The energy storage system is a complex energy system that changes with time. Multiple indicators are required to describe its performance, and different application scenarios have different requirements for the energy storage system. To solve the above problems, a cloud model-based method for evaluating the adaptability of electrochemical energy storage conditions is proposed. In the application scenario of energy storage participating in power grid peak and frequency regulation, comprehensive evaluation indicator domain and standard domain for energy storage system suitable for power grid peak regulation and frequency regulation are established firstly. Then, the entropy weight method is used to calculate weight matrix of energy storage system evaluation indicators. The forward cloud generator is used to calculate the membership matrix of the decision-making indicators of the energy storage system to be evaluated. Finally, the comprehensive score of the adaptability of the energy storage system to be evaluated is calculated according to the fuzzy subset on the comprehensive evaluation standard domain of the energy storage system, and the one with the highest score is selected as the best energy storage system for this application scenario. The working condition adaptability of five electrochemical energy storage systems is simulated and analyzed. The results show that the lithium iron phosphate battery has the highest score. The lithium iron phosphate battery has the best working condition adaptability in the peak and frequency regulation scenario, which is consistent with the actual engineering.