Day-Ahead Market Trading Model of Pumped-Hydro-Solar Hybrid System Considering Contract Decomposition

Abstract

The pumped-hydro-solar hybrid system is a comprehensive power generation system in which cascade hydropower and pumped storage units with strong regulation capabilities are set to stabilize the randomness and volatility of photovoltaic output. The optimization of the trading strategy of pumped-hydro-solar hybrid system in the day-ahead market considering decomposition of the contract market's daily electricity was studied in this paper. It's assumed that the contract power is decomposed into a daily contract curve, and a certain percentage of the excess and shortfall of the contract power is allowed, and the power over the contract is traded in the day-ahead market. The highest total market revenue was set as the optimization goal of the model. stochastic programming was used to obtain typical scenarios of photovoltaic output, and the randomness of electricity prices was handled through robust optimization. By linearization method and duality theory, the optimization model was transformed into a mixed integer programming model. Through the analysis of case study, the method proposed in this paper is proved to take both economy and robustness into account.