Optimized energy storage configuration for enhanced flexibility in renewable-integrated power systems

The increasing penetration of renewable energy sources in power grids has intensified the need for enhanced system flexibility to manage supply-demand imbalances. This study proposes a novel two-layer optimization framework for energy storage configuration, integrating two original indicators: the Flexibility Demand Matching Coefficient Index (FDMCI) and the Comprehensive Evaluation Index of Node Importance (CEINI). The upper layer determines optimal storage placement and capacity based on CEINI, which incorporates power flow impact, nodal betweenness, and proximity centrality. The lower layer applies Conditional Value at Risk (CVaR) to evaluate flexibility risk and employs FDMCI as a constraint to ensure supply-demand matching. The optimization is solved using the Yamip/CPLEX solver. Simulation results on modified IEEE 30-node and 118-node systems validate the effectiveness of the approach. The proposed method reduces total operational costs by 3.3 % (from $588,274.31 to $569,140.60), decreases average voltage deviation from 0.0317 to 0.0138, and maintains a high flexibility index of 0.986. Additionally, it enables a 1.4x increase in renewable capacity while minimizing curtailment and thermal dependency. These results demonstrate that the proposed framework offers a practical and scalable solution for flexibility enhancement and low-carbon dispatch in renewable-rich power systems.