Research On State Estimation And Robust Measurement Placement In Active Distribution Networks

The increasing integration of distributed generations(DG)is gradually changing the traditional distribution system.In addition,the automation level of distribution system has improved significantly,real-time network reconfiguration is possible.Distribution systems can flexibly choose the more economic and reliable network structures.Active distribution network(ADN)will be the trend of the future distribution system.The active nature of the ADN call for an online awareness of the system,distribution system state estimation(DSSE)is the key to obtain the status of the system.However,the real-time measurements in distribution system are insufficient,many pseudo measurements with high variance are usually added to obtain the observability of the system.Therefore,it is necessary to determine the number,locations and types of measurements to improve the accuracy of DSSE.It is of great theoretical and practical value to study the suitable state estimation and measurement allocation method for ADN,which can ensure the safe and stable operation of the system.In this paper,the sate estimation and measurement placement for ADN is researched,main research works are:(1)The sate estimation for ADN considering the impacts of DG is proposed.The probability density function of the non-monitored DG is modeled by gaussian mixture model(GMM),the parameters of which can be obtained by expectation maximization algorithm(EM).In DSSE,the power output of DG is considered as pseudo measurement,the value of which is the random variable following GMM,and the weight of it is the inverse of the variance of GMM.In order to reflect the correlations of DG,a multi-dimensional GMM is applied to model the power outputs of several DGs simultaneously.The off-diagonal elements of covariance matrix of GMM are the corresponding elements in the measurement error covariance matrix.(2)The measurement saturation characteristic is theoretically derived.The relationship between the DSSE accuracy and measurement number based on nonlinear measurement functions is analyzed.The measurement saturation characteristic is theoretically derived by Sherman-Morrison function and Submodularity,the impacts of network structure on it is also analyzed by simulation results.Based on the measurement saturation characteristic,the saturation number of measurement system is determined,which can be a reference to choose the number of measurements in measurement placement.It is a guide of the measurement placement and has practical significance,which can avoid the case that many measurements are installed without improvement in DSSE accuracy.(3)A robust measurement placement model in ADN is established,which considers the economy and the estimation accuracy of different network.In this model,the estimation accuracy of normal,meshed,optimal reconfiguration and fault reconfiguration network structures are considered,which improve the robustness of measurement placement.The weights of economy,estimation accuracy and different network structures are determined by analytic hierarchy process(AHP).The measurement placement is determined by heuristic algorithm.Simulation results demonstrate that the measurement placement model can guarantee the estimation accuracy of different network structures,and it can tradeoff the economy and the estimation accuracy effectively.