Result: Optimal PMU Placement Using Nonlinear Programming

Title:
Optimal PMU Placement Using Nonlinear Programming
Authors:
Theodorakatos, Nikolaos, Manousakis, Nikolaos, Korres, George
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, Institute of Structural Analysis and Antiseismic Research, National Technical University of Athens, Jun 2014, Kos Island Greece, Greece
Publisher Information:
HAL CCSD, 2014.
Publication Year:
2014
Collection:
collection:TDS-MACS
Subject Terms:
Binary Integer Programming, Optimal Placement, Sequential Quadratic Programming, Non Linear Programming, Phasor Measurement Unit, Mixed Integer Linear Programming, [MATH.MATH-OC]Mathematics [math], Optimization and Control [math.OC]
Subject Geographic:
Kos Island Greece, Greece
Original Identifier:
ARXIV: 1507.05258
HAL: hal-01178321
Document Type:
Conference conferenceObject<br />Conference papers
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/arxiv/1507.05258
Access URL:
https://hal.science/hal-01178321
https://hal.science/hal-01178321v2/document
https://hal.science/hal-01178321v2/file/Pages%20from%20e_book%20OPTi-Optimal_PMU_Placement_Using_Nonlinear_Programming.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.01178321v2
Database:
HAL

Further Information

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.