Investment Valuation of Grid-Side Independent Energy Storage Stations Under Uncertainty: An Integrated MILP and Real Options Approach

The deployment of grid-side independent energy storage stations (IESSs) is critical for managing the volatility introduced by high renewable energy penetration. However, investment in IESSs faces significant uncertainties, including fluctuating spot prices, policy changes, and equipment degradation, which traditional static valuation methods fail to address adequately. To bridge the gap between operational optimization and investment decision-making, this study proposes a novel framework integrating a mixed-integer linear programming (MILP) operational optimization model with the Black-Scholes-Merton Model (BSM). The MILP model explicitly incorporates capacity degradation, multi-market revenue structures and comprehensive cost expenditures. The BSM, with volatility estimated via Monte Carlo simulation, quantifies the value of delaying investment under different policy scenarios. Results indicate that capacity price subsidies provide superior early-stage cash flow relief compared to tax incentives, and their combination yields a synergistic effect, increasing the maximum tolerable electricity price decline rate from 4.08% to 8.88%. Furthermore, in pessimistic scenarios, the real options approach identifies positive returns (up to 8.02 million CNY) from delayed investment, whereas the net present value method would suggest immediate rejection. Sensitivity analysis reveals that construction cost and frequency control mileage are the most influential factors. This framework offers a robust quantitative tool for IESS investment timing and regional policy design.