@Article{jai.2026.075257,
AUTHOR = {Jiale Hu, Fan Chen, Yue Yang, Man Wang},
TITLE = {Optimized Energy Storage Dispatch Strategy Considering Reliability and Economy},
JOURNAL = {Journal on Artificial Intelligence},
VOLUME = {8},
YEAR = {2026},
NUMBER = {1},
PAGES = {51--64},
URL = {http://www.techscience.com/jai/v8n1/65601},
ISSN = {2579-003X},
ABSTRACT = {To enhance the operational performance of energy storage systems (ESS), this paper proposes an optimal dispatch strategy that jointly considers reliability and economic efficiency. First, we formulate a cost-minimization model that includes ESS dispatch costs, wind and photovoltaic (PV) curtailment costs, and load loss costs, while explicitly enforcing power supply reliability constraints. Next, we develop a comprehensive evaluation indicator system that integrates reliability, economic performance, renewable-energy utilization, and ESS technical indicators, thereby addressing the limitations of single-indicator assessments. Finally, a case study using real data from a region in China shows that the proposed strategy reduces the loss-of-load probability (LOLP) by 37.42%, halves the expected energy not supplied (EENS), and increases the system reliability indicator to 99.98%, with only a 0.014% increase in total cost. These results demonstrate the effectiveness and practical value of the proposed ESS dispatch optimization strategy.},
DOI = {10.32604/jai.2026.075257}
}