Enhanced GA-Fuzzy OPF under both Normal and Contingent Operation States
The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
[1] D.E. Goldberg, "Genetic Algorithms in Search Optimization and
Machine Learning," Addison Wesley, 1989.
[2] S.A. Kazarlis, S.A. Bakirtzis and V. Petridis, "A Genetic Algorithm
Solution to the Unit Commitment Problem," IEEE Transactions on
Power Systems, Vol. 11, No. 1, Feb 1996, pp. 83-92.
[3] S.R. Paranjothi and K. Anburaja, "Optimal Power Flow using Refined
Genetic Algorithm," Electric Power Components and Systems, Vol.
30, 2002, pp. 1055-1063.
[4] J. Yuryevich and K.P. Wong, "Evolutionary Programming Based
Optimal Power Flow Algorithm," IEEE Transactions on Power
Systems, Vol. 14(4), Nov. 1999, pp. 1245-1250.
[5] A.G. Bakirtzis, P.N. Biskas, E.Z. Christoforos and V. Petridis,
"Optimal Power flow by Enhanced Genetic Algorithm," IEEE
Transactions on Power Systems, Vol. 17, No. 17, May 2002, pp. 229-
236.
[6] S.N. Singh, A. Chandramouli, P.K. Kalra, S.C. Srivastava and D.K.
Mishra, "Optimal Reactive Power Dispatch using Genetic
Algorithms," Proc. Int. Symp. On Electricity Distribution and Energy
Management (ISEDEM 93), Singapore, 1993, pp. 464-469.
[7] K.S. Swarup, M. Yoshimi, S. Shimano and Y. Izni, "Optimization
Methods using Genetic Algorithms for Reactive Power Planning in
Power Systems," Proceedings of 12th PSCC, Dresden, Germeny,
Augest 17-23, 1996, Vol. 1, pp. 483-491.
[8] S.K. Lee, K.M. Son and J.K. Park, "Voltage Profile Optimization
using a Pyramid Genetic Algorithm," Proc. ISAP 97, Seoul, Korea,
July 6-10, 1997, pp. 407-414.
[9] D.C Walters and G.B. Sheble, "Genetic Algorithm Solution of
Economic Dispatch with Valve Point Loading," IEEE Trans. On
Power Systems, Vol. 8, No. 3, 1993, pp.1325-1332.
[10] G.B. Sheble and K. Britigg, "Refined Genetic Algorithm-Economic
Dispatch Example," IEEE Transactions on Power Systems, Vol. 10,
No. 1, Feb. 1995, pp. 117-124.
[11] Po-Hung Chen and Hong-Chan Chang, "Large-Scale Economic
Dispatch by Genetic Algorithm," IEEE Transactions on Power
Systems, Vol. 10, No. 4, Nov. 1995, pp. 1919-1926.
[12] S.O. Orero and M.R. Irving, " A Genetic Algorithm for Generator
Scheduling in Power Systems," International Journal on Electric
Power and Energy Systems, Vol. 18, No. 1, Jan 1996, pp. 19-26.
[13] Chira Achyuthakan, "Genetic Algorithms Applications to Economic
Load Dispatch," Master Thesis, AIT Bangkok, Thailand, August 1997.
[14] J.D. Weber, "Implementation of a Newton-Based Optimal Power Flow
into a Power System Simulation Environment," Master Thesis,
University of Illinois at Urbana-Champain; Urbana-Illinois.
Available from http://energy.ece.uiuc.edu/jamie (1997).
[15] C.A. Roa-Sepulveda, B.J. Pavez-lazo, "A Solution to the Optimal
Power Flow using Simulated Annealing," Electrical Power and
Energy Systems, 25 (2003), pp. 47-57.
[16] M.S. Osman, M.A. Abo-Sinna, A.A. Mousa, "A solution to the
optimal power flow using genetic algorithm," Applied Mathematics
and Computation, Elsevier, Vol. 155, Issue 2, Aug. 6, 2004, pp. 391-
405.
[17] K.Y. Lee, Y.M. Park and J.L. Ortiz, "A United Approach to Optimal
Real and Reactive Power Dispatch," IEEE Trans. on Power Apparatus
and Systems, Vol. PAS-104, No. 5, May 1985, pp. 1147-1153.
[18] L.L. Lai, J.T. Ma, R. Yokoyama and M. Zhao, "Improved Genetic
algorithms for Optimal Power Flow under both normal and contingent
operation states," Electrical Power and Energy Systems, Vol. 19, No.
5, 1997, pp. 287-292.
[19] Ashish Saini, D.K. Chaturvedi and A.K. Saxena, "Optimal Power
Flow Solution: a GA-Fuzzy System Approach," International Jr. of
Emerging Electric Power Systems, Vol. 5, Issue 2, 2006, Article 1.
[1] D.E. Goldberg, "Genetic Algorithms in Search Optimization and
Machine Learning," Addison Wesley, 1989.
