A Modified Genetic Based Technique for Solving the Power System State Estimation Problem
Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.
[1] Gu J., Clements K., Krumpholz G., Davis P., "The Solution of ill
conditioned Power System State Estimation Problems via the Method of
Peters and Wilkinson". Power Industry Computer Applications
Conference Proceedings, Houston, May 1983, pp.239-246.
[2] Schweppe F.C. and Wildes J., "Power System Static-State Estimation,
Part I: Exact Model", IEEE Transactions on Power Apparatus and
Systems, Vol. PAS-89, January 1970, pp. 120-125.
[3] Schweppe F.C. and Rom D.B., "Power System Static-State Estimation,
Part II: Approximate Model", IEEE Transactions on Power Apparatus
and Systems, Vol. PAS-89, January 1970, pp.125-130.
[4] Schweppe F.C., "Power System Static-State Estimation, Part III:
Implementation", IEEE Transactions on Power Apparatus and Systems,
Vol. PAS-89, January 1970, pp. 130-135.
[5] Emtethal N.Abdallah, Amr A.Ghazala and Norhan Hanafy,"Power
System State Estimation Using Genetic Algorithms", Proceedings of the
tenth middle east power systems conference, December 2005,pp.669-
676.
[6] A. Abur and A. G. Exposito, "Power System State EstimationÔÇöTheory
and Implementations", New York: Marcel Dekker, 2004, p.37.
[1] Gu J., Clements K., Krumpholz G., Davis P., "The Solution of ill
conditioned Power System State Estimation Problems via the Method of
Peters and Wilkinson". Power Industry Computer Applications
Conference Proceedings, Houston, May 1983, pp.239-246.
[2] Schweppe F.C. and Wildes J., "Power System Static-State Estimation,
Part I: Exact Model", IEEE Transactions on Power Apparatus and
Systems, Vol. PAS-89, January 1970, pp. 120-125.
[3] Schweppe F.C. and Rom D.B., "Power System Static-State Estimation,
Part II: Approximate Model", IEEE Transactions on Power Apparatus
and Systems, Vol. PAS-89, January 1970, pp.125-130.
[4] Schweppe F.C., "Power System Static-State Estimation, Part III:
Implementation", IEEE Transactions on Power Apparatus and Systems,
Vol. PAS-89, January 1970, pp. 130-135.
[5] Emtethal N.Abdallah, Amr A.Ghazala and Norhan Hanafy,"Power
System State Estimation Using Genetic Algorithms", Proceedings of the
tenth middle east power systems conference, December 2005,pp.669-
676.
[6] A. Abur and A. G. Exposito, "Power System State EstimationÔÇöTheory
and Implementations", New York: Marcel Dekker, 2004, p.37.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59332", author = "A. A. Hossam-Eldin and E. N. Abdallah and M. S. El-Nozahy", title = "A Modified Genetic Based Technique for Solving the Power System State Estimation Problem", abstract = "Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.", keywords = "Genetic algorithms, ill-conditioning, state
estimation, weighted least squares.", volume = "3", number = "7", pages = "1454-10", }