An information gap decision theory-based decision-making model for complementary operation of hydro-wind-solar system considering wind and solar output uncertainties

Abstract

As large-scale wind and solar power sharing hydropower transmission channels are put into operation in river basins to lower investment costs in China, joint operations of hydro-wind-solar energy sources have become an effective operating strategy in power systems. However, wind and solar output with uncertainties and volatilities are problematic and pose challenges for power grid optimal scheduling, especially for peak shaving of grid system. In this paper, a novel decision-making model based on the information gap decision theory method is formulated to optimize the complementary operation of multi-energy systems. First, with the objective of minimizing the variance of the residual load, a deterministic short-term peak shaving model for a hydro-wind-solar system as a base case is established. Then, to model uncertainties of wind and solar output in the hybrid system and analyze the impact of grid peak shaving, the risk averse and opportunity seeker strategies of information gap decision theory-based technique are developed. Finally, as a proficient multi-objective optimization method, the normalized normal constraint method is exploited to solve the information gap decision theory-based bilevel optimal problem, and a set of Pareto solutions is obtained for the decision maker. A hydro-wind-solar hybrid system in Guizhou Province in China, with seven hydropower plants, a virtual wind power plant and a virtual solar power plant, is taken as an example to demonstrate the effectiveness of the proposed model. The results indicate that, by considering the uncertainties of wind and solar output, the presented model not only reduces the load fluctuations but also increases the flexibility response to the system against operational risk. In addition, the calculation time and load variance of the system are greatly reduced in comparison with stochastic programming.