Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review

Phasor measurement unit (PMU) plays an important role in operation, protection, and control of modern power systems. PMU provides real time, synchronized measurements of bus voltage and branch current phasors. It is neither economical nor possible to place all the buses of the system with PMUs because of their high cost and communication facilities. Attaining the minimal number of PMUs to access an observable power system is the main objective of optimal PMU placement (OPP) problem, which is solved by utilizing different techniques. Graph theoretic and mathematical programming procedures have been first introduced to solve OPP problem, aiming to access power system observability. Heuristic method as an experience-based technique is defined as a quick method for obtaining solutions for optimization problems, in which optimal solutions are not achievable using mathematical methods in finite time. This paper provided the literature review on different heuristic optimization methods to solve the OPP problem. Then, the available methods were classified and compared with different points of views. Results from the tests of researches on heuristic algorithms with and without the consideration of zero-injection buses were compared and superiorities of the introduced heuristic concepts were demonstrated with relative to each other.

[1]  F. J. Marín,et al.  Genetic algorithms for optimal placement of phasor measurement units in electrical networks , 2003 .

[2]  A.G. Phadke,et al.  HISTORY AND APPLICATIONS OF PHASOR MEASUREMENTS , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[3]  Xiaomeng Bian,et al.  Adaptive Clonal Algorithm and Its Application for Optimal PMU Placement , 2006, 2006 International Conference on Communications, Circuits and Systems.

[4]  Behnam Mohammadi-Ivatloo,et al.  Identification of inter‐area oscillations using wavelet transform and phasor measurement unit data , 2015 .

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

[6]  Michaël Hurtgen,et al.  Optimal PMU placement using Iterated Local Search , 2010 .

[7]  Innocent Kamwa,et al.  Wide-area measurement based stabilizing control of large power systems-a decentralized/hierarchical approach , 2001 .

[8]  Li Ying,et al.  Sensitivity Constrained PMU Placement for Complete Observability of Power Systems , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

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

[10]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[11]  Hamid Lesani,et al.  A Multi-Objective PMU Placement Method Considering Measurement Redundancy and Observability Value Under Contingencies , 2013, IEEE Transactions on Power Systems.

[12]  Qi Huan,et al.  Hybrid of MST and Genetic Algorithm on Minimizing PMU Placement , 2013, 2013 Third International Conference on Intelligent System Design and Engineering Applications.

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

[14]  Mohammad Reza Meybodi,et al.  A Self-Organizing Channel Assignment Algorithm: A Cellular Learning Automata Approach , 2003, IDEAL.

[15]  Ying-Hong Lin,et al.  A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-part I: theory and algorithms , 2004 .

[16]  G. Thomas Bellarmine,et al.  Improving observability using optimal placement of phasor measurement units , 2014 .

[17]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[18]  I. Ivankovic,et al.  Applications Based on PMU Technology for Improved Power System Utilization , 2007, 2007 IEEE Power Engineering Society General Meeting.

[19]  K. S. Swarup,et al.  Power system observability Using Biogeography Based Optimization , 2011 .

[20]  Thawatch Kerdchuen and Wecrakorn Ongsakul Optimal Placement of PMU and RTU by Hybrid Genetic Algorithm and Simulated Annealing for Multiarea Power System State Estimation , 2009 .

[21]  Wei Zhao,et al.  Recent advance in energy management optimization for microgrid , 2013, 2013 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia).

[22]  A Yda Amira,et al.  Optimal PMU placement for full network observability case of the tunisian network , 2011, Eighth International Multi-Conference on Systems, Signals & Devices.

[23]  K. Mazlumi,et al.  Optimal placement of PMUs in power systems based on bacterial foraging algorithm , 2010, 2010 18th Iranian Conference on Electrical Engineering.

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

[25]  Heresh Seyedi,et al.  Optimal PMU placement for power system observability using BICA, considering measurement redundancy , 2013 .

[26]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[27]  Ashok Kumar Pradhan,et al.  An optimal PMU placement technique for power system observability , 2012 .

[28]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[29]  James S. Thorp,et al.  Synchronized Phasor Measurement Applications in Power Systems , 2010, IEEE Transactions on Smart Grid.

[30]  Jianfeng Guo,et al.  Multi-objective optimal PMU placement using a non-dominated sorting differential evolution algorithm , 2010 .

[31]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[32]  V. Venkatasubramanian,et al.  New Wide-Area Algorithms for Detection and Mitigation of Angle Instability using Synchrophasors , 2007, 2007 IEEE Power Engineering Society General Meeting.

[33]  K. S. Swarup,et al.  Multi-objective biogeography based optimization for optimal PMU placement , 2012, Appl. Soft Comput..

[34]  A.G. Phadke,et al.  An Alternative for Including Phasor Measurements in State Estimators , 2006, IEEE Transactions on Power Systems.

