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State Estimation in Smart Power Grids

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Smart Power Grids 2011

Part of the book series: Power Systems ((POWSYS))

Abstract

In this chapter, the role of State Estimation (SE) in smart power grids is presented. The trend of SE error with respect to the increasing of the smart grids implementation investigated. The observability analysis as a prior task of SE is demonstrated and an analytical method to consider the impedance values of the branches is developed and discussed by examples. Since most principles of smart power grids are appropriate to distribution networks, the Distribution SE (DSE) considering load correlation is argued and illustrated by an example. The main features of smart grid SE, which is here named as “Smart Distributed SE” (SDSE), are discussed. Some characteristics of proposed SDES are distributed, hybrid, multi-micro grid and islanding support, Harmonic State Estimation (HSE), observability analysis and restore, error processing, and network parameter estimation. Distribution HSE (DHSE) and meter placement for SDSE are also presented.

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References

  1. Abur, A.: A bad data identification method for linear programming state estimation. IEEE Transactions on Power Systems 5, 894–901 (1990)

    Article  Google Scholar 

  2. Abur, A., Exposito, A.G.: Power System State Estimation Theory and Implementation. Marcel Dekker Inc., New York (2004)

    Book  Google Scholar 

  3. Abur, A., Keyhani, A., Bakhtiari, H.: Autoregressive filters for the identification and replacement of bad data in power system state estimation. IEEE Transactions on Power Systems 2, 552–558 (1987)

    Article  Google Scholar 

  4. Abur, A., Magnago, F.H.: Optimal meter placement for maintaining observability during single branch outages. IEEE Transactions on Power Systems 14, 1273–1278 (1999)

    Article  Google Scholar 

  5. Ahmadi, A., Alinejad-Beromi, Y., Moradi, M.: Optimal PMU placement for power system observability using binary particle swarm optimization and considering measurement redundancy. Expert Systems with Applications 38, 7263–7269 (2011)

    Article  Google Scholar 

  6. Amin, M.: Challenges in reliability, security, efficiency, and resilience of energy infrastructure: Toward smart self-healing electric power grid. In: IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, pp. 1–5 (2008)

    Google Scholar 

  7. Aminifar, F., Fotuhi-Firuzabad, M., Shahidehpour, M., et al.: Probabilistic multistage PMU placement in electric power systems. IEEE Transactions on Power Delivery, 1-1 (2010)

    Google Scholar 

  8. Arefi, A., Haghifam, M.R., Fathi, S.H.: Observability analysis of electric networks considering branch impedance. International Journal of Electrical Power & Energy Systems (forthcoming 2011)

    Google Scholar 

  9. Arefi, A., Haghifam, M.R., Fathi, S.H., et al.: A novel algorithm based on Honey Bee Mating Optimization for distribution harmonic state estimation including distributed generators. In: IEEE Power Tech., Bucharest, pp. 1–7 (2009)

    Google Scholar 

  10. Arruda, E.F., Kagan, N., Ribeiro, P.F.: Three-phase harmonic distortion state estimation algorithm based on evolutionary strategies. Electric Power Systems Research 80, 1024 (2010)

    Article  Google Scholar 

  11. Bei, G., Abur, A.: An improved measurement placement algorithm for network observability. IEEE Transactions on Power Systems 16, 819–824 (2001)

    Article  Google Scholar 

  12. Bernieri, A., Betta, G., Liguori, C., et al.: Neural networks and pseudo-measurements for real-time monitoring of distribution systems. IEEE Transactions on Instrumentation and Measurement 45, 645–650 (1996)

    Article  Google Scholar 

  13. Bi, T.S., Qin, X.H., Yang, Q.X.: A novel hybrid state estimator for including synchronized phasor measurements. Electric Power Systems Research 78, 1343–1352 (2008)

    Article  Google Scholar 

  14. Borghetti, A., Nucci, C.A., Paolone, M., et al.: Synchronized phasors monitoring during the islanding maneuver of an active distribution network. IEEE Transactions on Smart Grid 2, 70–79 (2011)

