TY - JOUR
T1 - A multi-objective optimal PMU placement considering fault-location topological observability of lengthy lines
T2 - A case study in OMAN grid
AU - Al-Hinai, Amer
AU - Karami-Horestani, Ali Reza
AU - Alhelou, Hassan Haes
N1 - Funding Information:
The authors would like to acknowledge the support of the Sultan Qaboos University, the Ministry of Higher Education, Research and Innovation, Oman Electricity Transmission Company, and Occidental Oman. This paper is an outcome of the Block Funding program “Towards Integrated Monitoring System for Migration to Smart Grid in Oman (TIMSOman)” Project code (RC/RG-ENG/ECED/19/03).
Funding Information:
The authors would like to acknowledge the support of the Sultan Qaboos University , the Ministry of Higher Education, Research and Innovation, Oman Electricity Transmission Company , and Occidental Oman . This paper is an outcome of the Block Funding program “Towards Integrated Monitoring System for Migration to Smart Grid in Oman (TIMSOman)” Project code (RC/RG-ENG/ECED/19/03).
Publisher Copyright:
© 2022 The Author(s)
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Using PMU data, the fault location algorithm has gradually been trended in the literature. Besides the optimality of the algorithm, the fault location application should directly receive the data of the faulty line from the PMU devices to have the best performance; using state estimation to create the input data of fault location algorithm not only wastes the golden time, but it also decreases the reliability. Given, it is not possible to install PMU devices in all buses of the system, it is better to install them for the lengthy lines having the most probability of the failure. Although various approaches have been presented in the literature to solve optimal PMU placement (OPP), the fault location observability has less been considered in OPP formulation Accordingly, this paper considers a new index, named fault location observability (FLO), as a second objective function in its OPP formulation. Using this index, in addition to minimizing PMU installation cost, the number of lengthy lines being directly observable are also maximized. Using the ɛ-constraint method, the multi-objective problem has been solved several times as single-objective optimizations. Given the constraints and objective functions are linear, the work presents a mixed integer linear programming (MILP) formulation for the placement problem. Using the GAMS under CPLEX solver, the global optimal solutions of MILP model corresponding to the various ɛ-constraints yields to a Pareto optimal front. The simulation results, next, implements the proposed method on the IEEE 300 bus test system as well as the practical OMAN grid to prove the effectiveness of the proposed method.
AB - Using PMU data, the fault location algorithm has gradually been trended in the literature. Besides the optimality of the algorithm, the fault location application should directly receive the data of the faulty line from the PMU devices to have the best performance; using state estimation to create the input data of fault location algorithm not only wastes the golden time, but it also decreases the reliability. Given, it is not possible to install PMU devices in all buses of the system, it is better to install them for the lengthy lines having the most probability of the failure. Although various approaches have been presented in the literature to solve optimal PMU placement (OPP), the fault location observability has less been considered in OPP formulation Accordingly, this paper considers a new index, named fault location observability (FLO), as a second objective function in its OPP formulation. Using this index, in addition to minimizing PMU installation cost, the number of lengthy lines being directly observable are also maximized. Using the ɛ-constraint method, the multi-objective problem has been solved several times as single-objective optimizations. Given the constraints and objective functions are linear, the work presents a mixed integer linear programming (MILP) formulation for the placement problem. Using the GAMS under CPLEX solver, the global optimal solutions of MILP model corresponding to the various ɛ-constraints yields to a Pareto optimal front. The simulation results, next, implements the proposed method on the IEEE 300 bus test system as well as the practical OMAN grid to prove the effectiveness of the proposed method.
KW - Fault location observability (FLO) index
KW - MILP-based multi-objective optimization
KW - OMAN grid
KW - Optimal PMU placement
KW - Phasor measurement unit
UR - http://www.scopus.com/inward/record.url?scp=85145559241&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145559241&partnerID=8YFLogxK
U2 - 10.1016/j.egyr.2022.12.046
DO - 10.1016/j.egyr.2022.12.046
M3 - Article
AN - SCOPUS:85145559241
SN - 2352-4847
VL - 9
SP - 1113
EP - 1123
JO - Energy Reports
JF - Energy Reports
ER -