Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network

Modern power systems require advanced monitoring and control, a capability made possible by Phasor Measurement Units (PMUs) aided by synchrophasor technology. Because PMUs have significant costs, it is necessary to optimally place them in an electrical power network. This paper proposes the Optimal...

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Main Authors: Edwin Otieno Okendo, Cyrus Wabuge Wekesa, Michael Juma Saulo
Format: Article
Language:English
Published: Elsevier 2021-07-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844021017734
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spelling doaj-c4fea71713e44074a64caac916cca4be2021-08-02T04:41:59ZengElsevierHeliyon2405-84402021-07-0177e07670Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission networkEdwin Otieno Okendo0Cyrus Wabuge Wekesa1Michael Juma Saulo2Department of Electrical Engineering, Pan African University Institute of Basic Sciences Technology and Innovation (PAUSTI), Kenya; Corresponding author.School of Engineering, University of Eldoret (UOE), Eldoret, KenyaDepartment of Electrical and Electronics Engineering, Technical University of Mombasa (TUM), Mombasa, KenyaModern power systems require advanced monitoring and control, a capability made possible by Phasor Measurement Units (PMUs) aided by synchrophasor technology. Because PMUs have significant costs, it is necessary to optimally place them in an electrical power network. This paper proposes the Optimal PMU Placement (OPP) on the Kenya Power Transmission Network (Nairobi Region 30-bus system) using the existing methods; The Depth-First method, the Mixed Integer Linear Programming (MILP) using intlinprog solver, and the Artificial Bee Colony (ABC) algorithm. The algorithms are first implemented on the IEEE-14 and 30 bus test systems for verification before implementing the Kenya Power Transmission Network (Nairobi Region 30-bus system). Finally, the results for the three methods are compared. A key consideration is the System Observability Redundancy Index (SORI) under normal baseload conditions, with and without the inclusion of Zero Injection Buses (ZIBs). A higher value of SORI increases the measurement redundancy of the PMUs installed at a given bus. This paper further proposes the modelling of ZIB with adjacent buses by considering their Observability Index (OI). The case studies are modelled in Power System Analysis Toolbox (PSAT), and the simulations are carried out in MATLAB. From the simulation results, the ABC algorithm gives the optimal solution with the highest SORI compared to the Depth-First method and MILP, with the exclusion of the ZIB. The Nairobi region 30-bus system require 12 PMUs located at buses; 2, 5, 8, 9, 11, 13, 14, 16, 21, 24, 27 and 29 for complete power system observability with a SORI of 43.http://www.sciencedirect.com/science/article/pii/S2405844021017734Optimal PMU PlacementSystem Observability Redundancy IndexDepth FirstMixed Integer Linear ProgrammingArtificial Bee ColonyZero Injection Bus
collection DOAJ
language English
format Article
sources DOAJ
author Edwin Otieno Okendo
Cyrus Wabuge Wekesa
Michael Juma Saulo
spellingShingle Edwin Otieno Okendo
Cyrus Wabuge Wekesa
Michael Juma Saulo
Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
Heliyon
Optimal PMU Placement
System Observability Redundancy Index
Depth First
Mixed Integer Linear Programming
Artificial Bee Colony
Zero Injection Bus
author_facet Edwin Otieno Okendo
Cyrus Wabuge Wekesa
Michael Juma Saulo
author_sort Edwin Otieno Okendo
title Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
title_short Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
title_full Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
title_fullStr Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
title_full_unstemmed Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network
title_sort optimal placement of phasor measurement unit considering system observability redundancy index: case study of the kenya power transmission network
publisher Elsevier
series Heliyon
issn 2405-8440
publishDate 2021-07-01
description Modern power systems require advanced monitoring and control, a capability made possible by Phasor Measurement Units (PMUs) aided by synchrophasor technology. Because PMUs have significant costs, it is necessary to optimally place them in an electrical power network. This paper proposes the Optimal PMU Placement (OPP) on the Kenya Power Transmission Network (Nairobi Region 30-bus system) using the existing methods; The Depth-First method, the Mixed Integer Linear Programming (MILP) using intlinprog solver, and the Artificial Bee Colony (ABC) algorithm. The algorithms are first implemented on the IEEE-14 and 30 bus test systems for verification before implementing the Kenya Power Transmission Network (Nairobi Region 30-bus system). Finally, the results for the three methods are compared. A key consideration is the System Observability Redundancy Index (SORI) under normal baseload conditions, with and without the inclusion of Zero Injection Buses (ZIBs). A higher value of SORI increases the measurement redundancy of the PMUs installed at a given bus. This paper further proposes the modelling of ZIB with adjacent buses by considering their Observability Index (OI). The case studies are modelled in Power System Analysis Toolbox (PSAT), and the simulations are carried out in MATLAB. From the simulation results, the ABC algorithm gives the optimal solution with the highest SORI compared to the Depth-First method and MILP, with the exclusion of the ZIB. The Nairobi region 30-bus system require 12 PMUs located at buses; 2, 5, 8, 9, 11, 13, 14, 16, 21, 24, 27 and 29 for complete power system observability with a SORI of 43.
topic Optimal PMU Placement
System Observability Redundancy Index
Depth First
Mixed Integer Linear Programming
Artificial Bee Colony
Zero Injection Bus
url http://www.sciencedirect.com/science/article/pii/S2405844021017734
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