Scenario-Based Intraday Multi-Service Co-Optimization and Grid-Value Assessment of Renewable Power Plants with Co-Located Energy Storage

Renewable power plants with co-located battery energy storage systems (BESSs) coordinate forecast-deviation control, renewable-surplus management, electricity-price arbitrage, and ancillary-service commitments through the shared power and energy capability of the battery. This study develops a layered framework for scenario-based intraday multi-service co-optimization and grid-value assessment. The plant-level mixed-integer linear programming (MILP) model operates at 15 min resolution and represents piecewise deviation penalties, time-varying export limits, battery dynamics, a terminal state-of-charge condition, throughput-based degradation costs, and the opportunity cost of reserving regulation headroom. Its scenario-contingent formulation evaluates expected intraday operating value across ten representative photovoltaic trajectories under a perfect-information structure. A complementary service map assigns fast dynamic and system-level indicators to the control, power-flow, and dispatch models appropriate to their time scales. The numerical study considers an 80 MW photovoltaic plant with a 10 MW/20 MWh BESS, evaluates four regulation-compensation cases, and records a complete C4 run time of 209.421893 s on an Intel Core i7-10710U computer with 16 GB RAM. Energy-oriented service stacking increases expected daily plant benefit in the case study, while regulation reservation becomes attractive when compensation exceeds the opportunity cost of battery power and energy headroom. The framework provides a consistent basis for interpreting service interactions, decision timing, data provenance, and plant- and system-level value.