Optimal placement of synchronized phasor measurement units based on differential evolution algorithm

Al-Mohammed, A.H.; Abido, M. A.; Mansour, M.M.

doi:10.1109/isgt-mideast.2011.6220820

Cited by 10 publications

(3 citation statements)

References 20 publications

(21 reference statements)

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“…In (17), w3 and w4 are two weight values. The parameter NL refers to the number of buses that are not being observed twice by the PMUs placement and S is the measurement redundancy used when considering the single PMU loss.…”

Section: Single Pmu Lossmentioning

confidence: 99%

“…The integer linear programming (ILP) method is widely used for solving the OPP problem [5]- [8] since it is capable of solving the OPP problem in a very short time. The exhaustive search (ES) method [9]- [11] and heuristic algorithms such as simulated annealing (SA) [12], genetic algorithm (GA) [13], [14], firefly algorithm (FA) [15], tabu search [16], differential evolution (DE) [17], [18], and particle swarm optimization (PSO) through a binary variant called binary PSO (BPSO) [19]- [25] have shown that they are also capable of finding the optimal placement of PMUs. In these existing studies, many constrained factors such as the effect of the zero-injection bus (ZIB), conventional measurement, a single PMU loss, line outage and PMU's channel limits are considered while solving the OPP problem.…”

Section: Introductionmentioning

confidence: 99%

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Integrated Mutation Strategy With Modified Binary PSO Algorithm for Optimal PMUs Placement

Rahman

Zobaa

2017

IEEE Trans. Ind. Inf.

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Optimal phasor measurement units (PMUs) placement refers to the strategic placement of PMUs to achieve the full observability of power systems with a minimum number of PMUs. A strategic placement is needed because of the economic or technical restriction that hinders the deployment of PMUs on every bus. A modified version of the binary particle swarm optimization (BPSO) method is proposed in this paper by integrating a mutation strategy and the V-shaped sigmoid function for placing the PMUs that maintains the full power system observability in the presence of zero-injection bus, single PMU loss and PMU's channel limits while maximizing the measurement redundancy. The solution that has the highest measurement redundancy was selected as the best placement of PMUs. The use of mutation strategy and V-shaped sigmoid function in this paper improves the population diversity, thereby minimizing the chance of the particles being trapped in the local optima, consequently leading to a quality solution. In order to validate its effectiveness, the results obtained by the proposed method are compared with other published techniques to demonstrate the accuracy and validity of the proposed technique. The results of the IEEE 300bus system show that the proposed method effectively managed to reduce the number of PMUs needed.

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Section: Single Pmu Lossmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated Mutation Strategy With Modified Binary PSO Algorithm for Optimal PMUs Placement

Rahman

Zobaa

2017

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

show abstract

“…Nonlinear constraints were formed when considering an adjacent zero-injection bus based on the hybrid topology transformation. Differential evolution (DE) optimization was adopted by Al-Mohammed et al [21] to solve the OPP problem. Chakrabarti and Kyriakides [22] used exhaustive search (ES) algorithm where the authors claimed it gave better results than the method used by Xu and Abur [13] based on the uniform measurement redundancies obtained in the results.…”

Section: Introductionmentioning

confidence: 99%