Realistic Approach for Phasor Measurement Unit Placement: Consideration of Practical Hidden Costs

This paper presents a realistic cost-effective model for optimal placement of phasor measurement units (PMUs) for complete observability of a power system considering practical cost implications. The proposed model considers hidden or otherwise unaccounted practical costs involved in PMU installation. Consideration of these hidden but significant and integral part of total PMU installation costs was inspired from practical experience on a real-life project. The proposed model focuses on the minimization of total realistic costs instead of a widely used theoretical concept of a minimal number of PMUs. The proposed model has been applied to IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, New England 39-bus, and large power system of 300 buses and real life Danish grid. A comparison of the presented results with those reported by traditional methods has also been shown to justify the effectiveness of the proposed model with regard to its realistic and practical nature.

[1]  Salman Mohagheghi,et al.  Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems , 2008, IEEE Transactions on Evolutionary Computation.

[2]  M. Shahidehpour,et al.  Contingency-Constrained PMU Placement in Power Networks , 2010, IEEE Transactions on Power Systems.

[3]  Arne Hejde Nielsen,et al.  Simulation Model of the Transmission Grid for a Large Offshore Windfarm, Used in Education and Research at the Technical University of Denmark , 2006 .

[4]  M. Begovic,et al.  Nondominated sorting genetic algorithm for optimal phasor measurement placement , 2002, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[5]  Yuanzhan Sun,et al.  Optimal PMU placement for full network observability using Tabu search algorithm , 2006 .

[6]  Satu Viljainen,et al.  All quiet on the western front? Transmission capacity development in the Nordic electricity market , 2015 .

[7]  A.M. Ranjbar,et al.  Optimal Placement of Phasor Measurement Units: Particle Swarm Optimization Approach , 2007, 2007 International Conference on Intelligent Systems Applications to Power Systems.

[8]  J. S. Thorp,et al.  State Estimlatjon with Phasor Measurements , 1986, IEEE Transactions on Power Systems.

[9]  F Aminifar,et al.  Probabilistic Multistage PMU Placement in Electric Power Systems , 2011, IEEE Transactions on Power Delivery.

[10]  J.F. Hauer,et al.  Performance of "WAMS East" in providing dynamic information for the North East blackout of August 14, 2003 , 2004, IEEE Power Engineering Society General Meeting, 2004..

[11]  B. Gou,et al.  Generalized Integer Linear Programming Formulation for Optimal PMU Placement , 2008, IEEE Transactions on Power Systems.

[12]  M. Fotuhi-Firuzabad,et al.  Optimal Placement of Phasor Measurement Units Using Immunity Genetic Algorithm , 2009, IEEE Transactions on Power Delivery.

[13]  A.G. Phadke,et al.  Phasor measurement unit placement techniques for complete and incomplete observability , 2005, IEEE Transactions on Power Delivery.

[14]  K. R. Padiyar,et al.  ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY , 1990 .

[15]  M. Hurtgen,et al.  Advantages of power system state estimation using Phasor Measurement Units , 2008 .

[16]  J. Thorp,et al.  State Estimation with Phasor Measurements , 1986, IEEE Power Engineering Review.

[17]  Narayana Prasad Padhy,et al.  Comparison of Particle Swarm Optimization and Genetic Algorithm for TCSC-based Controller Design , 2007 .

[18]  Ali Mohammad Ranjbar,et al.  Optimal PMU Placement by an Equivalent Linear Formulation for Exhaustive Search , 2012, IEEE Transactions on Smart Grid.

[19]  J.-A. Jiang,et al.  Transmission network fault location observability with minimal PMU placement , 2006, IEEE Transactions on Power Delivery.

[20]  S. Premrudeepreechacharn,et al.  An Optimal PMU Placement Method Against Measurement Loss and Branch Outage , 2007, IEEE Transactions on Power Delivery.

[21]  Arun G. Phadke,et al.  Synchronized Phasor Measurements and Their Applications , 2008 .

[22]  P. S. Georgilakis,et al.  Taxonomy of PMU Placement Methodologies , 2012, IEEE Transactions on Power Systems.

[23]  M. Fotuhi-Firuzabad,et al.  Optimal PMU Placement Based on Probabilistic Cost/Benefit Analysis , 2013, IEEE Transactions on Power Systems.

[24]  A.G. Phadke,et al.  Synchronized phasor measurements in power systems , 1993, IEEE Computer Applications in Power.

[25]  M. Begovic,et al.  Nondominated Sorting Genetic Algorithm for Optimal Phasor Maesurement Placement , 2002 .

[26]  E. Kyriakides,et al.  Optimal Placement of Phasor Measurement Units for Power System Observability , 2008, IEEE Transactions on Power Systems.

[27]  Ali Abur,et al.  Placement of PMUs with channel limits , 2009, 2009 IEEE Power & Energy Society General Meeting.

[28]  Bo Wang,et al.  An Improved Ant Colony System in Optimizing Power System PMU Placement Problem , 2009, 2009 Asia-Pacific Power and Energy Engineering Conference.

[29]  A. Abur,et al.  Enhanced Topology Error Processing via Optimal Measurement Design , 2008, IEEE Transactions on Power Systems.

[30]  Z. Chen,et al.  Challenges of Danish power system and their possible solutions , 2012, 2012 IEEE International Conference on Power System Technology (POWERCON).

[31]  S.A. Soman,et al.  Optimal Multistage Scheduling of PMU Placement: An ILP Approach , 2008, IEEE Transactions on Power Delivery.

[32]  Vittal S. Rao,et al.  Optimal placement of PMUs with limited number of channels , 2011, 2011 North American Power Symposium.

[33]  Jean Claude Maun.  Adv antages of power system state estimation using Phasor Measurement Units , 2008 .

[34]  Elham B. Makram,et al.  Optimal PMU placement considering number of analog channels , 2011, 2011 North American Power Symposium.

[35]  T. Baldwin,et al.  Power system observability with minimal phasor measurement placement , 1993 .

[36]  J. Thorp,et al.  Real Time Voltage-Phasor Measurements for Static State Estimation , 1985, IEEE Power Engineering Review.

[37]  Babak Mozafari,et al.  Optimal placement of PMUs to maintain network observability using a modified BPSO algorithm , 2011 .

[38]  Antonio J. Conejo,et al.  Participation factor approach for phasor measurement unit placement in power system state estimation , 2012 .

[39]  Demetrios G. Eliades,et al.  Placement of Synchronized Measurements for Power System Observability , 2009, IEEE Transactions on Power Delivery.

[40]  T.G. Habetler,et al.  Comparison of Particle Swarm Optimization and Genetic Algorithm in the design of permanent magnet motors , 2009, 2009 IEEE 6th International Power Electronics and Motion Control Conference.