    Article  Google Scholar 

  15. Bose, A.: Smart transmission grid applications and their supporting infrastructure. IEEE Transactions on Smart Grid 1, 11–19 (2010)

    Article  Google Scholar 

  16. Caro, E., Conejo, A.J., Minguez, R.: Power system state estimation considering measurement dependencies. IEEE Transactions on Power Systems 24, 1875–1885 (2009)

    Article  Google Scholar 

  17. Castillo, E., Conejo, A.J., Pruneda, R.E., et al.: Observability analysis in state estimation: a unified numerical approach. IEEE Transactions on Power Systems 21, 877–886 (2006)

    Article  Google Scholar 

  18. Castillo, E., Conejo, A.J., Pruneda, R.E., et al.: State estimation observability based on the null space of the measurement jacobian matrix. IEEE Transactions on Power Systems 20, 1656–1658 (2005)

    Article  Google Scholar 

  19. Chicco, G., Ilie, I.S.: Support vector clustering of electrical load pattern data. IEEE Transactions on Power Systems 24, 1619–1628 (2009)

    Article  Google Scholar 

  20. Chowdhury S.P., Crossley P., Chowdhury S.: Microgrids and active distribution networks. The Institution of Engineering and Technology, London (2009)

    Google Scholar 

  21. Clement-Nyns, K., Haesen, E., Driesen, J.: The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Transactions on Power Systems 25, 371–380 (2010)

    Article  Google Scholar 

  22. Clements, K.A., Krumpholz, G.R., Davis, P.W.: Power system state estimation with measurement deficiency: an algorithm that determines the maximal observable subnetwork. IEEE Transactions on Power Apparatus and Systems, PAS-101, 3044–3052 (1982)

    Article  Google Scholar 

  23. Clements, K.A., Krumpholz, G.R., Davis, P.W.: Power system state estimation with measurement deficiency: an observability/measurement placement algorithm. IEEE Power Engineering Review, PER-3 , 28–28 (1983)

    Article  Google Scholar 

  24. Conejo, A.J., De La Torre, S., Canas, M.: An optimization approach to multiarea state estimation. IEEE Transactions on Power Systems 22, 213–221 (2007)

    Article  Google Scholar 

  25. Contaxis, G.C., Korres, G.N.: A reduced model for power system observability: analysis and restoration. IEEE Transactions on Power Systems 3, 1411–1417 (1988)

    Article  Google Scholar 

  26. D’antona, G., Muscas, C., Sulis, S.: State estimation for the localization of harmonic sources in electric distribution systems. IEEE Transactions on Instrumentation and Measurement 58, 1462–1470 (2009)

    Article  Google Scholar 

  27. De Almeida, M.C., Asada, E.N., Garcia, A.V.: On the use of gram matrix in observability analysis. IEEE Transactions on Power Systems 23, 249–251 (2008)

    Article  Google Scholar 

  28. De Almeida, M.C., Asada, E.N., Garcia, A.V.: Power system observability analysis based on gram matrix and minimum norm solution. IEEE Transactions on Power Systems 23, 1611–1618 (2008)

    Article  Google Scholar 

  29. De Arruda, E.F., Kagan, N., Ribeiro, P.F.: Harmonic distortion state estimation using an evolutionary strategy. IEEE Transactions on Power Delivery 25, 831–842 (2010)

    Article  Google Scholar 

  30. De La Ree, J., Centeno, V., Thorp, J.S., et al.: Synchronized phasor measurement applications in power systems. IEEE Transactions on Smart Grid 1, 20–27 (2010)

    Article  Google Scholar 

  31. Ding, Q., Emesih, V.A.: A simple factorization-based observability analysis and meter placement method. International Journal of Electrical Power & Energy Systems 29, 731 (2007)

