Dynamic-Depreciation-Aware Bi-Level Capacity Optimization of Shared Energy Storage for Renewable Energy Bases Considering Multi-Service Operation

Shared energy storage (SES) in renewable energy bases can integrate reliability support, curtailed-energy accommodation, spot-market arbitrage, and frequency-regulation services, but unclear service boundaries and static depreciation may distort capacity-allocation and economic-evaluation results. This paper proposes a bi-level capacity optimization model that incorporates operational intensity and dynamic depreciation. The model defines service-occupation boundaries and cycle-attribution rules, uses annual equivalent cycles to quantify cycling intensity, and feeds this intensity back into economic lifetime and capacity-side depreciation, forming a closed loop of capacity configuration, operational dispatch, lifetime assessment, and cost correction. A seasonal representative-day case study shows that static depreciation overestimates annualized net income by 7.55% under the same configuration. The dynamic-depreciation closed loop corrects the evaluation of high-cycling schemes and identifies leasing-based reliability support, passive curtailed-energy accommodation, and spot-market arbitrage as the preferred scheme under the benchmark conditions. Passive accommodation reduces annual curtailed energy by 54.90% and increases annualized net income by 41.40%. The proposed method provides a quantitative basis for capacity configuration and multi-service operation of shared energy storage in renewable energy bases.