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

• Published in: International transactions on electrical energy systems Vol. 29; no. 11
• Main Authors: Tarif, Toufik, Ladjici, Ahmed Amine, Amrane, Youcef, Chabane, Yasmina
• Format: Journal Article
• Language: English
• Published: Hoboken John Wiley & Sons, Inc 01.11.2019
• Subjects: 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
• DOI: 10.1002/2050-7038.12117

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.