    Article  Google Scholar 

  32. Djapic, P., Ramsay, C., Pudjianto, D., et al.: Taking an active approach. IEEE Power and Energy Magazine 5, 68–77 (2007)

    Article  Google Scholar 

  33. Dugan, R.C., Arritt, R.F., Mcdermott, T.E., et al.: Distribution system analysis to support the smart grid. In: IEEE Power and Energy Society General Meeting, pp. 1–8 (2010)

    Google Scholar 

  34. El-Keib, A.A., Singh, H.: Fast linear programming state estimation using the dual formulation. IEEE Transactions on Power Systems 7, 620–628 (1992)

    Article  Google Scholar 

  35. El-Zonkoly, A.: Optimal meter placement using genetic algorithm to maintain network observability. Expert Systems with Applications 31, 193–198 (2006)

    Article  Google Scholar 

  36. Falcao, D.M., Arias, M.A.: State estimation and observability analysis based on echelon forms of the linearized measurement models. IEEE Transactions on Power Systems 9, 979–987 (1994)

    Article  Google Scholar 

  37. Garcia, A., Monticelli, A., Abreu, P.: Fast Decoupled State Estimation and Bad Data Processing. IEEE Transactions on Power Apparatus and Systems, PAS-98, 1645–1652 (1979)

    Article  Google Scholar 

  38. Gomez-Exposito, A., Abur, A.: Generalized observability analysis and measurement classification. IEEE Transactions on Power Systems 13, 1090–1095 (1998)

    Article  Google Scholar 

  39. Gomez-Exposito, A., De La Villa Jaen, A.: Two-level state estimation with local measurement pre-processing. IEEE Transactions on Power Systems 24, 676–684 (2009)

    Article  Google Scholar 

  40. Gou, B.: Jacobian matrix-based observability analysis for state estimation. IEEE Transactions on Power Systems 21, 348–356 (2006)

    Article  Google Scholar 

  41. Gou, B., Abur, A.: A direct numerical method for observability analysis. IEEE Transactions on Power Systems 15, 625–630 (2000)

    Article  Google Scholar 

  42. Gu, I.Y.H., Bollen, M.H.J.: Estimating Interharmonics by Using Sliding-Window ESPRIT. IEEE Transactions on Power Delivery 23, 13–23 (2008)

    Article  Google Scholar 

  43. Habiballah, I.O., Irving, M.R.: Observability analysis for state estimation using linear programming. IEEE Proceedings of Generation, Transmission and Distribution 148, 142–145 (2001)

    Article  Google Scholar 

  44. Hajian, M., Ranjbar, A.M., Amraee, T., et al.: Optimal placement of PMUs to maintain network observability using a modified BPSO algorithm. International Journal of Electrical Power & Energy Systems 33, 28 (2011)

    Article  Google Scholar 

  45. Harris, A.: Smart grid thinking-(power super grid). Engineering & Technology Magazine 4, 46–49 (2009)

    Google Scholar 

  46. Heydt, G.T.: The next generation of power distribution systems. IEEE Transactions on Smart Grid 1, 225–235 (2010)

    Article  Google Scholar 

  47. Horisberger, H.P., Richard, J.C., Rossier, C.: A fast decoupled static state-estimator for electric power systems. IEEE Transactions on Power Apparatus and Systems 95, 208–215 (1976)

    Article  Google Scholar 

  48. Hurtgen, M., Maun, J.C.: Optimal PMU placement using Iterated Local Search. International Journal of Electrical Power & Energy Systems 32, 857 (2010)

    Article  Google Scholar 

  49. Irving, M.R.: Robust algorithm for generalized state estimation. IEEE Transactions on Power Systems 24, 1886–1887 (2009)

    Article  Google Scholar 

  50. Irving, M.R., Owen, R.C., Sterling, M.J.H.: Power-system state estimation using linear programming. Proceedings of the Institution of Electrical Engineers 125, 879–885 (1978)

