Energy Storage Configuration Method for Industrial Parks Considering Profit Maximization

With the implementation of demand response (DR) policies, consumers have gained the ability to participate in the electricity ancillary services market, using load shifting to reduce electricity costs and even generate profits. This has further driven the widespread adoption of energy storage systems (ESS) in power systems. This paper analyzes the optimal configuration of energy storage for an industrial park in Jiangsu Province, considering factors such as ESS construction and maintenance costs, peak and off-peak electricity prices, and revenue from DR participation. The Monte Carlo (MC) method is used to account for uncertainties in photovoltaic (PV) generation and user load, with backward scenario reduction to generate representative scenarios. By utilizing energy storage, the park can engage in peak-valley arbitrage and participate in DR, achieving cost recovery within a reasonable timeframe.