Randomized trial demonstrates high accuracy in assessing regulation capability of lithium-ion battery energy storage across multiple scenarios, suggesting a reliable tool for industry.
Key Points
This study aims to develop an intelligent assessment method for evaluating the regulation capability of lithium-ion battery energy storage systems across various scenarios.
Developed a multi-scenario assessment indicator system encompassing capability, economy, and safety.
Utilized the analytic hierarchy process and entropy weight method to establish indicator weights.
Modeled assessment as a Markov decision process and enhanced the DDQN algorithm with an attention mechanism.
Achieved high accuracy and efficiency in assessing multi-scenario regulation capability based on simulation analysis.
The proposed method improves decision-making accuracy and convergence speed compared to traditional approaches.