Optimized configuration of electro-thermal hybrid energy storage capacity based on wind power scenario probabilistic

Abstract

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%.

Keywords

• hybrid energy storage
• capacity configuration
• particle swarm optimization algorithm
• k-means clustering
• wind power uncertainty quantification
• integrated energy system for electricity and heat