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Content Provider | IEEE Xplore Digital Library |
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Author | Negnevitsky, M. Terry, J. Thanh Nguyen |
Copyright Year | 2014 |
Description | Author affiliation: TasNetworks Pty Ltd., Hobart, TAS, Australia (Terry, J.; Thanh Nguyen) || Sch. of Eng., Univ. of Tasmania, Hobart, TAS, Australia (Negnevitsky, M.) |
Abstract | Information about the certainty of the predicted state of a network is crucial for the effective management of a modern power system. In transmission systems, observability analysis is used to assess whether the estimated state is valid, based on the available measurements. In distribution systems there is no method for quantifying the uncertainty in a modelled state; this places limitations on how the modelled state can be used. This paper explores a new method of quantifying the uncertainty in a state estimation solution, with information entropy. A Monte Carlo simulation approach was used to determine the probability of the network being in a specific state. The proposed approach allows for the objective evaluation of the certainty of a state solution in distribution networks, which can be easily interpreted by distribution network service providers. Case studies were conducted, results are resented and discussed. |
Starting Page | 1 |
Ending Page | 6 |
File Size | 1583709 |
Page Count | 6 |
File Format | |
ISBN | 9780646923758 |
DOI | 10.1109/AUPEC.2014.6966487 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-09-28 |
Publisher Place | Australia |
Access Restriction | Subscribed |
Rights Holder | ACPE |
Subject Keyword | optimal meter placement Distribution network state network observability information entropy Uncertainty Power measurement Entropy Loss measurement Observability State estimation Load flow |
Content Type | Text |
Resource Type | Article |
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