Bayesian Distribution System State Estimation In Presence Of Non-Gaussian Pseudo-Measurements
2016 IEEE INTERNATIONAL WORKSHOP ON APPLIED MEASUREMENTS FOR POWER SYSTEMS (AMPS)(2016)
摘要
Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could not fit with the normal distribution typically considered in DSSE. For this reason, suitable approaches have to be designed both to model the pseudo-measurements uncertainty and to consider it in the DSSE process. This paper proposes a DSSE algorithm based on the Bayesian theory able to handle appropriately pseudo-measurements with any uncertainty distribution. The procedure used to cluster different categories of prosumers and to generate the pseudo-measurement parameters provided as input to the DSSE is also presented. Tests on a low voltage network show the applicability of the proposed approach and the associated benefits.
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关键词
State Estimation,Bayesian Theory,Non-Gaussian uncertainty,pseudo-measurements,Distribution Grids
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