Optimal placement of PMUs to maintain network observability using a modified BPSO algorithm

Hajian, M.; Ranjbar, Ali Mohammad; Amraee, Turaj; Mozafari, Babak

doi:10.1016/j.ijepes.2010.08.007

Cited by 195 publications

(94 citation statements)

References 18 publications

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“…Step 5: Repair the strategy for constraint management Whenever the firefly position in the algorithm is modified, check the constraints (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). If there is any violation in constraint, alter the bit to zero to uninstall the PMU, in the corresponding bus to overcome the violation.…”

Section: Methodsmentioning

confidence: 99%

“…The stochastic search algorithms such as Genetic Algorithm (GA) [12], Immunity Genetic Algorithm (IGA) [13], Binary Particle Swarm Optimization (BPSO) [14] and Improved Tabu Search (ITS) [15] are presented to obtain the reliable OPP solutions. These techniques are found to be good for determining the global optimal solutions of PMUs placement and can be considered successful to a certain extent.…”

Section: Analysis Of Optimal Pmus Placementmentioning

confidence: 99%

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A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

Jeyaraj¹,

Rajasekaran²,

Kumar³

et al. 2015

Journal of Electrical Engineering and Technology

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-This paper proposes a multi-objective optimal placement method of Phasor Measurement Units (PMUs) in large electric transmission systems. It is proposed for minimizing the number of PMUs for complete system observability and maximizing measurement redundancy of the buses, simultaneously. The measurement redundancy of the bus indicates that number of times a bus is able to monitor more than once by PMUs set. A high level of measurement redundancy can maximize the system observability and it is required for a reliable power system state estimation. Therefore, simultaneous optimizations of the two conflicting objectives are performed using a binary coded firefly algorithm. The complete observability of the power system is first prepared and then, single line loss contingency condition is added to the main model. The practical measurement limitation of PMUs is also considered. The efficiency of the proposed method is validated on IEEE 14, 30, 57 and 118 bus test systems and a real and large-scale Polish 2383 bus system. The valuable approach of firefly algorithm is demonstrated in finding the optimal number of PMUs and their locations by comparing its performance with earlier works.

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Section: Methodsmentioning

confidence: 99%

Section: Analysis Of Optimal Pmus Placementmentioning

confidence: 99%

A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

Jeyaraj¹,

Rajasekaran²,

Kumar³

et al. 2015

Journal of Electrical Engineering and Technology

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%

Optimal Placement of Phasor Measurement Unit for Observation Reliability Enhancement

Tran¹,

Zhang²,

Nguyen³

2017

Journal of Electrical Engineering and Technology

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-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.

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“…PSO has been found to be extremely effective in solving a wide range of engineering optimization problems [22,83].…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Artificial Intelligence Versus Conventional Mathematical Techniques: A Review for Optimal Placement of Phasor Measurement Units

Negash

Khan

Yohannes

2016

Technol Econ Smart Grids Sustain Energy

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The Phasor Measurement Unit (PMU) is a contemporary metering device installed on system to enable the power system monitoring and control. PMUs are most accurate and advance time synchronized technology which provides measurements of voltages at the buses and also current phase values which are connected to those buses where these PMUs are located. PMU placement on each bus of a system is difficult to achieve either due to cost factor or due to non-existence limitation of communication facilities in some parts of the system. Moreover, as a consequence of Ohm's Law, when a PMU is placed at a bus, neighboring busses also become observable. This implies that a system can be made observable with a lesser number of PMUs than the number of busses. It is necessary to determine the minimum number of PMUs for entire observability of the power network. The optimal placement of PMUs (OPP) problem can be solved by various techniques. Hence in this paper a comprehensive review is presented on the OPP problems under the characterization of heuristic and mathematical methodologies. Also a comparison between

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Optimal placement of PMUs to maintain network observability using a modified BPSO algorithm

Cited by 195 publications

References 18 publications

A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

A Multi-objective Placement of Phasor Measurement Units Considering Observability and Measurement Redundancy using Firefly Algorithm

Optimal Placement of Phasor Measurement Unit for Observation Reliability Enhancement

Artificial Intelligence Versus Conventional Mathematical Techniques: A Review for Optimal Placement of Phasor Measurement Units

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