Day-Ahead Scheduling for Renewable Energy Generation Systems considering Concentrating Solar Power Plants

Abstract

With the advent of the new types of electrical systems that attach more importance to the renewability of the energy resource, issues arising out of the randomness and volatility of the renewable energy resource, such as the safety, reliability, and economic operation of the underlying power generation system, are expected to be challenging. Generally speaking, the power generation company can do a reasonable dispatch of each unit according to weather forecast and load demand information. Focusing on concentrating solar power (CSP) plants (wind power, photovoltaic, battery energy storage, and thermal power plants), this paper proposes a day-ahead scheduling model for renewable energy generation systems. The model also considers demand response and related generator set constraints. The problem is described as a mixed-integer nonlinear programming (MINLP) problem, which can be solved by the CPLEX solver to obtain an optimal solution. At the same time, the paper compares and analyzes the impact of concentrating solar power plants on other renewable energy generation and thermal power operation systems. The results show that the renewable energy generation system can lower power generation costs, reduce load fluctuation, and enhance the energy storage rate.