Energy Storage Systems (ESS) represent capital-intensive technologies set to play a pivotal role in the future energy landscape. In competitive markets, ESS rely heavily on cross-temporal energy arbitrage within day-ahead markets and across multiple segments, such as day-ahead to real-time markets. However, their revenue potential is heavily reliant on the accuracy of renewable energy generation forecasts, such as wind forecasts, which can influence market prices. This dependence can hinder the integration and development of ESS technologies. To address this challenge, this study presents a novel investment planning and participation strategy framework for ESS market engagement. The framework formulates the problem as a distributionally robust chance-constrained program, approximating it as a deterministic mixed-integer second-order cone program. To mitigate the impact of imperfect wind forecast uncertainties, we introduce two innovative block orders that facilitate ESS order clearing based solely on price spread, preserving convexity and computational efficiency. Numerical findings demonstrate the effectiveness of the proposed block orders in enabling energy arbitrage in the day-ahead and real-time markets in the presence of imperfect wind forecasts. The proposed model can identify the optimal investment and operational strategy, hedging system operators against wind power generation uncertainty while offering ESS investors a safety margin on the recovery of their investment. Read more here: https://doi.org/10.1016/j.est.2024.115197
