Combined dispatching of hydropower and wind power based on the hedging theory

Abstract

In order to improve the utilization rate of water resources in the flood season of the reservoir effectively and promote wind power consumption, this paper proposes an optimization model for the combined dispatching of wind power and hydropower based on the hedging theory. First, the conflicting relationship between the water storage benefits of hydropower stations, flood control risks, and the joint output of hydropower and wind power in joint dispatching is studied. The introduction of hedging theory divides the combined dispatching of wind power and hydropower into a twostage dispatching problem including the decision-making stage and the remaining stage; Second, considering the uncertainty of water forecasting and wind power forecasting, a multi-objective optimal dispatching model of hydropower and wind power based on hedging theory is constructed. This model aims to minimize flood control risks, maximize water storage benefits, and minimize wind power and hydropower combined power output volatility. Finally, the non-dominated sorting genetic algorithm (NSGA2) is used to solve the specific examples. The results show that the model built in the article controls the flood control risk at each time period not to be higher than 1.63 × 10−3 (the flood control standard corresponding to the flood control risk in 50 years is 0.006). Additionally, the water level of the reservoir increased from the flood limit water level (583.00 m) to 583.70 m. It greatly increases the water storage capacity and effectively improves the utilization rate of water resources. At the same time, the optimized scheduling scheme reduced the peak-valley difference of joint output from 125.00 MW to 35.66 MW, and the peak-valley difference was greatly reduced. It effectively improves the volatility of wind power. The validity of the model is verified, and the obtained scheme can provide decision-making for the joint dispatch scheme of hydropower and wind power.