Adaptive stochastic scheduling of cascade hydropower-photovoltaic power hybrid systems under climate change

Na Lu, Xiaoyue Peng, Chengguo Su, Guangyan Wang and Quan Sui

Energy, 2025, vol. 319, issue C

Abstract: The joint operation of cascade hydropower plants with flexible adjustment capacity and photovoltaic power is a reliable and realistic choice for dealing with the problems caused by the high penetration rate of photovoltaic power. However, the power generation capacity of these renewable energy sources will be affected by climate change. Insufficient consideration has been given to the impact by climate change on supply and demand in the hybrid energy systems. Hence an optimization model for the scheduling of CHPV hybrid energy systems is developed to adapt to climate change in this paper. Firstly, the large-scale hydrometeorological data of various Global Climate Models (GCMs) are downscaled, and the combination of GCMs with the best performance of hydrometeorological data in the research area is determined by applying the Taylor Chart method. Secondly, the Latin hypercube sampling and K-means clustering method are used to deal with the uncertainty of the optimal GCM combination data after downscaling. Thirdly, the chance constrained programming based stochastic scheduling model for the CHPV hybrid energy systems is established. Finally, the original model is transformed into a standard MILP model and solved by CPLEX optimization solver. The case study shows that under climate change, CMCC-CM2-SR5&SSP5-8.5, MIROC6&SSP2-4.5 and NorESM2-LM&SSP5-8.5 is suitable to project the monthly mean streamflow, temperature and solar radiation in the future periods, respectively, in Beipan River basin. The power supply guarantee rate of the CHPV hybrid system during the scheduling periods is 75.83 %, and the annual power generation is 4520 GWh. Compared with the individual hydropower operation, the power supply guarantee rate of the hybrid energy system is increased by 13.53 %. It can be concluded that the stochastic scheduling strategy of the CHPV hybrid systems can more effectively hedge the impact of future climate change on power generation scheduling.

Keywords: Climate change; CHPV power hybrid systems; GCM; Hydrometeorological information uncertainties; Adaptive stochastic scheduling; Chance constraint programming (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:319:y:2025:i:c:s0360544225006073

DOI: 10.1016/j.energy.2025.134965

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