Reactive Power Coordination Optimization Of Distribution Network In New Energy Environment

In order to alleviate the energy crisis and cope with climate change,the large-scale application of new energy has become a trend.However,the access to the grid,such as distributed generation and electric vehicle,can have a large impact on the grid,especially for distribution network that is directly connected to distributed generation and electric vehicle.The essence of reactive power optimization problem in distribution network is an optimal power flow problem,that is,based on the power flow equation,the evaluation indicators such as economy,safety and stability of the system are optimized,under the known structural parameters of the distribution network system and the constraints of the variables to be optimized.Reasonable reactive power distribution can not only effectively reduce the network loss of the distribution network,but also improve the voltage quality of the distribution network,thus effectively ensuring the economic operation,safety and stability of the distribution network.This paper focuses on the problem of reactive power coordination optimization in distribution network under the new energy environment.The main work is summarized as follows:(1)This paper studies the problem of reactive power coordination optimization in "source-network-load" distribution network,considering the stochastic model of distributed generation and load,the stochastic chance constrained programming model of multi-objective reactive power optimization in "source-network-load" distribution network is established with the minimum maximum voltage deviation and the minimum active power loss as the objective function.The hybrid intelligent algorithm combined with stochastic simulation,BP neural network and fast non-dominated solution sorting genetic algorithm is used to solve the model,and the simulation calculations is carried out in the IEEE-33 node power distribution system,which verifies the feasibility and effectiveness of the proposed model and solution method.(2)This paper studies the problem of reactive power coordination optimization in "source-network-load-storage" distribution network,and the randomness of photovoltaic,wind power output and load power is processed by the multi-state model,transforming the stochastic problem into multiple deterministic problems under single state and probability combination problems.Based on this,a multi-objective reactive power optimization model of "source-network-load-storage" distribution network is established,and the original mixed integer nonlinear programming model is transformed into a mixed integer second-order cone programming model by using the second-order cone technique.The simulation calculations are carried out in the IEEE-33 node and IEEE-123 node power distribution system respectively.The Gurobi mathematical programming solver is called to solve the model,and the feasibility and effectiveness of the proposed model and the solution method are verified.(3)This paper studies the problem of reactive power coordination optimization in "source-network-load-storage-vehicle" distribution network,considering the stochastic fuzzy characteristics of distributed generation,load and electric vehicle,the stochastic fuzzy chance constrained programming model for multi-objective reactive power optimization of "source-network-load-storage-vehicle" distribution network is established.The hybrid intelligent algorithm based on stochastic fuzzy simulation is used to solve the model,and the IEEE-33 node power distribution system is used as the simulation system to verify the feasibility and effectiveness of the proposed model and solution method.