Optimal design and scheduling of carbon capture power plant based on uncertainty decision-making methods

Abstract

Post-combustion capture is one of the most mature carbon reduction technologies which plays an important role in pushing forward the process of "carbon neutrality". However, most previous efforts focused merely on the fixed operation of power plants and carbon capture devices, without taking into account the effects of fluctuating electricity prices and the subsequent variations in energy penalty of solvent regeneration process. As a result, the ability of carbon capture power plants (CCPP) to withstand fluctuations has deteriorated, leading to a decrease in robustness. In order to take advantage of the flexible operation characteristics of the power plant and the carbon capture device, the deterministic hourly electricity price and power load demand, as well as uncertainty of power load demand in future are considered in the study to determine the optimal network configuration and the flexible scheduling of carbon capture power plants based on decision-making theories. The uncertain parameters are presented by scenarios, and through MINLP-based optimization, the optimal system configuration under each scenario is obtained. Then these configurations are applied to other scenarios to obtain the scheduling and economic performance of the system. Five uncertainty decision-making theories (optimistic method, pessimistic method, optimistic coefficient method, equal probability method, minimum maximum regret value method) are adopted to select the most appropriate system scheme. Finally, a case study is investigated to demonstrate the proposed method, and the effectiveness and the feasibility are proved by the obtained results. Two network configurations with daily profit from $30,000 to $240,000 by scenarios are obtained and investigated. Results show that the turbine layout in the configuration chosen by optimistic method is radical, while by pessimistic criterion the turbine system shows margin in operation. Configuration selected by the equal possible value method and minimax regret method can achieve good economic performance operating in various scenarios. This research can help decision makers to make scientific decisions and reduce operating risks under uncertainties.