    Article  Google Scholar 

  51. Iso-New-England: Overview of the Smart Grid—Policies, Initiatives, and Needs. In: ISO New England Inc., p. 50 (February 17, 2009 )

    Google Scholar 

  52. Jabr, R.A., Pal, B.C.: AC network state estimation using linear measurement functions. IET Generation, Transmission & Distribution 2, 1–6 (2008)

    Article  Google Scholar 

  53. Jabr, R.A., Pal, B.C.: Iteratively reweighted least-squares implementation of the WLAV state-estimation method. IEEE Proceedings of Generation, Transmission and Distribution 151, 103–108 (2004)

    Article  Google Scholar 

  54. Jen-Hao, T.: A direct approach for distribution system load flow solutions. IEEE Transactions on Power Delivery 18, 882–887 (2003)

    Article  Google Scholar 

  55. Jian, C., Abur, A.: Enhanced topology error processing via optimal measurement design. IEEE Transactions on Power Systems 23, 845–852 (2008)

    Article  Google Scholar 

  56. Jian, C., Abur, A.: Placement of PMUs to enable bad data detection in state estimation. IEEE Transactions on Power Systems 21, 1608–1615 (2006)

    Article  Google Scholar 

  57. Jim, S., Carr, W., Collier, S.E.: Real time distribution analysis for electric utilities. In: IEEE Rural Electric Power Conference, pp (B5-1)–(B5-8) (2008)

    Google Scholar 

  58. Jiyuan, F., Borlase, S.: The evolution of distribution. IEEE Power and Energy Magazine 7, 63–68 (2009)

    Article  Google Scholar 

  59. Korres, G.N., Hatziargyriou, N.D., Katsikas, Pj.: State estimation in Multi-Microgrids. European Transactions on Electrical Power (2010) doi:10.1002/etep.442

    Google Scholar 

  60. Korres, G.N.: A distributed multiarea state estimation. IEEE Transactions on Power Systems 26, 73–84 (2011)

    Article  Google Scholar 

  61. Korres, G.N.: A robust method for equality constrained state estimation. IEEE Transactions on Power Systems 17, 305–314 (2002)

    Article  Google Scholar 

  62. Korres, G.N., Katsikas, P.J.: A hybrid method for observability analysis using a reduced network graph theory. IEEE Transactions on Power Systems 18, 295–304 (2003)

    Article  Google Scholar 

  63. Korres, G.N., Katsikas, P.J.: Reduced model for numerical observability analysis in generalised state estimation. IEEE Proceedings of Generation, Transmission and Distribution 152, 99–108 (2005)

    Article  Google Scholar 

  64. Korres, G.N., Katsikas, P.J., Clements, K.A., et al.: Numerical observability analysis based on network graph theory. IEEE Transactions on Power Systems 18, 1035–1045 (2003)

    Article  Google Scholar 

  65. Krumpholz, G.R., Clements, K.A., Davis, P.W.: Power system observability: a practical algorithm using network topology. IEEE Transactions on Power Apparatus and Systems, PAS-99, 1534–1542 (1980)

    Article  Google Scholar 

  66. Kulshrestha, P., Lei, W., Mo-Yuen, C., et al.: Intelligent energy management system simulator for PHEVs at municipal parking deck in a smart grid environment. In: IEEE Power & Energy Society General Meeting, pp. 1–6 (2009)

    Google Scholar 

  67. Lakshminarasimhan, S., Agirgis, A.: Hierarchical state estimation applied to wide-area power systems. In: IEEE Power Engineering Society General Meeting, Tampa, FL, pp. 1–6 (2007)

    Google Scholar 

  68. Larson, R.E., Tinney, W.F., Hajdu, L.P., et al.: State Estimation in Power Systems Part II: Implementation and Applications. IEEE Transactions on Power Apparatus and Systems, PAS-89, 353–363 (1970)

    Article  Google Scholar 

  69. Larson, R.E., Tinney, W.F., Peschon, J.: State Estimation in Power Systems Part I: Theory and Feasibility. IEEE Transactions on Power Apparatus and Systems, PAS-89, 345–352 (1970)

