An optimal PMU placement technique for power system observability

Roy, Biman Kumar Saha; Sinha, A.K.; Pradhan, Ashok Kumar

doi:10.1016/j.ijepes.2012.03.011

Cited by 180 publications

(42 citation statements)

References 18 publications

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“…By utilizing an embedded heuristic, a sequence of solutions is provided in which the best solution is obtained if one were to utilize repeated random trials of that heuristic. The Iterated Local Search (ILS) metaheuristic in [26,28,31] is used to minimize the size of the PMU configuration needed to observe the network .The algorithm is tested on IEEE test networks with 14, 57 and 118 nodes and compared to the results obtained in previous publications.…”

Section: Iterated Local Search (Ils)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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Section: Iterated Local Search (Ils)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 optimal PMU placement problem concerns with how many PMUs and where they should be installed in a power network to achieve full observability at minimum number of PMUs [14]. Hence, minimizing the number of PMUs is the objective function of this optimization problem and the constraint of the problem is being full observable of the network.…”

Section: Description Of Optimal Pmu Placement Problemmentioning

confidence: 99%

Optimal phasor measurement units placement to maintain network observability using a novel binary particle swarm optimization and fuzzy system

Abiri

Rashidi

2015

Journal of Intelligent &Amp; Fuzzy Systems

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This paper presents a hybrid modified binary particle swarm optimization and fuzzy system for obtaining the optimal number of PMUs which makes the power system completely observable. Observability assessment is done by means of topological observability rules. Moreover a new rule is employed which can decrease the number of required PMUs for full network observability. In all of the investigations, the effect of zero-injection buses in the power system is considered. Developed PMU placement method is illustrated using IEEE standard systems to demonstrate the effectiveness of the proposed algorithm. The results show that the whole system can be observable with installing PMUs on less than 20% of system buses.

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“…[14] presents an iterative whereas [15] determines the imperialistic competition algor partial swarm optimization (BP Table II describes the buse different references. Total no IEEE-30 bus system are 6.…”

Section: Test Systems and Simulatiomentioning

confidence: 99%

“…Ref. [14] presents an iterative method for PMU placement, whereas [15] determines the optimal location by binary imperialistic competition algorithm (BICA) and [16] by binary partial swarm optimization (BPSO) technique. Table III shows the buses taken as zero injection bus by different references.…”

Section: Test Systems and Simulatiomentioning

confidence: 99%

Optimal PMU placement using matrix modification based integer linear programming

Khare

Sahu

Sunitha

2014

2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014]

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Power system state estimation with exclusive utilization of synchronous phasor measurements demands that the system should be completely observable through PMUs only. To have minimum number of PMUs, the PMU placement issue in any network is an optimization problem. In this paper, a model for the optimal placement of phasor measurement units (PMUs) in electric power networks is presented. Optimal measurement set is determined to achieve full network observability during normal conditions, i.e. no PMU failure or transmission line outage is considered. Observability analysis is carried out using topological observability rules. A connectivity matrix modification based integer linear programming is used as an optimization tool to obtain the minimal number of PMUs and their corresponding locations while satisfying associated constraint. Simulation results for IEEE 30-bus and New England 39-bus test systems are presented and compared with the existing techniques, to justify the effectiveness of proposed method. In All investigations, the zeroinjected buses are considered to obtain the best answers.Keywords-Phasor measurment unit; integer linear programming; network observability; optimal placement; network connectivity.I.

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An optimal PMU placement technique for power system observability

Cited by 180 publications

References 18 publications

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

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

Optimal phasor measurement units placement to maintain network observability using a novel binary particle swarm optimization and fuzzy system

Optimal PMU placement using matrix modification based integer linear programming

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