Minimizing the number of PMUs and their optimal placement in power systems

Mahaei, Seyyed Mehdi; Hagh, Mehrdad Tarafdar

doi:10.1016/j.epsr.2011.09.010

Cited by 76 publications

(62 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is then applied to various IEEE standard test systems. The results are presented and some of which are found to be better in terms of their MR with the same number of PMUs as compared to those of other published papers for the same problem and test system with similar conditions (Mahaei and TarafdarHagh, 2012;Jamuna and Swarup, 2012).…”

Section: Introductionmentioning

confidence: 64%

“…In Chakrabarti et al (2008), the PMU placement problem has been solved by a weighted sum single objective approach, but the weights which can lead to optimal solutions are not discussed. In Mahaei and TarafdarHagh (2012), integer linear programming (ILP) approach is used to find the minimum number of PMUs. The observability determination is dependent on the conventional measurements due to their inclusion in the measurement scheme and also the computational burden is very high in this approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-objective artificial bee colony-based optimal PMU placement with considering zero injection bus in power network

Nayak

Mahapatra

Rout

2017

IJCAET

View full text Add to dashboard Cite

Abstract:A novel multi-objective discrete artificial bee colony-based optimisation algorithm is proposed for the optimal phasor measurement units placement problem. The proposed algorithm is designed to incorporate a binary mutation step for efficient exploration and exploitation of any undiscovered region in the search space. A fuzzy-based mechanism is used to evaluate the best compromised solution from the final Pareto optimal set obtained by non-dominated sorting and crowding distance mechanism. A combination of two diverse objectives, i.e., minimisation of number of phasor measurement units and maximisation of N -1 measurement reliability are taken into consideration with complete system observability. The simulation results are obtained both with and without inclusion of the zero injection effect in the observability analysis on IEEE standard systems and are compared with the recently published papers to demonstrate the effectiveness of the proposed algorithm. All the programmes are implemented in standard MATLAB environment version R2010a.Keywords: phasor measurement units; PMUs; power system observability; measurement redundancy; artificial bee colony-based optimisation; multi-objective optimisation. Multi-objective artificial bee colony-based optimal PMU placement 103Reference to this paper should be made as follows: Nayak, M.R., Mahapatra, K. and Rout, P.K. (2017)

show abstract

Section: Introductionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Multi-objective artificial bee colony-based optimal PMU placement with considering zero injection bus in power network

Nayak

Mahapatra

Rout

2017

IJCAET

View full text Add to dashboard Cite

show abstract

“…References [1][2][3][4][5][6][7][8][9][10][11][24][25][26] accounted PMUs at every bus are the same cost, so the objective function of the minimum cost of PMUs corresponds to the minimum number of PMUs. However given the fact that, the cost corresponding to different PMUs are different due to the number of channels of each bus is not the same.…”

Section: Object Function For Full Network Observabilitymentioning

confidence: 99%

“…This solution is based on the required number of redundancies to find out the minimum number and the placement of PMUs. However, as same as the solution in [4,[10][11][12], the redundancy is still passive; it cannot implement to obtain the desired redundancy for the specific buses.…”

Section: Introductionmentioning

confidence: 99%

“…With the aim of finding out the PMU placement which achieves the best observable reliability, the authors in [4,[10][11][12] proposed solutions to get the maximum redundancy in the network observability. These studies could find the best redundant case; however, the redundancy is passive because it happens casually when solving the observability problem.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Placement of Phasor Measurement Unit for Observation Reliability Enhancement

Tran¹,

Zhang²,

Nguyen³

2017

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-Phasor Measurement Unit (PMU) placement is a crucial problem for State Estimation (SE) of the power system, which can ensure that the power network is fully observed. Further, the observation reliability problem of the system has been concerned in the operation conditions. In this paper, based on modified weighted adjacent matrix (A w ), an optimal placement method is proposed to solve simultaneously two problems involving the optimal PMU placement problem and the observation reliability enhancement problem of the system. The purpose of the proposed method is to achieve both the minimum total cost and the maximum observation reliability, with a focus on increasing the security of observability, strengthening the observation reliability of buses as well as enhancing the effectiveness of redundancy. Simulations on IEEE 14, 24, 30 and 57 bus test systems are presented to justify the methodology. The results of this study show that the proposed method is not only ensuring the power network having the observability effectively but also enhancing significantly the observation reliability. Therefore, it can be a useful tool for SE of the power system.

show abstract

Optimal PMU placement for modeling power grid observability with mathematical programming methods

Almunif

Fan

2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Phasor measurement units (PMUs) can obtain synchronized voltage and current phasors to increase the accuracy of state estimation results. Optimal PMU placement (OPP) reduces the required number of PMUs to make the system fully observable. In this paper, two mathematical programming formulations, which are mixed integer linear programming (MILP) and nonlinear programming (NLP), for power grid observability modeling to solve the OPP problem are presented. Power flow and zero injection measurement modeling along with restricted communication facilities, PMU failure, and limited channel capacity contingencies are investigated. MILP zero injection formulation is improved to overcome the observability redundancy and optimality drawbacks. A new formulation for nonlinear programming‐based PMU placement for zero injection measurement is proposed. MILP and NLP methods are compared to illustrate the advantages and disadvantages of each method. The comparison and proposed formulations are examined on IEEE 14‐, 57‐, 118‐, 300‐bus test systems and a large 2383‐bus Polish system to demonstrate their effectiveness.

show abstract

Minimizing the number of PMUs and their optimal placement in power systems

Cited by 76 publications

References 12 publications

Multi-objective artificial bee colony-based optimal PMU placement with considering zero injection bus in power network

Multi-objective artificial bee colony-based optimal PMU placement with considering zero injection bus in power network

Optimal Placement of Phasor Measurement Unit for Observation Reliability Enhancement

Optimal PMU placement for modeling power grid observability with mathematical programming methods

Contact Info

Product

Resources

About