Reconfiguration and Optimal Micro-Phasor Unit Placement in a Distribution System Using Taguchi-Binary Particle Swarm Opt
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RESEARCH ARTICLE-ELECTRICAL ENGINEERING
Reconfiguration and Optimal Micro-Phasor Unit Placement in a Distribution System Using Taguchi-Binary Particle Swarm Optimization Sukriti Tiwari1
· Ashwani Kumar1
Received: 1 March 2020 / Accepted: 17 September 2020 © King Fahd University of Petroleum & Minerals 2020
Abstract The concepts of smart grid and microgrid require new monitoring systems to support automation functionalities in control centers at electrical distribution system (EDS) level. The availability of micro-PMUs (µPMUs) nowadays equips the control centers with the necessary information, which improves the accuracy of distribution system state estimation, for its various applications. Further, a non-configured EDS involves a significant amount of active power losses that causes additional costs to utilities. The work presented in this paper introduces a generalized, two-stage robust methodology for optimal µPMU placement considering reconfiguration of the EDS. This hybrid method combines the Taguchi method and upgraded version of binary particle swarm optimization (BPSO) that ultimately provides fast and accurate global optimum. The Taguchi method engenders a more diversified population, which eventually evades premature convergence, and consequently, it makes BPSO more robust. The proposed methodology provides optimal solution for any radial distribution system. Here, for illustration, results obtained for standard IEEE-33 nodes feeder system have been given to demonstrate the behavior and viability of the referred methodology. Various case studies under complex conditions along with the comparative analysis with the existing methods have been carried out to corroborate the superiority and versatility of the proposed methodology. Keywords EDS · Reconfiguration · Micro-placement · Optimization
List of Symbols TIBPSOTaguchi integrated binary particle swarm optimization DSSE Distribution system state estimation EDS Electrical distribution system OA Orthogonal array APLM Active power loss minimization µPMU Micro-phasor measurement unit OmPP Optimal micro-PMU placement TM Taguchi method BPSO Binary particle swarm optimization EDS total power loss in configuration FT y Position of particle J Cost function T Represents configuration H Vector matrix for 7-node feeder
B 1
Sukriti Tiwari [email protected] Electrical Engineering Department, National Institute of Technology Hamirpur, Hamirpur, Himachal Pradesh 177005, India
cmk gmk Ain StNR NT p d P D, E M m, k θ N ˆ fit v
bˆ c1 , c2 fv pbest gbest γ
m − k switch state m − k branch conductance Bus incidence matrix Signal to noise ratio Branch numbers on T configuration Number of particles Dimension of search space Bus real power injection Denotes 2 levels of OA Number of experiments Bus indices Bus phase angle Number of nodes Fitness function Velocity of particle Transpose Vector of 1s or greater than 1 Acceleration constant Fitness value Particle best Global best Penalty factor
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Arabian Journal for Science and Engineering
i, j r1 ,r2 A R Y W C
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