Low-carbon Optimal Scheduling Of Integrated Energy System Considering Multiple Uncertainties

With the rapid changes in the global energy structure,wind power and photovoltaic renewable energy have gradually become one of the main forms of power generation.Improving energy utilization and increasing the proportion of renewable energy consumption are important measures to promote the "peak carbon dioxide emissions and carbon neutrality" strategy.In the face of increasingly diverse electricity consumption,quickly constructing an Integrated Energy System(IES)to comprehensively promote energy production,energy conversion,energy storage,and energy consumption for unified low-carbon optimal scheduling is an effective way to achieve large-scale renewable energy consumption and efficient energy utilization.Therefore,integrated energy systems are crucial in building a modern energy architecture that is "clean,safe,efficient,and low-carbon.".However,IES is faced with multiple uncertainties of renewable energy on the power supply side and flexible loads on the load side,which can strongly interfere with the supply and demand balance of the system,leading to a decline in the economy of IES,a reduction in the consumption rate of renewable energy,and a sharp increase in carbon emissions indicators.In response to the above issues,this thesis takes IES as the main research subject,and conducts research from the perspective of IES optimal scheduling considering source load uncertainties.At the same time,carbon trading is considered to reduce system carbon emissions,thereby achieving energy supply and demand balance in IES,improving system economy and carbon emission reduction.The innovative research carried out in this thesis are as follows:Firstly,starting with the uncertainty model and coupling equipment model of the integrated energy system,the probability models of IES wind power and photovoltaic power generation units are established,and the characteristics of each coupling equipment in the IES system are analyzed in detail.At the same time,the schemes for carbon trading to achieve carbon emission reduction are analyzed,and the practical role of each link in the system is verified through theory.Secondly,based on considering the uncertainty of both source and load terminals,a lowcarbon optimal scheduling model for integrated energy systems is established.Probability modeling is performed on the power supply side,and electrical thermal integrated demand response modeling is performed on the load side.IES uses power grids,gas turbines,and energy storage to set up rotating reserves to mitigate the uncertainty of renewable energy output.It uses sequence operation theory to convert opportunity constraints into deterministic constraints,thereby transforming the established model into a mixed integer linear programming model,which is solved using a Cplex solver.The results show that the constructed IES scheduling model balances the energy demand of the system by coordinating flexible demand response,uncertainty of energy storage equipment,and renewable energy,improving the economy of the system,and reducing the carbon emissions of the system.Finally,by introducing power to gas(P2G)and carbon capture and storage(CCS)equipment into the integrated energy system,a low-carbon optimal scheduling model for the integrated energy system considering P2G and CCS is established.The coupling characteristics of cogeneration(CHP),P2G,and CCS are analyzed.A mixed integer quadratic constraint programming model is established using Yalmip,and solved using Ipopt.Comparative analysis of the optimal scheduling results of CHP,P2G,and CCS coupling and considering only CHP shows that the introduction of electricity to gas and carbon capture equipment can improve renewable energy consumption in IES,reduce operating costs,and reduce carbon emissions.