    Article  Google Scholar 

  70. Lee, K.Y., Ma, E.-S.: Modern heuristic optimization techniques, theory and applications to power systems. John Wiley & Sons, Inc., IEEE Press, Hoboken, New Jersey (2008)

    Google Scholar 

  71. Liang, Z., Abur, A.: Multi area state estimation using synchronized phasor measurements. IEEE Transactions on Power Systems 20, 611–617 (2005)

    Article  Google Scholar 

  72. Liao, H.: Power system harmonic state estimation and observability analysis via sparsity maximization. IEEE Transactions on Power Systems 22, 15–23 (2007)

    Article  Google Scholar 

  73. Lin, W.M., Teng, J.H.: Distribution fast decoupled state estimation by measurement pairing. IEEE Proceedings- Generation, Transmission and Distribution 143, 43–48 (1996)

    Article  Google Scholar 

  74. Lobos, T., Kozina, T., Koglin, H.J.: Power system harmonics estimation using linear least squares method and SVD. In: IEEE Proceedings of Generation, Transmission and Distribution, vol. 148, pp. 567–572 (2001)

    Google Scholar 

  75. Lourenco, E.M., Costa, A.J.S., Clements, K.A., et al.: A topology error identification method directly based on collinearity tests. IEEE Transactions on Power Systems 21, 1920–1929 (2006)

    Article  Google Scholar 

  76. Lu, Z., Ji, T.Y., Tang, W.H., et al.: Optimal harmonic estimation using a particle swarm optimizer. IEEE Transactions on Power Delivery 23, 1166–1174 (2008)

    Article  Google Scholar 

  77. Madureira, A., Pereira, J., Gil, N., et al.: Advanced control and management functionalities for multi-microgrids. European Transactions on Electrical Power, doi:10.1002/etep.407

    Google Scholar 

  78. Magnago, F.H., Abur, A.: A unified approach to robust meter placement against loss of measurements and branch outages. IEEE Transactions on Power Systems 15, 945–949 (2000)

    Article  Google Scholar 

  79. Manitsas, E., Singh, R., Pal, B., et al.: Modelling of pseudo-measurements for distribution system state estimation. In: CIRED Seminar, SmartGrids for Distribution, pp. 1–4 (2008)

    Google Scholar 

  80. Meliopoulos, A.P.S., Fan, Z., Zelingher, S.: Power system harmonic state estimation. IEEE Transactions on Power Delivery 9, 1701–1709 (1994)

    Article  Google Scholar 

  81. Meyer, C.D.: Matrix analysis and applied linear algebra. SIAM Publisher, Philadelphia (2000)

    Book  MATH  Google Scholar 

  82. Monticelli, A., Garcia, A.: Fast decoupled state estimators. IEEE Transactions on Power Systems 5, 556–564 (1990)

    Article  Google Scholar 

  83. Monticelli, A., Wu, F.F.: Network observability: identification of observable islands and measurement placement. IEEE Transactions on Power Apparatus and Systems PAS-104, 1035–1041 (1985)

    Article  Google Scholar 

  84. Monticelli, A., Wu, F.F.: Network observability: theory. IEEE Power Engineering Review, PER-5, 32–33 (1985)

    Google Scholar 

  85. Monticelli, A., Wu, F.F.: Observability analysis for orthogonal transformation based state estimation. IEEE Transactions on Power Systems 1, 201–206 (1986)

    Article  Google Scholar 

  86. Mori, H., Tsuzuki, S.: A fast method for topological observability analysis using a minimum spanning tree technique. IEEE Transactions on Power Systems 6, 491–500 (1991)

    Article  Google Scholar 

  87. Muscas, C., Pilo, F., Pisano, G., et al.: Optimal allocation of multichannel measurement devices for distribution state estimation. IEEE Transactions on Instrumentation and Measurement 58, 1929–1937 (2009)

