A multi-objective stochastic model enhances coordinated operation in hydro-wind-PV systems, suggesting effective renewable energy integration.
• A multi-objective stochastic operation model for HWPHS under uncertainties is developed. • A peak-shaving strategy considering load variations in the next period is proposed. • Interdependencies and trade-offs among multiple objectives in HWPHS are quantified. With the integration of uncertain power sources such as wind and PV into the power system, the multi-energy complementary operation mode centered on hydropower becomes more complex. Determining a reasonable multi-objective stochastic optimal operation strategy for the hydro-wind-PV hybrid system, and revealing the feedback relationships among objectives, is of great significance for promoting renewable energy integration and achieving coordinated operation among hydropower, wind, and PV power. This paper proposes a framework for multi-objective stochastic optimal operation and decision-making in a hydro-wind-PV multi-energy complementary system under uncertainty. An improved synchronous peak-shaving strategy is also introduced to solve the model. The framework has been applied to a case study in the upper reaches of the Yellow River in China. The results show that (1) The proposed model can effectively capture the trade-offs and synergies among multiple objectives in the hydro-wind-PV system and support rational decision-making. (2) The optimal decision scheme achieves a complementary power generation of 10,334.98 million kWh and a total output fluctuation of 1071.27 MW. (3) Compared to the average peak-shaving rate across multiple scenarios, the peak-shaving rate of the optimal scheme improves by 6.32%. Therefore, the proposed framework provides a promising approach for conflict coordination in hydro-wind-PV systems.
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Lei et al. (2026) studied this question.
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