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

[36]  B. Mohammadi,et al.  Optimal Placement of PMUs for Power System Observability Using Topology Based Formulated Algorithms , 2009 .

[37]  Ying-Hong Lin,et al.  A new PMU-based fault detection/location technique for transmission lines with consideration of arcing fault discrimination-part II: performance evaluation , 2004 .

[38]  Jin Xu,et al.  Optimal PMU placement for wide-area monitoring using chemical reaction optimization , 2013, 2013 IEEE PES Innovative Smart Grid Technologies Conference (ISGT).

[39]  Behnam Mohammadi-Ivatloo,et al.  Online small signal stability analysis of multi-machine systems based on synchronized phasor measurements , 2011 .

[40]  Seema Singh,et al.  Optimal PMU placement method for complete topological and numerical observability of power system , 2010 .

[41]  Yuin-Hong Liu,et al.  A PMU based special protection scheme: a case study of Taiwan power system , 2005 .

[42]  Minyue Fu,et al.  Optimal PMU placement for power system state estimation with random component outages , 2013 .

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

[44]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[45]  S. M. Nosratabadi,et al.  Optimal PMU placement based on Mean Square Error using Differential Evolution algorithm , 2010, 2010 First Power Quality Conferance.

[46]  B. Mohammadi-Ivatloo,et al.  Optimal PMU placement for power system observability considering secondary voltage control , 2008, 2008 Canadian Conference on Electrical and Computer Engineering.

[47]  Franz Franchetti,et al.  An Information-Theoretic Approach to PMU Placement in Electric Power Systems , 2012, IEEE Transactions on Smart Grid.

[48]  Federico Milano,et al.  A security oriented approach to PMU positioning for advanced monitoring of a transmission grid , 2002, Proceedings. International Conference on Power System Technology.

[49]  Chi Su,et al.  Optimal Placement of Phasor Measurement Units with New Considerations , 2010, 2010 Asia-Pacific Power and Energy Engineering Conference.

[50]  Chunhua Peng,et al.  A hybrid algorithm based on BPSO and immune mechanism for PMU optimization placement , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[51]  Chih-Wen Liu,et al.  New methods for computing power system dynamic response for real-time transient stability prediction , 2000 .

[52]  B. Rajasekhar,et al.  Differential evolution based optimal PMU placement for fault observability of power system , 2013, 2013 Students Conference on Engineering and Systems (SCES).

[53]  C. W. Taylor,et al.  Real-Time Transient Stability Prediction - Possibilities for On-Line Automatic Database Generation and Classifier Training , 1995 .

[54]  G. Trudel,et al.  Wide-area monitoring and control at Hydro-Quebec: past, present and future , 2006, 2006 IEEE Power Engineering Society General Meeting.

[55]  Vijay S. Kale,et al.  Optimum PMU placement considering one Line/ One PMU outage and maximum redundancy using genetic algorithm , 2011, The 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011.

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

[57]  A.G. Phadke,et al.  A preprocessing method for effective PMU placement studies , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[58]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[59]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[60]  Ping Ju,et al.  A real-time monitoring method for power system steady state angle stability based on WAMS , 2005, 2005 International Power Engineering Conference.

[61]  N. Eva Wu,et al.  Fault-tolerant placement of phasor measurement units based on control reconfigurability , 2013 .

[62]  Farrokh Aminifar,et al.  Observability of Hybrid AC/DC Power Systems With Variable-Cost PMUs , 2014, IEEE Transactions on Power Delivery.

[63]  Nikolaos M. Manousakis,et al.  Numerical observability method for optimal phasor measurement units placement using recursive Tabu search method , 2013 .

[64]  Y. Alinejad-Beromi,et al.  Optimal PMU placement for power system observability using binary particle swarm optimization and considering measurement redundancy , 2011, Expert Syst. Appl..

[65]  Victor O. K. Li,et al.  Chemical-Reaction-Inspired Metaheuristic for Optimization , 2010, IEEE Transactions on Evolutionary Computation.

[66]  H. Mesgarnejad,et al.  Multi-objective measurement placement with new parallel Tabu Search method , 2008, 2008 IEEE Canada Electric Power Conference.

[67]  A. Kulanthaisamy,et al.  A Multi-objective PMU Placement Method Considering Observability and Measurement Redundancy using ABC Algorithm , 2014 .

[68]  A.G. Phadke,et al.  Recent developments in state estimation with phasor measurements , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[69]  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).

[70]  Mohammad Ali Abido,et al.  Optimal PMU placement for power system observability using differential evolution , 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

[71]  Helena Ramalhinho Dias Lourenço,et al.  Iterated Local Search , 2001, Handbook of Metaheuristics.

[72]  Mohamed A. El-Sharkawi,et al.  Modern heuristic optimization techniques :: theory and applications to power systems , 2008 .

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

[74]  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.