Reserve Planning Method for a Renewable-Energy-Dominated Power System Considering Reserve Availability

Traditional reserve planning methods often suffer when balancing system economics and reliability due to the uncertainty and transmission constraints of renewable energy sources (RESs) being neglected, affecting the availability of reserves. To overcome these challenges, in this study, we propose a new reserve planning method tailored to a renewable-energy-dominated power system, with particular consideration of reserve availability. First, the method assesses reserve availability using a unified reliability economics model at the composite system assessment (CSA) level; it also employs a conditional cost–benefit analysis (CCBA) to optimize the reliability–cost trade-off. To solve the planning problem, a particle swarm optimization (PSO)-based hierarchical optimization method is employed to co-optimize the allocation of reserve capacity, thus maximizing the comprehensive benefit. Furthermore, the analysis quantifies the impact of the RES penetration level and risk preference on the reserve capacity and its allocation. The results of tests conducted on IEEE RTS-79 demonstrate that the proposed method can effectively assess reserve availability, as well as achieve an increase of up to 19.5% in comprehensive benefit and a 73.8% reduction in EENS. Furthermore, increasing RES penetration and ensuring stronger risk preference can lead to reserve capacity increases of 42.4% and 76.0%, respectively.