Energy storage participating in grid auxiliary services can effectively enhance the regulation capacity of the grid and promote the consumption of renewable energy, and the selection type of energy storage systems is the basis to ensure its safe and economic operation. Starting from the economics and safety of energy storage systems, an adaptive evaluation method of energy storage working conditions based on the cloud decision fusion is proposed. Aiming at strong subjective characteristics of the analytic hierarchy, an adaptability assessment model of energy storage working conditions based on the entropy weight-analysis hierarchy process method is established to obtain the scores of different types of energy storage systems. Aiming at the characteristics of ambiguity and randomness in decision-making indicators, an adaptability assessment model of energy storage working conditions based on the entropy weight-cloud model is established to obtain the scores of different types of energy storage systems. The results of the two scores are fused using Dempster-Shafer evidence theory to get the evaluation result of the best energy storage condition adaptability. In the application scenarios of the peak shaving and frequency regulation, the effectiveness of the proposed method is verified by simulation analysis of performance indicators of the peak shaving and frequency regulation. The simulation results show that the iron phosphate battery has the highest adaptability to work conditions of the peak shaving and frequency regulation, and the Dempster–Shafer evidence theory can eliminate the randomness and qualitative-quantitative doping of decision indicators on the selection type of energy storage systems, which can provide a theoretical basis for the planning of energy storage stations.

参与电网辅助服务的储能系统可以有效地提高电网的监管能力，促进可再生能源的消耗，而储能系统的选择类型是保证其安全经济运行的基础。从储能系统的经济性和安全性出发，提出了一种基于云决策融合的储能工况自适应评估方法。针对分析层次结构的主观性强的特点，建立了基于熵权-层次分析法的储能工况适应性评估模型，以获取不同类型储能系统的得分。针对决策指标中的歧义性和随机性，建立了基于熵权-云模型的储能工况适应性评估模型，以获取不同类型储能系统的得分。使用Dempster-Shafer证据理论将两个分数的结果融合，以获得最佳储能条件适应性的评估结果。在调峰调频的应用场景中，通过对调峰调频性能指标的仿真分析，验证了该方法的有效性。仿真结果表明，磷酸铁锂电池对削峰和调频的工作条件适应性最高，