Multi‐objective optimal PMUs placement for online assessment of small‐signal stability

Summary The current paper presents a multi‐objective approach for the optimal placement of phasor measurement units (PMUs) for small‐signal stability assessment of a power system. The proposed methodology is based on a multi‐signal Prony analysis of the voltage amplitude, voltage angle, and frequenc...

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Vydáno v:International transactions on electrical energy systems Ročník 29; číslo 11
Hlavní autoři: Tarif, Toufik, Ladjici, Ahmed Amine, Amrane, Youcef, Chabane, Yasmina
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken John Wiley & Sons, Inc 01.11.2019
Témata:
Algorithms
Classification
Electric potential
Evolutionary algorithms
Evolutionary computation
Measuring instruments
Modal analysis
multi‐objective optimization
multi‐Prony analysis
Noise measurement
Particle swarm optimization
phasor measurement units
Placement
small signal stability assessment
Sorting algorithms
Stability analysis
system observability
Voltage
ISSN:2050-7038, 2050-7038
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Shrnutí:Summary The current paper presents a multi‐objective approach for the optimal placement of phasor measurement units (PMUs) for small‐signal stability assessment of a power system. The proposed methodology is based on a multi‐signal Prony analysis of the voltage amplitude, voltage angle, and frequency signals measured by the PMUs. A Pareto Archive Differential Evolution (PADE) algorithm is used to determine the best location of PMUs minimizing the PMUs number and maximizing the signal‐to‐noise ratio (SNR) subject to full system constraints. The capability of the proposed approach has been demonstrated through several cases studies, where it gives an accurate estimation of electromechanical modes when confronted with modal analysis under various scenarios, disturbances, and measurement noise. Additionally, the PADE algorithm is compared with nondominated sorting approach (NSGA)‐III, multi‐objective differential evolution (MODE), and multi‐objective particle swarm optimization (MOPSO) algorithms, and the superiority of PADE algorithm for solving the optimal PMUs placement (OPP) problem is demonstrated.
Bibliografie:ObjectType-Article-1
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ISSN:2050-7038
2050-7038
DOI:10.1002/2050-7038.12117