Reactive Power Optimization Of Distribution Network With Distributed Generation

Traditional power generation method bring about two problems.First,the energy used is non-renewable energy,which will cause energy shortage.Second,the combustion of coal,oil,etc.produces a large amount of greenhouse gases.In this context,distributed power sources that use clean energy for power generation have rapidly developed.When distributed power is connected to the distribution network,it will inevitably have certain impact on the distribution network.The beneficial effects include reducing the network loss of the system,etc.The adverse effects include voltage imbalance and voltage flashover,waveform distortion,etc.,so it is necessary to study the optimization of distribution network with distributed generation.This paper studies the reactive power optimization problem of distribution network with distributed generation as follows:Firstly,the static reactive power optimization model of distribution network with distributed generation is studied.The reactive power characteristics of two common distributed generation are studied: doubly-fed wind turbines and photovoltaic generator sets.So that the range of reactive output can be obtained when the active power and other parameters are known.Therefore,its reactive output can be incorporated into the static reactive power optimization model as one of the optimization methods.Combined with the traditional capacitor bank switching optimization method,a static reactive power optimization model with network loss as the optimization target is established.Secondly,for optimization model,the intelligent optimization algorithm-particle swarm optimization algorithm is considered to solve the problem.And the particle swarm algorithm is improved in two ways: the parameters of the particle swarm optimization algorithm are improved,on the other hand,in the process of particle swarm optimization,variation of the particles is considered.The improved particle swarm optimization algorithm is tested by the test function ‘Griewank' to verify the superiority of the algorithm over the ordinary particle swarm.Then the improved particle swarm optimization algorithm is applied to the reactive power optimization model.Simulation shows that it can effectively reduce the network loss of the distribution network,optimize the node voltage,and the simulation can also prove the effectiveness of the distributed generation reactive power into the optimization model.Finally,considering that in actual situation,the load value always fluctuates,andthe output of the distributed power supply is often fluctuating,dynamic reactive power optimization is more in line with the actual situation.To this end,this paper studies the dynamic reactive power optimization problem of distribution network with distributed power supply.Aiming at this problem,the time division strategy based on Fisher's segmentation method is used to solve the problem.Firstly,Fisher's optimal segmentation method is introduced to segment the forecast data of one day's load and distributed power output.For each segment,the average is equivalent to the segment.The reactive power output range of the distributed power supply is calculated with considering the influence of randomness,and then the static reactive power optimization method for reactive power optimization is used to solve it.The simulation verifies the effectiveness of the time slot.