Research On Optimal Dispatch Of Active Distribution Network With Electric Vehicle And New Energy

The traditional distribution network optimization scheduling strategy only optimizes the scheduling with economic benefits as the single goal,which is di fficult to meet the new development needs.At the same time,it does not consider the interaction between source,network and load,and does not consider the response of demand side resources such as electric vehicles and energy storage devices.This puts a new test and broader development direction for the research of distribution network optimization dispatching with electric vehicles and new energy.It is in this context that the Active Distribution Network(ADN)was proposed.ADN is based on the real-time operating state of the power system,to ensure the stability and security of the system economy,using advanced information,communication and power electronics technology to distribute a large number of renewable energy,energy storage equipment,and controllable load.Energy-efficient distribution network with active management and autonomous coordinated control.In order to realize the mutual coordination and benign interaction between “source,network and load”,this paper proposes a multi-stage and multi-objective optimal scheduling strategy for active distribution network.The optimized scheduling strategy will respond to the orderly interaction of demand-side resources through distributed power supply such as wind power,photovoltaic power generation,and biogas power station,so as to achieve the synergistic development of economic benefits and environmental benefits.In the optimal dispatching strategy of active distribution network,this paper intends to simulate the disordered charging load of electric vehicles and the orderly charging load of electric vehicles under peak-to-valley time-of-use electricity price by Monte Carlo simulation method because of many factors affecting the charging load of electric vehicles.It can provide initial variables for the active distribution network optimization scheduling by using the uncertainty modeling method to establish the output model of wind power generation and photovoltaic power generation system.In order to coordinate the distributed power and demand side resources on the distribution network side more effectively,the active distribution network optimization scheduling strategy creatively introduces the electric user's response model to the peak-to-valley time-of-use electricity price.Considering the Pareto optimal frontier problem of the optimization model in the solution process,the fuzzy theory is used to fuzzify the optimization model,and the multi-objective optimization problem is transformed into the single-objective optimization with the greatest satisfaction of decision makers.Based on the fuzzy optimization model,the NSGA-? intelligent multi-objective optimization algorithm is used to obtain the Pareto frontier,and the simulation is carried out on the extended standard 33-node system.In order to verify the validity and accuracy of the proposed active distribution network optimal scheduling model,this paper sets up three different optimized scheduling scenarios for simulation analysis,and verifies that the rational us e of demand side resources and new energy network optimization scheduling can maximize the consumption.Renewable energy,smooth system load fluctuations,and meet the principles of power system economic dispatch.