Optimal Scheduling of CSP-PHES Integrated Systems Under Wind-PV Uncertainty

With the continuous increase in renewable energy installed capacity in modern power systems, the stochastic variability of wind and photovoltaic (PV) power and their accommodation challenges pose significant difficulties for operational dispatch. The uncertainty of renewable energy can be effectively mitigated using Latin Hypercube Sampling (LHS) and K-means clustering methods. To address renewable energy accommodation issues, this paper integrates Concentrated Solar Power (CSP) and Pumped Hydro Energy Storage (PHES) to improve the renewable energy accommodation rate. Finally, a CSP-PHES model is established to investigate potential interactions between the integrated CSP and PHES systems, with the objective of minimizing total operational costs to derive a day-ahead scheduling plan. Results demonstrate that the proposed strategy effectively enhances the renewable energy accommodation rate while mitigating wind and PV uncertainty. Additionally, under the influence of PHES, the output duration of CSP units is extended. The integrated CSP-PHES system reduces the output pressure on thermal power units, lowers flexibility requirements for conventional coal-fired generators, improves economic efficiency, and validates the effectiveness of the strategy.