    Article  Google Scholar 

  88. Naka, S., Genji, T., Yura, T., et al.: A hybrid particle swarm optimization for distribution state estimation. IEEE Transactions on Power Systems 18, 60–68 (2003)

    Article  Google Scholar 

  89. Nucera, R.R., Brandwajn, V., Gilles, M.L.: Observability and bad data analysis using augmented blocked matrices (power system analysis computing). IEEE Transactions on Power Systems 8, 426–433 (1993)

    Article  Google Scholar 

  90. Nucera, R.R., Gilles, M.L.: Observability analysis: a new topological algorithm. IEEE Transactions on Power Systems 6, 466–475 (1991)

    Article  Google Scholar 

  91. Paolone, M., Borghetti, A., Nucci, C.A.: Development of an RTU for synchrophasors estimation in active distribution networks. In: IEEE Power Tech., Bucharest, pp. 1–6 (2009)

    Google Scholar 

  92. Pei, Z., Fangxing, L., Bhatt, N.: Next-generation monitoring, analysis, and control for the future smart control center. IEEE Transactions on Smart Grid 1, 186–192 (2010)

    Article  Google Scholar 

  93. Peng, C., Sun, H., Guo, J.: Multi-objective optimal PMU placement using a non-dominated sorting differential evolution algorithm. International Journal of Electrical Power & Energy Systems 32, 886–892 (2010)

    Article  Google Scholar 

  94. Peng, C., Sun, H., Guo, J.: Multi-objective optimal PMU placement using a non-dominated sorting differential evolution algorithm. International Journal of Electrical Power & Energy Systems 32, 886 (2010)

    Article  Google Scholar 

  95. Phadke, A.G., Thorp, J.S.: Synchronized phasor measurements and their applications. Springer Science, Heidelberg (2008)

    Google Scholar 

  96. Pilo, F., Pisano, G., Soma, G.G.: Robust distribution state estimation for active networks. In: 43rd International Conference on Universities Power Engineering,UPEC 2008, pp. 1–6 (2008)

    Google Scholar 

  97. Pires, R.C., Simoes Costa, A., Mili, L.: Iteratively reweighted least-squares state estimation through Givens Rotations. IEEE Transactions on Power Systems 14, 1499–1507 (1999)

    Article  Google Scholar 

  98. Podmore, R., Robinson, M.R.: The role of simulators for smart grid development. IEEE Transactions on Smart Grid 1, 205–212 (2010)

    Article  Google Scholar 

  99. Pruneda, R.E., Solares, C., Conejo, A.J., et al.: An efficient algebraic approach to observability analysis in state estimation. Electric Power Systems Research 80, 277–286 (2010)

    Article  Google Scholar 

  100. Quintana, V.H., Simoes-Costa, A., Mandel, A.: Power system topological observability using a direct graph-theoretic approach. IEEE Transactions on Power Apparatus and Systems, PAS-101, 617–626 (1982)

    Article  Google Scholar 

  101. Ramesh, L., Choudhury, S.P., Chowdhury, S., et al.: Electrical power system state estimation meter placement—a comparative survey report. Electric Power Components and Systems 36, 1115–1129 (2008)

    Article  Google Scholar 

  102. Ramesh, L., Chowdhury, S.P., Chowdhury, S., et al.: Distributed state estimation technique for active distribution networks. In: 42nd International Conference on Universities Power Engineering, UPEC 2007, pp. 861–866 (2007)

    Google Scholar 

  103. Roytelman, I., Landenberger, V.: Real-time distribution system analysis - integral part of DMS. In: IEEE/PES Power Systems Conference and Exposition, PSCE 2009, pp. 1–6 (2009)

    Google Scholar 

  104. Rubinstein, R., Kroese, D.: Simulation and the monte carlo method. John Wiley & Sons Inc., Hoboken (2008)

    MATH  Google Scholar 

  105. Russell, B.D., Benner, C.L.: Intelligent systems for improved reliability and failure diagnosis in distribution systems. IEEE Transactions on Smart Grid 1, 48–56 (2010)

