Research On Distributed Robust Optimization Scheduling Of Integrated Energy System

At present,global energy transformation is in the period of accelerating promotion,and promoting renewable energy development is an important way to promote energy transformation and upgrading.Integrated energy system has been widely used in the energy field because of its advantages of energy gradient utilization and multi-energy coupling and complementation.However,with the continuous growth of renewable energy access scale and various loads,the source and load uncertainty within the integrated energy system keeps increasing,which affects the safe and stable operation of the system.At the same time,the day-ahead scheduling plan cannot guarantee the economic and reliable operation of the system during the day due to the lack of dayahead prediction accuracy and intra-day system disturbance.To address the above problems,this paper proposes a multi-time scale distributionally robust rolling optimal scheduling method of the integrated energy system,which can effectively cope with the effects of multi-timescale uncertainties and improve the robustness and economy of system operation.The main research tasks and conclusions of the paper are as follows:(1)Analyze the operating characteristics of each unit of the integrated energy system,in order to improve energy conversion and utilization efficiency,establish the basic structure and corresponding mathematical model of the integrated energy system in this paper.(2)In the day-ahead optimal scheduling stage of the integrated energy system,this paper establishes the integrated energy system distributionally robust optimization scheduling model based on the imprecise Dirichlet model,which improves the operational stability and economy of the system under the source and load uncertainty conditions.On this basis,considering the periodicity of the operating scenario and the correlation characteristics of multivariate variables,the scenario analysis and Cholesky decomposition method are used to obtain the sample matrix with independengt variables of the scheduling scenario.Then,this paper establishs the integrated energy system distributionally robust day-ahead optimal scheduling model taking into account the integrated demand response,and uses the strong duality theory and C&CG method to complete the model transformation and solution,and thus obtains the day-ahead optimal scheduling plan.(3)In the intra-day optimal scheduling stage of the integrated energy system,this paper adopts a model predictive control method and establishes an intra-day rolling optimization model to improve the reliability and traceability of the intra-day dispatching schedule.The model aims at minimizing the amount of day-ahead schedule adjustment,and adjusts the day-ahead scheduling plan in a timely manner according to the actual intra-day operation of the system.(4)Through simulation and comparison analysis,the effectiveness of the multitime scale integrated energy system distributionally robust rolling optimal scheduling scheme proposed in this paper is verified.Under the conditions of multi-timescale uncertainty,the resulting day-ahead scheduling plan balances the robustness and economy of system operation,while the intra-day scheduling plan can ensure safe and stable intra-day operation of the system,and at the same time,it has good tracking performance for the day-ahead scheduling plan.