| In order to achieve the dual carbon goals proposed in the 14 th Five-Year Plan,China has carried out the overall deployment of carbon peaking and carbon neutrality in key areas such as energy and petrochemicals.In China,coal is responsible for more than 40% of the power supply.Therefore,due to economic and energy needs,coal-fired power plant cannot be retired in advance and it has to undertake system peak shaving.Carbon Capture and Storage(CCS)technology could reduce carbon emissions while allowing coal-fired power plants to continue to operate.At present,most of the researches on the simultaneous schedule of power plants and carbon capture devices are assumed to be under fixed loads,but in practical applications,the power demand is often fluctuating or even uncertain.At the same time,the high energy consumption characteristics of carbon capture devices require them to perform peak-staggered capture to meet the power supply during high demand periods.Therefore,considering the influence of uncertain factors on the system in the design process,making the system capable of flexible dispatch is the key to building a low-carbon energy system.In response to the above problems,this paper carried out the following research:(1)In order to realize the real-time flexible scheduling of the power plant and the carbon capture integrated system,this paper proposes a simultaneous integration model of the power plant and carbon capture.The model redesigns the turbine configuration inside the power plant and the flexible operation mode of the carbon capture device respectively,and explores the coupling integration structure and dispatching schedule.On the one hand,the model explores the coupling relationship between the steam power cycle system and the carbon capture device in the power plant.On the other hand,the model decouples the interior of the carbon capture device and between the capture device and the power plant by adding two flexible operating mechanisms,solvent storage tank and flue gas bypass,to achieve dispatched operation.In this study,a mixed integer nonlinear programming(MINLP)model is established to optimize and solve the system structure and scheduling scheme that can achieve the maximum daily profit.Compared with the model that does not consider the rational configuration of the steam power cycle system and its coupling relationship with the carbon capture device,the daily profit of the integrated model has increased by 33.2%.Among them,the electricity market revenue of power plants has increased significantly,indicating that the proposed method can effectively improve the economy of the system.(2)Based on the coupled system model established in Chapter 2,this paper considers further utilizing the waste heat of the flue gas from the power plant to offset the heat consumption inside the system,especially the carbon capture device.The improvement is aimed at improving energy efficiency and reducing carbon emissions.In this study,waste heat was recovered by direct heat exchange and organic Rankine cycle for boiler feedwater preheating or desorption tower reboiler,respectively.The application and scheduling of these recycling technologies are closely related to the configuration and scheduling scheme of the background system,so a mathematical programming model is established to optimize the entire system.Finally,the dispatching scheme of the steam turbine structure,carbon capture and waste heat recovery system of the power plant is obtained.Based on the optimization results,the research analyzes the relationship between different flue gas waste heat utilization approaches and carbon capture scheduling from the perspectives of economy and thermodynamic exergy.(3)Carbon capture power plants are often affected by a variety of uncertain factors in the actual operation,and these effects should be considered in the optimization process of the system structure and dispatch scheme to ensure that the system has sufficient robustness.On the basis of the first two parts,this part introduces two methods: uncertainty decision theory and information gap decision theory,and establishes a model that fully considers the influence of uncertain factors by adding descriptions of uncertain parameters.Uncertainty optimization aims to reveal the influence of uncertain parameters on system configuration and operation.Uncertainty optimization is performed on the same case by applying the above method.Among them,the uncertainty decision theory shows that the maximum daily profit of the two system structure schemes under 6 scenarios ranges from 40,000 $ to 240,000 $,and different decision theories will give the optimal scheme according to the decision value.Under different economic goals,the corresponding uncertainty can be obtained by using the information gap decision theory,and the decision under different risk preferences can be given.Therefore,the research on optimization and scheduling of uncertain systems can provide guidance for actual industrial production. |
