Optimization of power dispatching strategies integrating management attitudes with low carbon factors

Abstract With the rapid development of low-carbon electricity, wind power and carbon prices serving as low carbon factors have drawn significant attention. Owing to the wind power uncertainties, the carbon price fluctuations and the immeasurability of management attitudes towards these two factors, the traditional dynamic economic emission dispatch (DEED) models are no longer completely practicable for low-carbon power dispatching problem. Aiming at these difficulties, this paper establishes a stochastic DEED model concentrating on low carbon factors. After discussing the wind power’s statistical characteristics, a scenario-based deterministic form for the proposed model is set up. Furthermore, a sequence of nondominated sorting genetic algorithm-II (NSGA-II) program steps with constraints-handling techniques is designed to solve this model, and an auxiliary decision-making method is developed for the selection of optimal power dispatching strategies. According to carbon prices, wind power uncertainties and satisfaction degrees, the optimal power dispatching strategies integrating management attitudes with low carbon factors could be achieved through the proposed model and method. The simulation results finally prove that carbon emissions could be controlled by carbon trading without significantly increasing generation costs, and carbon trading will further contribute to improvement of energy efficiency.