2017
DOI: 10.1049/iet-gtd.2016.1983
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Optimal cost wide area measurement system incorporating communication infrastructure

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Cited by 26 publications
(24 citation statements)
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References 27 publications
(81 reference statements)
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“…Communication constraints on PMU placement GA [97] Data loss constraints on PMU placement ILP [98] Limited communication constraints ILP [99] Multi-objective discrete Artificial Bee Colony [100] sequential quadratic programming [101] ILP [102] ILP [103] Constraint on routing paths between PMUs and PDC GA [104] Constraint on power system observability with maximum communication reliability ILP [105] Multi-objective GA [106] Communication feasibility constraint using a minimum number of nodes. Randomized greedy algorithm [107] Minimization of communication system cost Simulated Annealing (SA) [108] binary imperialistic competition algorithm [109] GA [110,111] Constraint on communication system reliability incorporating network failures ILP [112] Constraint on power system observability with minimum communication system cost and maximum communication redundancy…”
Section: Resultsmentioning
confidence: 99%
“…Communication constraints on PMU placement GA [97] Data loss constraints on PMU placement ILP [98] Limited communication constraints ILP [99] Multi-objective discrete Artificial Bee Colony [100] sequential quadratic programming [101] ILP [102] ILP [103] Constraint on routing paths between PMUs and PDC GA [104] Constraint on power system observability with maximum communication reliability ILP [105] Multi-objective GA [106] Communication feasibility constraint using a minimum number of nodes. Randomized greedy algorithm [107] Minimization of communication system cost Simulated Annealing (SA) [108] binary imperialistic competition algorithm [109] GA [110,111] Constraint on communication system reliability incorporating network failures ILP [112] Constraint on power system observability with minimum communication system cost and maximum communication redundancy…”
Section: Resultsmentioning
confidence: 99%
“…32 It has been reported to be an efficient method for solving different optimization problems in power systems. [33][34][35][36] The optimization of the static VAR compensator parameters has been achieved through GSA for reactive power compensation in real-time application by Sankar et al 33 Enhanced GSA has been employed for feeder reconfiguration, losses, and operational cost minimization in distribution network. 34 In Singh, 35 binary GSA has been utilized for optimal cost and observability of wide area measurement system.…”
Section: Contributionmentioning
confidence: 99%
“…The VVO problem has been solved through a discrete gravitational search algorithm (DGSA) that bears interest for highly complex optimization problems regarding faster convergence and real‐time applications . It has been reported to be an efficient method for solving different optimization problems in power systems . The optimization of the static VAR compensator parameters has been achieved through GSA for reactive power compensation in real‐time application by Sankar et al Enhanced GSA has been employed for feeder reconfiguration, losses, and operational cost minimization in distribution network .…”
Section: Introductionmentioning
confidence: 99%
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“…Additionally, that work considers contingency conditions and pre-existence of some PMUs and communication cables in certain parts of the network. In the same way, [19] considered CI cost and several contingency conditions in a binary gravitational search algorithm, which showed better performance than in the previous work.…”
Section: Related Workmentioning
confidence: 99%