Uncertainty Measurement Of Islanded Microgrid Power Flow With Renewable Energy Generations

With the development of renewable energy and distributed generation technology,microgrid can achieve efficient use of energy,and is an effective supplement to traditional power grids,as an important carrier for dissipating distributed power.The microgrid has two operation modes: grid-connected mode and islanded mode.The islanded operation mode of the microgrid is conducive to improving the flexibility and reliability of the grid operation,which is increasingly valued by researchers.The calculation of power flow analysis is the basis for the planning and operation of the islanded microgrid.At the same time,the output of distributed renewable generation in the microgridis is intermittent and fluctuant,which makes the operation of microgrid with significant uncertainty.Therefore,based on probabilistic power flow calculation and global sensitivity analysis,this paper studies the power flow calculation of islanded microgrids considering uncertain factors,quantifies the influence of uncertain factors on system operation,and provide more comprehensive and reliable information for planning and operation of microgrid.This paper mainly studies from the following aspects:Based on the islanded operation mode of microgrid,the droop control strategies of DG are studied.Considering the difference in the characteristics of grid structure,system parameters and operation mode between the islanded microgrid and the main network,the power flow model of the islanded microgrid is established.A robust and adaptive method Leavenberg-Marguardt algorithm is used to solve the islanded microgrid power flow current.The parametric and non-parametric modeling methods for uncertain output of distributed renewable energy and load fluctuation are studied,and the probabilistic power flow model of the islanded microgrid is established.A probabilistic power flow algorithm based on polynomial chaos expansion(PCE)is proposed to overcome the low computational efficiency of traditional Monte Carlo simulation algorithms.Furthermore,in order to overcome the " dimension disaster" problem of PCE method in high-dimensional random variables problem,a minimum angle regression(LAR)is introduced to select input variables,and sparse polynomial chaos expansion(SPCE)is proposed.to solve probabilistic problem.Compared with the traditional method,the accuracy and efficiency of the proposed algorithm in solving the probabilistic power flow current of the islanded microgrid are verified.Sobol's global sensitivity analysis(GSA)method based on the variance analysis decomposition is used to quantify the influence of uncertainty factors on the power flow of islanded microgrids.Furthermore,a GSA method that takes the correlation of stochastic input variables into account is studied and applied to analyze the impact of the correlated distributed renewable generation output on the operation of islanded microgrid.Applying SPCE method to the calculation of the global sensitivity coefficients helps to overcome the problem of low efficiency of that based on Monte Carlo simulation,so that GSA method can be applied to the analysis of actual systems.Finally,the algorithm proposed in this paper is applied in the IEEE test system.The islanded microgrid power flow under different operating conditions are calculated.The influence of uncertainty factors on the power flow of the islanded microgrid is analyzed.Based on the GSA index,the key input random variables for system operation is identified.