    Article  Google Scholar 

  106. Sainz, L., Mesas, J.J., Teodorescu, R., et al.: Deterministic and stochastic study of wind farm harmonic currents. IEEE Transactions on Energy Conversion 25, 1071–1080 (2010)

    Article  Google Scholar 

  107. Sakis Meliopoulos, A.P., Cokkinides, G., Huang, R., et al.: Smart grid technologies for autonomous operation and control. IEEE Transactions on Smart Grid 2, 1–10 (2011)

    Article  Google Scholar 

  108. Sakis Meliopoulos, A.P., Fan, Z.: Multiphase power flow and state estimation for power distribution systems. IEEE Transactions on Power Systems 11, 939–946 (1996)

    Article  Google Scholar 

  109. Saric, A.T., Ciric, R.M.: Integrated fuzzy state estimation and load flow analysis in distribution networks. IEEE Transactions on Power Delivery 18, 571–578 (2003)

    Article  Google Scholar 

  110. Schweppe, F.C.: Power System Static-State Estimation, Part III: Implementation. IEEE Transactions on Power Apparatus and Systems, PAS-89, 130–135 (1970)

    Article  Google Scholar 

  111. Schweppe, F.C., Rom, D.B.: Power System Static-State Estimation, Part II: Approximate Model. IEEE Transactions on Power Apparatus and Systems, PAS-89, 125–130 (1970)

    Article  Google Scholar 

  112. Schweppe, F.C., Wildes, J.: Power System Static-State Estimation, Part I: Exact Model. IEEE Transactions on Power Apparatus and Systems, PAS-89, 120–125 (1970)

    Article  Google Scholar 

  113. Sebastian, M., Devaux, O., Huet, O.: Description and benefits of a situation awareness tool based on a distribution state estimator and adapted to smart grids. In: CIRED Seminar, SmartGrids for Distribution, pp. 1–4 (2008)

    Google Scholar 

  114. Shahidehpour, M., Wang, Y.: Communication and control in electric power systems, applications of parallel and distributed processing. John Wiley & Sons Inc., Hoboken (2003)

    Google Scholar 

  115. Shan, Z., Abur, A.: Combined state estimation and measurement calibration. IEEE Transactions on Power Systems 20, 458–465 (2005)

    Article  Google Scholar 

  116. Singh, R., Pal, B.C., Jabr, R.A.: Choice of estimator for distribution system state estimation. IET Generation, Transmission & Distribution 3, 666–678 (2009)

    Article  Google Scholar 

  117. Singh, R., Pal, B.C., Jabr, R.A.: Distribution system state estimation through Gaussian mixture model of the load as pseudo-measurement. IET Generation, Transmission & Distribution 4, 50–59 (2010)

    Article  Google Scholar 

  118. Slutsker, I.W., Scudder, J.M.: Network Observability Analysis through Measurement Jacobian Matrix Reduction. IEEE Transactions on Power Systems 2, 331–336 (1987)

    Article  Google Scholar 

  119. Smith, M.M., Powell, R.S., Irving, M.R., et al.: Robust algorithm for state estimation in electrical networks. IEEE Proceedings of Generation, Transmission and Distribution C 138, 283–288 (1991)

    Article  Google Scholar 

  120. Sodhi, R., Srivastava, S.C., Singh, S.N.: Multi-criteria decision-making approach for multistage optimal placement of phasor measurement units. IET Generation, Transmission & Distribution 5, 181–190 (2011)

    Article  Google Scholar 

  121. Solares, C., Conejo, A.J., Castillo, E., et al.: Binary-arithmetic approach to observability checking in state estimation. IET Generation, Transmission & Distribution 3, 336–345 (2009)

    Article  Google Scholar 

  122. Tavanir: National metering reports. Iran Power Generation, Transmission and Distribution Management Company (2010), http://www.tavanir.org.ir (accessed, 2004)

