Treffer: Optimal PMU Placement Using Nonlinear Programming

Title:
Optimal PMU Placement Using Nonlinear Programming
Contributors:
National Technical University of Athens Athens (NTUA), Institute of Structural Analysis and Antiseismic Research, National Technical University of Athens
Source:
OPT-i An International Conference on Engineering and Applied Sciences Optimization M. Papadrakakis, M.G. Karlaftis, N.D. Lagaros (eds.) Kos Island, Greece, 4-6 June 2014 ; https://hal.archives-ouvertes.fr/hal-01178321 ; OPT-i An International Conference on Engineering and Applied Sciences Optimization M. Papadrakakis, M.G. Karlaftis, N.D. Lagaros (eds.) Kos Island, Greece, 4-6 June 2014, Institute of Structural Analysis and Antiseismic Research, National Technical University of Athens, Jun 2014, Kos Island Greece, Greece
Publisher Information:
HAL CCSD
Publication Year:
2014
Collection:
Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
Subject Geographic:
Time:
Kos Island Greece, Greece
Document Type:
Konferenz conference object
Language:
English
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.AA6B2239
Database:
BASE

Weitere Informationen

International audience ; Phasor Measurement Units (PMUs) are essential measuring devices for monitoring, control and protection of power systems. The objective of the optimal PMU placement (OPP) problem is to minimize the number of PMUs and select the bus locations to make a power system completely observable. In this paper, the OPP problem is formulated as a nonlinear programming (NLP) problem and a sequential quadratic programming (SQP) method is used for its solution. Simulations are carried out on IEEE standard test systems, using MATLAB. The numerical results are compared to those obtained by a binary integer programming (BIP) model, also implemented in MATLAB. The comparative study shows that the proposed formulation yields the same number of PMUs as the BIP model. The fundamental contribution of this paper lies in investigating the feasibility of using NLP for the solution of the OPP problem and the ability of the proposed methodology to provide multiple solutions in contrast to the binary integer programming model. The System Observability Redundancy Index is adopted to further rank the multiple solutions.