Research On Modeling And Optimization Of Distributed Energy Network Based On Energy Hub

In order to achieve the goal of carbon neutrality by 2060,China pays more attention to the efficient utilization of clean energy.With the in-depth development of Energy Internet,the large-scale development and application of distributed energy supply network have injected new vitality into energy industry and made great contributions to emission reduction and green development.However,the distributed energy network has a large volume and variable coupling characteristics.The coordinated operation of multiple energy stations increases the difficulty of its design and planning,and its optimization problem is crucial to the improvement of overall performance.Therefore,based on the concept of energy hubs,this paper proposes a multi-objective collaborative optimization model for optimal capacity configuration and operation scheduling of distributed energy networks for regional heat and power sharing to improve the overall energy,economic and environmental performance of distributed energy network.Firstly,according to the local renewable resources and user loads,this paper initially determines the system integration scheme of the regional distributed energy network,and establishes the dynamic energy hub model of the system energy flow to describe the multi-energy coupling relationship within the system.And for the system integration scheme,a dynamic output model of equipment components is established.It also describes the operation strategy of heat and power sharing between regions of the distributed energy network with complementary multi-energy stations,as well as the operation strategy of heat determined by power in the distributed energy system with complementary multi-energy.Secondly,the method of establishing the collaborative optimization model is introduced,and the effectiveness of the model is verified through three operating modes set by examples.The results show that collaborative optimization can effectively improve the comprehensive performance of energy supply network through capacity allocation optimization and energy scheduling management.Compared with independent optimization,collaborative optimization increases the primary energy saving rate of the distributed energy network by 5.3%,the total annual cost saving rate by 5.1%,and the carbon dioxide emission reduction rate by1.1%.The energy utilization form of heat and power sharing has reduced the waste heat and excess electricity by 16.5% and 1.1% respectively,and the structure of energy production and energy consumption is more scientific and reasonable.Collaborative optimization has increased the installed capacity of renewable energy technologies by 19.7%,which is conducive to the consumption of renewable resources.In addition,collaborative optimization not only improves the power generation efficiency of the equipment,but also improves the utilization rate of the system equipment.Finally,for the supply and demand network composed of energy station systems and regional users,with the help of the multi-objective collaborative optimization model in the first stage and the multi master and multi follower game optimization model in the second stage,the objective function formed by the energy price on the energy supply side of the energy station and the load demand on the user load side is calculated by game theory.The game optimization result improves the overall objective function value and increases the user’s energy satisfaction degree.The energy station can obtain stable profit and integrate the system scheme of optimal capacity allocation and output scheduling.