| The access of a large number of distributed power sources(DG)has changed the unidirectional radiation type grid structure of the traditional distribution network,which has led to the development of the distribution network towards the active distribution network(ADN).The intermittent power generation of high-permeability DG makes the state estimation of ADN more need to consider the uncertainty of DG,and the results obtained by the traditional Distribution State Estimation(DSE)method can not meet the actual operation.Scheduling requirements.Therefore,how to reasonably model the uncertainty of DG output and improve the accuracy of ADN state estimation becomes an urgent problem to be solved.In response to this problem,this paper mainly studies from the following aspects:First,the mathematical model of DSE is described,including the mathematical description of the distribution network measurement system and the mathematical description of the network parameters of the distribution network.Then the state based on Weighted Least Square Method(WLS)is introduced.The related theory of estimator;finally,the measurement function of DSE based on node voltage method and the related elements in the Jacobian matrix in its iterative process are described,which provides a theoretical basis for interval state estimation.Secondly in view of the uncertainties of distributed photovoltaic and wind power output,the related factors affecting the output of photovoltaics and wind turbines are introduced respectively.The extension of the output of photovoltaics and wind turbines is proposed by using the Extreme Learning Machine(ELM)theory.The model is verified by the example,and the pseudo-measurement data is provided for the state estimation.At the same time,an interval state estimation method for active distribution network considering fan and PV output randomness is proposed.Firstly the interval quantity is used to describe the uncertainty in the distribution network.The interval output of the photovoltaic and wind turbines predicted by ELM is used as the pseudo-quantit.measurement.The ADN interval state estimation model is established,based on Particle Swarm Optimization(PSO).State estimation of ADN.Finally,the example verification is carried out through the IEEE-33 distribution network.The results show that after the DG is connected to the distribution network,the voltage amplitude and phase angle of each node in the system have a certain degree compared with that before the access to the DG.The state estimation result obtained by PSO algorithm is more accurate than the traditional weighted least squares method(WLS);after using the interval number to describe the randomness of wind power and photovoltaic output,the estimated result is also in the interval form.This interval can provide a more intuitive upper and lower boundary information of the state of the distribution network. |