  123. Teng, J.H.: Using voltage measurements to improve the results of branch-current-based state estimators for distribution systems. IEEE Proceedings- Generation, Transmission and Distribution 149, 667–672 (2002)

    Article  Google Scholar 

  124. Terzija, V.V., Stanojevic, V.: STLS Algorithm for Power-Quality Indices Estimation. IEEE Transactions on Power Delivery 23, 544–552 (2008)

    Article  Google Scholar 

  125. Thukaram, D., Jerome, J., Surapong, C.: A robust three-phase state estimation algorithm for distribution networks. Electric Power Systems Research 55, 191–200 (2000)

    Article  Google Scholar 

  126. Valverde, G., Chakrabarti, S., Kyriakides, E., et al.: A constrained formulation for hybrid state estimation. IEEE Transactions on Forthcoming Power Systems (forthcoming 2010)

    Google Scholar 

  127. Vandoorn, T.L., Renders, B., Degroote, L., et al.: Active load control in islanded microgrids based on the grid voltage. IEEE Transactions on Smart Grid 2, 127–139 (2011)

    Article  Google Scholar 

  128. Watson, N.R., Arrillage, J., Du, Z.P.: Modified symbolic observability for harmonic state estimation. IEEE Proceedings of Generation, Transmission and Distribution 147, 105–111 (2000)

    Article  Google Scholar 

  129. Whei-Min, L., Jen-Hao, T., Shi-Jaw, C.: A highly efficient algorithm in treating current measurements for the branch-current-based distribution state estimation. IEEE Transactions on Power Delivery 16, 433–439 (2001)

    Article  Google Scholar 

  130. Wu, F.F., Liu, W.H.E., Holten, L., et al.: Observability analysis and bad data processing for state estimation using Hachtel’s augmented matrix method. IEEE Transactions on Power Systems 3, 604–611 (1988)

    Article  Google Scholar 

  131. Wu, F.F., Liu, W.H.E., Lun, S.M.: Observability analysis and bad data processing for state estimation with equality constraints. IEEE Transactions on Power Systems 3, 541–548 (1988)

    Article  Google Scholar 

  132. Youman, D., Ying, H., Boming, Z.: A branch-estimation-based state estimation method for radial distribution systems. IEEE Transactions on Power Delivery 17, 1057–1062 (2002)

    Article  Google Scholar 

  133. Yu, K.K.C., Watson, N.R., Arrillaga, J.: An adaptive Kalman filter for dynamic harmonic state estimation and harmonic injection tracking. IEEE Transactions on Power Delivery 20, 1577–1584 (2005)

    Article  Google Scholar 

  134. Zhu, J., Abur, A., Rice, M. et al.: Enhanced state estimators. Power Systems Engineering Research Center (2006) , http://www.pserc.wisc.edu/documents/publications/reports/2006_reports/abur_state_estimators_s22_reports.pdf (accessed November 2006)

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Authors and Affiliations

  1. Electric Transmission & Distribution Laboratory, Department of Electrical and Computer Engineering, Tarbiat Modares University, P.O. Box: 14115-139, Tehran, Iran

    Ali Arefi & Mahmood-Reza Haghifam

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  1. Ali Arefi
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  2. Mahmood-Reza Haghifam
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Correspondence to Ali Arefi .

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Editors and Affiliations

  1. Dept. Electrical & Computer Engineering, Ohio State University, Neil Avenue 2015, Columbus, 43210, Ohio, USA

    Ali Keyhani

  2. 7 Marian Lane, Loundonville, 12211, New York, USA

    Muhammad Marwali

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Arefi, A., Haghifam, MR. (2012). State Estimation in Smart Power Grids. In: Keyhani, A., Marwali, M. (eds) Smart Power Grids 2011. Power Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21578-0_14

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  • DOI: https://doi.org/10.1007/978-3-642-21578-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21577-3

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