Research On Intelligent Community Optimization Scheduling Strategy With Multiple Demand Side Resources

As an important part of the smart grid,the intelligent community is an important carrier for the interaction between residential users and the power grid.Resident-side response resources have the characteristics of fast response,spatial dispersion,small single-unit response,but large cluster response potential.Participating in grid operation after intelligent community aggregation will greatly improve responsiveness.In addition,the demand side resources can be allocated through the energy management system within the community to improve the overall operational efficiency of the community.Therefore,this dissertation focuses on the positioning of intelligent communities,aggregates the demand side resources,and studies the optimal scheduling strategy of participating in power grid clipping and community energy management.Firstly,the load characteristics of demand side resources in intelligent community are studied in depth,including air-conditioning load and electric vehicles in residents' controllable loads,as well as photovoltaic and energy storage devices in distributed power sources.Their load models are established,which lays the foundation for load regulation methods.Secondly,the control method of demand side resources is studied,and the response potential is evaluated on this basis.Based on the load polymerization technology,the approximate load model of the aggregated air conditioner is established.In the traditional temperature regulation method,the start-stop control,the approximate evaluation of the aggregate power and the comprehensive sorting of the air conditioner are combined,and a control method suitable for large-scale residential air-conditioning temperature regulation is proposed.The simulation results show that the method can effectively avoid the load fluctuation problem after temperature adjustment.The potential of the polymerization air conditioner is divided into short-term response potential and long-term response potential.The characteristics of the two types of response potential are analyzed.The charging load prediction model of the disordered charging of the electric vehicle is established,and the charging load transfer potential of the electric vehicle is evaluated.Then,based on the potential evaluation,a peaking regulation strategy suitable for intelligent communities is proposed.The organization structure and process of the demand side resources participating in peak clipping are sorted out,and the priority of each response resource participating in peak clipping is sorted according to the influence of the power consumption comfort level.To improve the flexibility of peak clipping,the aggregated air conditioning is grouped and regulated.Based on the evaluation of various resource response potentials during peak clipping period,the intelligent peak clipping optimization model is established with the minimum peak clipping deviation as the goal,and the household users and the community operators are rationally allocated.The peak compensation and the simulation of the example verify that the strategy can reasonably arrange various resources to reduce power and effectively execute the peak clipping command of the power grid.Finally,an intelligent community energy management strategy that takes into account multiple demand side resources is proposed.The scheduling methods of various resources participating in energy management are analyzed.With the goal of minimizing the power consumption cost and load fluctuation of the community,a pre-energy optimization management model considering the PV prediction bias is established.The schedulable potential of response resources in each period is considered in the constraints of the model.The energy management strategy without energy management and without considering PV prediction bias and the strategy proposed in this dissertation are compared and analyzed.The results show that the proposed strategy can not only rationally allocate the output of each response resource,but also improve the economy and reliability of the community.