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基于风电场景概率的电热混合储能优化配置

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为有效提高风电入网的经济性和可行性,文中提出一种考虑风电典型场景概率的电热混合储能优化配置方案.首先通过场景分析,利用K-means聚类法将大量风机历史出力数据简化为6个典型出力场景,确定各场景发生的概率,其中聚类数目由肘部曲线法和Dunn指数法综合确定;其次提出电热混合储能系统控制策略,建立适用于多场景的风储联合系统模型;最后,以经济性成本最低与弃风量最小为目标,建立包含电、热负荷综合响应的容量配置优化模型,并将场景概率以权值的形式加入到目标函数中,采用粒子群算法求解模型.通过仿真分析和与其他储能配置场景对比,发现所提配置策略能够提高风电利用率约16.12％,同时减少系统综合成本约43.76％,验证了所提策略的合理性和有效性.
Optimized configuration of electro-thermal hybrid energy storage capacity based on wind power scenario probabilistic
In order to effectively improve the economy and feasibility of wind power grid access,an optimal configuration scheme of electric-thermal hybrid energy storage considering the probability of typical scenarios of wind power is proposed.Firstly,using scenario analysis and K-means clustering method,a large amount of wind power historical data is simplified into six typical output scenarios and the probability of each scenario is established.The number of clusters is determined by the elbow curve method and the Dunn index method.Secondly,a control strategy for electric-thermal hybrid energy storage system is proposed and a combined wind-storage system model applicable to multiple scenarios is established.Finally,a capacity configuration optimization model containing the integrated response of electric and thermal load with the objective of minimizing the economic cost and the amount of abandoned wind is established.The scenario probabilities are added to the objective function in the form of weights.The model is solved by particle swarm algorithm.Through simulation analysis and comparison with other energy storage configuration scenarios,it is verified that the proposed configuration strategy can improve wind power utilization by about 16.12％while reducing the overall system cost by about 43.76％.

hybrid energy storagecapacity configurationparticle swarm optimization algorithmK-means clusteringwind power uncertainty quantificationintegrated energy system for electricity and heat

李家珏、刘子祎、白伊琳、张潇桐、李平、宋政湘

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国网辽宁省电力有限公司电力科学研究院,辽宁沈阳 110006

国网国际发展有限公司,北京 100031

西安交通大学(电工材料电气绝缘全国重点实验室),陕西西安 710049

混合储能 容量配置 粒子群优化算法 K-means聚类 风电不确定性量化 电热综合能源系统

新疆维吾尔自治区重点研发计划辽宁省"兴辽英才计划"青年拔尖人才项目

2022B01019-2XLYC2007100

2024

10.12158/j.2096-3203.2024.03.018

电力工程技术
江苏省电力公司 江苏省电机工程学会

电力工程技术

CSTPCD北大核心
影响因子：0.969
ISSN：2096-3203
年,卷(期)：2024.43(3)
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