Researching On Modeling And Coordinative Optimization Of Distributed Integrated Energy Demand Response

The centralized charging behavior of electric vehicles and energy storage at low electric prices will generate new peak loads,exceeding the capacity transmission limit of the power system.Updating power equipment and load shedding are the main methods to solve the above problem.However,these methods will bring economic pressure to power grids and affect the comfort of end users.With the increasing application of distributed electric-gasheat conversion equipment,the study object of demand response has expanded from the single energy source to multi-energy sources,including electricity,heat and natural gas.The centralized gas consumption behavior will also lead to natural gas exceeding the transmission limit of pipelines.To solve the above problems,the comprehensive management of integrated energy system is proposed to achieve the coordination and complementarity of multi-energy,increase energy efficiency and reduce energy supply and energy costs.The research work in this paper is as follows:Aiming at the problem of coupling and interaction of multi-energy in the integrated energy system of smart buildings,an optimization model of multi-energy coordination in intelligent buildings is established.The objective function is to minimize the energy consumption cost of users in one day.The operation constraints of load equipment in integrated energy system are considered in the optimization model.The energy consumption behavior of each smart building participating in the integrated demand response alone is analyzed through simulation.The influence of multi-energy interaction behavior on power system and natural gas system is analyzed.A distributed demand response optimization is proposed to solve the problem of transformer overloading caused by the centralized charging behavior of electric vehicles and energy storage systems in demand response programs,considering the user's independent power consumption behavior.The lagrangian multipliers are introduced to solve the global constraints in the optimization problem.The centralized demand response problem is decomposed into regional autonomic distributed optimization problems.The distributed algorithm is used to solve the problem.Compared with the centralized optimization scheme,the distributed demand response could solve the problem of transformer overload,reduce the complexity of the communication system and ensure the information security and privacy of the end users.A distributed integrated energy demand response method is proposed to solve the problems of transformer overload and natural gas supply shortage caused by centralized electricity and gas consumption behavior when large-scale smart buildings participate in demand response.The Lagrangian multipliers are introduced to transform the centralized optimization problem into the distributed integrated energy demand response problem based on Lagrangian decomposition.The distributed algorithm is used to solve the problem.The effects of the energy consumption behavior of each smart building in the distributed integrated energy demand response on the natural gas and power system are analyzed through simulation.In summary,this paper focuses on the problem of large-scale integrated demand response considering the end-user interest and energy transfer constraints.A distributed demand response method based on Lagrangian decomposition is proposed,which can protect the privacy of end users,relieve communication pressure and achieve regional autonomy.