Expansion Planning And Robust Scheduling For Integrated Energy System Considering Source-network-load Uncertainty

The key issue that the current development of the energy society faces is how to improve energy efficiency and promote clean energy.Integrated Energy System(IES)has attracted widespread attention because of its higher energy supply efficiency and more flexible operation style.The integrated energy system realizes the deep coupling between multiple energy sources such as electricity,gas,and heat.Through the coordinated operation of multiple energy sources,it improves the acceptance of renewable energy sources,i.e.,wind power.Therefore,the integrated energy system will surely become one of the mainstream ways of energy supply in the future.However,the complexity of the deep coupling between multiple energy sources and the multiple uncertainties at the source-network-load sides,result that the planning and operation scheduling of the integrated energy system face many difficulties and challenges.First,for typical uncertainties such as wind power,the probability distribution is difficult to obtain accurately,and its computational efficiency is low.On the load side,there are also many errors in the prediction of terminal load growth.How to accurately grasp the characteristics of wind power and load forecast deviation,is the basis for ensuring the safe and efficient operation of the system.Secondly,in terms of network-side uncertainty,the existing literature only considers uncertainties on the grid side such as random failures of transmission and transformation equipment,while ignoring the uncertainties in the heating pipeline.How to effectively deal with the double uncertainty of wind power and heating pipe network,to ensure the quality and safe operation of the heating network,is also a problem that has not been solved in the joint scheduling research of the integrated electric-heating system.In addition,due to the random volatility of wind power,the complexity of the current rolling scheduling model has further increased.Therefore it is difficult to meet the requirements of online applications.How to realize the online tracking of the optimal scheduling strategy of the integrated electric-heating systems according to the changes of external parameters such as wind power and load is an urgent problem to be solved.In terms of the above problems,the main work of this thesis is as follows:(1)For the stochastic volatility of wind power and the forecast deviation of load,a scenario analysis method based on AP clustering is proposed,to obtain a set of clustered and representative wind power and load scenarios.This method is applied in the expansion planning of the combined electric-gas system.A multi-stage expansion planning model considering sourceload uncertainty is established,which not only considers long-term joint planning of combined electric-gas system,but also takes into account short-term economic operation constraints and N-1 reliability.A fault screening method based on line outage distribution factors is proposed to improve the reliability of the system.An iterative Benders decomposition method is proposed to decompose the original problem into a main problem and three sub-problems.Finally,an economical,reliable,and feasible gas supply optimal planning scheme is obtained.The case studies verify the feasibility of the proposed model and the effectiveness of the method.(2)The uncertainty of pipeline parameters may affect the operation quality or even the safety of the integrated electric-heating system.In order to deal with this problem,this thesis proposes a two-stage robust electric-heating joint dispatching model considering the uncertainty of heat load,ambient temperature and heat dissipation coefficient.The model with bilinear terms is equivalently converted into an adaptive linear robust optimization problem by the big M method,and the column and constraint generation(C&CG)algorithm is used to solve it.Simulation results show that the method can effectively deal with the uncertainty in the district heating network,improve the robustness of the integrated electric-heating system,and ensure the safe operation of the system.(3)The rolling scheduling model of the integrated electric-heating system has a large amount of calculation and a low solution efficiency,which cannot meet the requirements of online applications.An online rolling robust scheduling method for an integrated electric-heating system based on multi-parameter programming is proposed.Through the dual transformation and reconstruction,the second-stage subproblem in the online rolling robust scheduling model is transformed into a multi-parameter linear programming embedded with external parameters.The analytical function and corresponding mathematical critical region of the worst operating state of the integrated electric-heating system with external parameters are derived.The results of case studies show that the proposed method can reduce the number of iterations of the C&CG algorithm and the calculation amount of the rolling cycle,which provides the possibility to further shorten the time granularity of the rolling scheduling plan and increase the frequency of rolling correction of the generation plan.