Evaluation of Power System Adaptability Considering Planned Future Wind Farms and Photovoltaic Stations

With the increasing integration of wind and solar energy, power systems face growing challenges in supply–demand balancing, renewable energy accommodation, and reserve regulation, especially in future power systems with evolving generation mixes. To this end, a system adaptability evaluation method particularly considering planned future wind farms and photovoltaic (PV) stations is proposed. Available historical meteorological data are converted into wind and PV power output sequences through renewable power conversion models. Then, a generative adversarial network (GAN)-based model is built to learn the temporal fluctuation characteristics and inter-station correlations of renewable generation, thereby generating multiple representative wind and PV output scenarios. Finally, these scenarios are embedded into a security-constrained unit commitment (SCUC)-based model to evaluate system adaptability in terms of load shedding, renewable energy curtailment, accommodation rate, and reserve margin. The proposed method provides a forward-looking framework for assessing the operational adaptability of power systems under high renewable energy penetration.