基于风电场景概率的电热混合储能优化配置

本文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，以提高风电入网的经济性和可行性。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，利用粒子群算法对模型进行求解。通过仿真分析和与其他储能配置场景对比，我们发现所提出的配置策略能够提高风电利用率约11.04%，同时减少系统综合成本约44.52%，验证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

Considering the uncertainty of wind power output, an optimal configuration scheme for electric and thermal multi-energy storage system is proposed, to improve the economics and feasibility of wind power integration. 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, where 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 allocation optimization model containing the integrated response of electric and thermal loads with the objective of minimizing the economic cost and the amount of abandoned wind is established, and the scenario probabilities are added to the objective function in the form of weights. The model is solved using a particle swarm algorithm. Through simulation analysis and comparison with other energy storage configuration scenarios, we found that the proposed configuration strategy can improve wind power utilization by about 11.04% while reducing the overall system cost by about 44.52%, which verifies the rationality and effectiveness of the proposed strategy.