Differential evolution based optimal PMU placement for fault observability of power system

Rajasekhar, B.; Chandel, Ashwani Kumar; Vedik, B.

doi:10.1109/sces.2013.6547514

Cited by 24 publications

(7 citation statements)

References 17 publications

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“…As mentioned early that the fault observability analysis has not extensively studied in literature work, However, there are few efforts made in [ 8 , 9 , 10 , 11 ] as discussed in the introduction part. The proposed algorithm results compared with the previous works in this section.…”

Section: Resultsmentioning

confidence: 99%

“…Minimizing the PMUs and maximizing the measurement redundancy lead the majority of researchers dealing with the PMU optimal placement as an optimization problem [ 1 , 3 , 4 , 5 , 6 , 7 , 8 ]. Therefore, the optimization problem of PMU placement is usually solved by the mathematical (conventional) techniques or the evolutionary (heuristic) algorithms [ 1 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…The optimal PMU placement for fault observability [ 9 , 10 , 11 , 12 ] issue has not been extensively discussed in research like the normal observability [ 1 , 3 , 4 , 5 , 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

“…The PMU placement is introduced in [11] as an optimization problem. The placement problem is formulated based on the integer linear programming procedure and solved using the differential evolution method to ensure the global optimization of the placement problem.…”

Section: Introductionmentioning

confidence: 99%

“…Topological representation done in this step is essential to describe the topological structure of any network configuration using the Connectivity Matrix (CM) [ 3 , 4 , 6 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical Clustering based optimal PMU placement for power system fault observability

Eissa

Kassem

2018

Heliyon

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Optimal number and location of phasor measurement units (PMUs) in the power system networks faces challenges for achieving the full network observability during fault conditions. Achieving fault observability approach requires more constraints than normal system observability and consequently suffers from complex analysis and heavy computational burden for the large-scale networks. A new algorithm for determining the optimal PMU placement considering the network fault observability is introduced. The proposed algorithm is achieved through four stages. The first stage is achieved through the network fault simulation to obtain the post fault change in voltage (ΔV) at each bus. Then, the post fault change in voltage (ΔV) is used to build the network connectivity matrix (CM) and forming a new developed Faulted Connectivity Matrix (FCM) that describes the power system topology during the fault conditions. The correlation between the buses is obtained, in the second stage, by applying Pearson correlation coefficient. Hierarchical Clustering technique is given, in the third stage, to cluster the network into coherent zones to find the most correlated buses. Finally, the optimal location of the PMUs is identified within each zone based on simple proposed placement rules. The proposed algorithm is tested under a variety of fault events applied on different standard test systems. The results show the simplicity and the effectiveness of the proposed algorithm.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The optimal PMU placement for fault observability [ 9 , 10 , 11 , 12 ] issue has not been extensively discussed in research like the normal observability [ 1 , 3 , 4 , 5 , 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Topological representation done in this step is essential to describe the topological structure of any network configuration using the Connectivity Matrix (CM) [ 3 , 4 , 6 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations