月度总点数2%的每个不合格点按额定容量考核1元/MW
功率预测	超短期	第15 min点合格率不小于97%；第4 h点合格率不小于87%	每个不合格点按额定容量考核0.4元/MW
AGC	调节范围	20%~100%额定容量范围内连续可调	下限达不到20%，每超1%，考核15元/(MW·月)
	调节速度	10%额定容量/min	每降低0.1%额定容量/min，考核5元/(MW·月)
	调节精度	min{1.5%额定容量，0.05 MW}以内	每超0.1%额定容量，考核5元/(MW·月)
一次调频	投运率	达到98%	每低1%，考核0.1元/(MW·天)
一次调频	响应指数	风电场0.7	每低0.01，考核0.4元/(MW·天)

参数	数值	参数	数值
充放电效率/%	90	ESS寿命/年	15
荷电状态上限	0.8	设备价格/万元·套^–1	47
荷电状态下限	0.2	贴现率/%	8

参数	数值	参数	数值
充放电效率/%	90	ESS寿命/年	15
荷电状态上限	0.8	设备价格/万元·套^–1	47
荷电状态下限	0.2	贴现率/%	8

ESS 编号	SOC	分配系数		ESS 编号	SOC	分配系数
ESS 编号	SOC	充电	放电	ESS 编号	SOC	充电	放电
#1	0.57	0.02	0.03	#21	0.63	0.02	0.03
#2	0.49	0.03	0.02	#22	0.44	0.03	0.02
#3	0.67	0.01	0.04	#23	0.50	0.03	0.02
#4	0.72	0.01	0.04	#24	0.41	0.04	0.02
#5	0.78	0	0.04	#25	0.49	0.03	0.02
#6	0.49	0.03	0.02	#26	0.39	0.04	0.01
#7	0.74	0.01	0.04	#27	0.76	0	0.04
#8	0.68	0.01	0.04	#28	0.54	0.02	0.03
#9	0.69	0.01	0.04	#29	0.33	0.04	0.01
#10	0.72	0.01	0.04	#30	0.37	0.04	0.01
#11	0.74	0.01	0.04	#31	0.48	0.03	0.02
#12	0.64	0.01	0.03	#32	0.23	0.05	0
#13	0.55	0.02	0.03	#33	0.39	0.04	0.01
#14	0.49	0.03	0.02	#34	0.44	0.03	0.02
#15	0.27	0.05	0.01	#35	0.53	0.02	0.03
#16	0.72	0.01	0.04	#36	0.29	0.05	0.01
#17	0.38	0.04	0.01	#37	0.48	0.03	0.02
#18	0.49	0.03	0.02	#38	0.73	0.01	0.04
#19	0.23	0.05	0	#39	0.56	0.02	0.03
#20	0.47	0.03	0.02	#40	0.41	0.04	0.02