Optimization of Unit Commitment with Large-Scale Energy Storage to Minimize Solar PV Curtailment

This paper presents a mixed-integer linear programming (MILP) based optimization model for unit commitment (UC) and optimal power flow (OPF). We consider a small 5-bus test power system integrated with solar photovoltaic and energy storage and demonstrate that storage reduces PV curtailment, lowers operation cost, and maintains network feasibility. Sensitivity analyses are conducted on storage capacity, PV priority weighting, and line congestion limits. Results show solar penetration has the most significant impact on cost reduction. Increasing PV availability notably decreases operational costs, demonstrating the system’s economic benefit from renewable integration. However, beyond a certain penetration level, the marginal benefit diminishes due to curtailment indicating the importance of energy storage integration. Expanding storage from 100 to 300 MWh significantly reduces costs during high-photovoltaic scenarios by allowing excess mid-day solar to charge batteries, which is later discharging during evening peaks. This time-shifting of energy mitigates the reliance on expensive peaking generators and smooths net load profiles, but the effect plateaus as storage saturation occurs.