Robust optimisation-based state estimation considering parameter errors for systems observed by phasor measurement units

This study presents a new robust state estimation (SE) approach for power systems that are monitored by synchronised phasor measurements. The proposed robust SE utilises the least absolute value (LAV) of residuals to determine the system state. Although conventional deterministic LAV-based SE is rob...

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Vydáno v:IET generation, transmission & distribution Ročník 12; číslo 8; s. 1915 - 1921
Hlavní autoři: Kabiri, Mehdi, Amjady, Nima
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 30.04.2018
Témata:
Big‐M linearisation technique
integer programming
LAV‐SE method
least absolute value
linear programming
linearisation techniques
parameter errors
phasor measurement
phasor measurement units
power system state estimation
probabilistic evaluation approach
probability
Research Article
robust optimisation
robust optimisation‐based state estimation
robust SE
synchronised phasor measurements
tractable mixed‐integer linear programming optimisation problem
synchronised phasor measurements
linearisation techniques
power system state estimation
integer programming
probability
parameter errors
linear programming
robust optimisation
phasor measurement units
tractable mixed-integer linear programming optimisation problem
robust SE
LAV-SE method
Big-M linearisation technique
least absolute value
probabilistic evaluation approach
phasor measurement
robust optimisation-based state estimation
ISSN:1751-8687, 1751-8695
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Shrnutí:This study presents a new robust state estimation (SE) approach for power systems that are monitored by synchronised phasor measurements. The proposed robust SE utilises the least absolute value (LAV) of residuals to determine the system state. Although conventional deterministic LAV-based SE is robust against bad measurements, it is vulnerable with respect to the network parameters’ errors. In other words, the conventional LAV-SE method is not robust against the network parameters’ errors and these errors can make the SE results inaccurate. The proposed robust SE aims at solving this problem of the conventional LAV-SE. Robust optimisation, strong duality theorem, and Big-M linearisation technique have been used to construct the proposed SE approach, which is robust against the network parameters’ errors. Additionally, the proposed robust SE is finally formulated as a tractable mixed-integer linear programming optimisation problem. Comprehensive numerical experiments and a probabilistic evaluation approach are presented to evaluate the effectiveness of the proposed robust SE compared to the conventional deterministic SE in the presence of the uncertainty source of network parameters’ errors.
ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2017.1128