[2] S.A. Kazarlis, S.A. Bakirtzis and V. Petridis, "A Genetic Algorithm
Solution to the Unit Commitment Problem," IEEE Transactions on
Power Systems, Vol. 11, No. 1, Feb 1996, pp. 83-92.
[3] S.R. Paranjothi and K. Anburaja, "Optimal Power Flow using Refined
Genetic Algorithm," Electric Power Components and Systems, Vol.
30, 2002, pp. 1055-1063.
[4] J. Yuryevich and K.P. Wong, "Evolutionary Programming Based
Optimal Power Flow Algorithm," IEEE Transactions on Power
Systems, Vol. 14(4), Nov. 1999, pp. 1245-1250.
[5] A.G. Bakirtzis, P.N. Biskas, E.Z. Christoforos and V. Petridis,
"Optimal Power flow by Enhanced Genetic Algorithm," IEEE
Transactions on Power Systems, Vol. 17, No. 17, May 2002, pp. 229-
236.
[6] S.N. Singh, A. Chandramouli, P.K. Kalra, S.C. Srivastava and D.K.
Mishra, "Optimal Reactive Power Dispatch using Genetic
Algorithms," Proc. Int. Symp. On Electricity Distribution and Energy
Management (ISEDEM 93), Singapore, 1993, pp. 464-469.
[7] K.S. Swarup, M. Yoshimi, S. Shimano and Y. Izni, "Optimization
Methods using Genetic Algorithms for Reactive Power Planning in
Power Systems," Proceedings of 12th PSCC, Dresden, Germeny,
Augest 17-23, 1996, Vol. 1, pp. 483-491.
[8] S.K. Lee, K.M. Son and J.K. Park, "Voltage Profile Optimization
using a Pyramid Genetic Algorithm," Proc. ISAP 97, Seoul, Korea,
July 6-10, 1997, pp. 407-414.
[9] D.C Walters and G.B. Sheble, "Genetic Algorithm Solution of
Economic Dispatch with Valve Point Loading," IEEE Trans. On
Power Systems, Vol. 8, No. 3, 1993, pp.1325-1332.
[10] G.B. Sheble and K. Britigg, "Refined Genetic Algorithm-Economic
Dispatch Example," IEEE Transactions on Power Systems, Vol. 10,
No. 1, Feb. 1995, pp. 117-124.
[11] Po-Hung Chen and Hong-Chan Chang, "Large-Scale Economic
Dispatch by Genetic Algorithm," IEEE Transactions on Power
Systems, Vol. 10, No. 4, Nov. 1995, pp. 1919-1926.
[12] S.O. Orero and M.R. Irving, " A Genetic Algorithm for Generator
Scheduling in Power Systems," International Journal on Electric
Power and Energy Systems, Vol. 18, No. 1, Jan 1996, pp. 19-26.
[13] Chira Achyuthakan, "Genetic Algorithms Applications to Economic
Load Dispatch," Master Thesis, AIT Bangkok, Thailand, August 1997.
[14] J.D. Weber, "Implementation of a Newton-Based Optimal Power Flow
into a Power System Simulation Environment," Master Thesis,
University of Illinois at Urbana-Champain; Urbana-Illinois.
Available from http://energy.ece.uiuc.edu/jamie (1997).
[15] C.A. Roa-Sepulveda, B.J. Pavez-lazo, "A Solution to the Optimal
Power Flow using Simulated Annealing," Electrical Power and
Energy Systems, 25 (2003), pp. 47-57.
[16] M.S. Osman, M.A. Abo-Sinna, A.A. Mousa, "A solution to the
optimal power flow using genetic algorithm," Applied Mathematics
and Computation, Elsevier, Vol. 155, Issue 2, Aug. 6, 2004, pp. 391-
405.
[17] K.Y. Lee, Y.M. Park and J.L. Ortiz, "A United Approach to Optimal
Real and Reactive Power Dispatch," IEEE Trans. on Power Apparatus
and Systems, Vol. PAS-104, No. 5, May 1985, pp. 1147-1153.
[18] L.L. Lai, J.T. Ma, R. Yokoyama and M. Zhao, "Improved Genetic
algorithms for Optimal Power Flow under both normal and contingent
operation states," Electrical Power and Energy Systems, Vol. 19, No.
5, 1997, pp. 287-292.
[19] Ashish Saini, D.K. Chaturvedi and A.K. Saxena, "Optimal Power
Flow Solution: a GA-Fuzzy System Approach," International Jr. of
Emerging Electric Power Systems, Vol. 5, Issue 2, 2006, Article 1.
@article{"International Journal of Electrical, Electronic and Communication Sciences:62191", author = "Ashish Saini and A.K. Saxena", title = "Enhanced GA-Fuzzy OPF under both Normal and Contingent Operation States", abstract = "The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.", keywords = "Contingent operation state, Fuzzy rule base, Genetic
Algorithms, Optimal Power Flow.", volume = "2", number = "5", pages = "965-9", }
