A TSP-CVaR Model for Day-ahead Schedule Optimization of Wind-PV-Hydro Hybrid Power System under Uncertainties

Based on TSP-CVaR risk aversion theory, this paper proposes an optimal dispatching model for wind-PV-hydro hybrid power system with complementarity characteristics. Under the framework of two-stage programming (TSP), the proposed method could effectively deal with the volatility of demand, the randomness of upstream traffic, and the complex connection of hydraulic resource in cascade hydropower station. Besides, conditional value at risk (CVaR) is introduced to characterize the risk aversion attitude of decision makers (DMs), and take full account of the minimum acceptable profit under certain confidence level. Finally, the feasibility and effectiveness of the proposed method is verified through a case study. The influence of the risk aversion attitude of DMs on the scheduling and operation plan of the multi-energy complementary power generation system is also analyzed and discussed.