An integrated optimization framework unlocks energy storage economic value in renewable energy bases through planning operation coordination

This paper proposes an integrated hierarchical coordination framework for planning and operations to address the decoupling between long-term capacity planning and short-term operational scheduling in renewable energy systems and the resulting economic and reliability losses. The core innovation lies in its “planning-operation” closed-loop feedback system. The upper-level planning adopts the non-dominated sorting genetic algorithm III (NSGA-III) to optimize the capacity mix of wind, solar, and energy storage, balancing investment economy and system reliability. The lower-level operation introduces an adaptive distributed model predictive control (DMPC) strategy empowered by deep deterministic policy gradient (DDPG), enabling efficient response to real-time uncertainty. Through a multi-stage elite feedback mechanism, high-fidelity annual performance indicators from the lower-level operation directly guide the iterative optimization of upper-level planning. Simulation results on the modified IEEE 30-bus system show that the closed-loop coordination mechanism guides planning to configure Energy Storage Systems with higher energy-to-power ratios (3.0 h vs. 1.5 h in conventional methods), fundamentally transforming energy storage from a “power buffer” into an efficient “energy time-shifter.” This planning-driven structural optimization reduces the average daily operating cost by 24.6% compared with traditional decoupled methods and decreases the annual comprehensive curtailment rate from 9.9% to 3.4%. Importantly, the framework quantifies the pure gains of planning-operation integration: even compared with decoupled schemes using the same advanced scheduling, the integrated framework further lowers operating cost by 20.4%. Furthermore, when benchmarked against state-of-the-art integrated methods such as two-stage stochastic programming and end-to-end deep reinforcement learning, the proposed framework demonstrates superior performance by reducing daily operating costs by 13.9% and 15.7% respectively, while ensuring system safety and constraint satisfaction. When facing high-frequency stochastic disturbances, the maximum system frequency deviation is strictly controlled within ± 0.05 Hz. This study shows that the proposed closed-loop coordination is a core mechanism for unlocking the potential of advanced control strategies and shifting the economic role of flexibility resources, providing an effective and robust paradigm for the full-life-cycle optimization of large-scale renewable energy.