Unit Commitment Solution Using Shuffled Complex Evolution with Principal Component Analysis
This paper proposes Unit Commitment solution based on the Shuffled complex evolution with Principal component analysis algorithm-University of California at Irvine. The features of the proposed algorithm are: It solves the problem of population degeneration. It combines the strength of shuffled complex, the Nelder-Mead simplex and multi-normal re-sampling to achieve efficient optimization. By representing the chromosome intelligently, the chromosome length and population size is reduced. The effectiveness of the proposed algorithm is tested on standard 10, 40, 80 and 100 units, 24 hour power system. Simulation results obtained illustrate that the proposed algorithm can produce global optimal solution compared to that of other reported methods.
Copyright © 2014 Praise Worthy Prize - All rights reserved.
Wood, A. J., and Wollenberg, B. F., Power Generation, Operation, and Control. New York, John Wiley & Sons, Inc., 1984.
N. P. Padhy, “Unit Commitment - A Bibliographical Survey”, IEEE Transactions on Power Systems, Vol. 19, No. 2, pp. 1196-2005, 2004.
K. Hara, M. Kimura, and N. Honda, “A method for planning economic unit commitment and maintenance of thermal power systems,” IEEE Trans. Power App. Syst., vol. PAS-85, pp. 427–436, May 1966.
F. N. Lee, “Short-term unit commitment—a new method,” IEEE Trans. Power Syst., vol. 3, pp. 421–428, May 1988.
Burns, R. M., and Gibson, C. A., “Optimization of priority lists for a unit commitment program”, Proc. IEEE Power Engineering Society Summer Meeting, Paper A, 75 453-1, 1975.
W. L. Snyder, Jr., H. D. Powell, Jr., and J. C. Rayburn, “Dynamic programming approach to unit commitment,” IEEE Trans. Power Syst., vol. 2, pp. 339–347, May 1987.
Ouyang, Z., and Shahidehpour, S. M., “An intelligent dynamic programming for unit commitment application”, IEEE Trans. on Power Systems, Vol. 6, No. 3, pp. 1203-1209, Aug. 1991.
T. S. Dillon, K. W. Edwin, H. D. Kochs, and R. J. Taud, “Integer programming approach to the problem of optimal unit commitment with probabilistic reserve determination,” IEEE Trans. Power App. Syst., vol. PAS-97, pp. 2154–2166, Nov./Dec. 1978.
Muckstadt, J. A., and Wilson, R. C., “An application of mixed-integer programming duality to scheduling thermal generating systems”, IEEE Trans. on Power Apparatus and Systems, pp. 1968-1978, 1968.
Cohen, A. I., and Yoshimura, M., “A branch-and bound algorithm for unit commitment”, IEEE Trans. on Power Apparatus and Systems, Vol. PAS-102, pp. 444-451, Feb. 1983.
Zhuang, F., and Galiana, F. D., “Toward a more rigorous and practical unit commitment by Lagrangian relaxation”, IEEE Trans. on Power Systems, Vol. 3, No. 2, pp. 763-770, May 1988.
L. Coelho and V. Mariani, “Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect,” Power Systems, IEEE Transactions on, vol. 21, no. 2, pp. 989 – 996, May 2006.
A. H. Mantawy, Y. L. Abdel-Magid, and S. Z. Selim, “Unit commitment by Tabu search,” Proc. Inst. Elect. Eng., Gen. Transm. Dist., vol. 145, no. 1, pp. 56–64, Jan. 1998.
D. N. Simopoulos, S. D. Kavatza, and C. D. Vournas, “Unit commitment by an enhanced simulated annealing algorithm,” IEEE Trans. on Power Systems, Vol. 21, No. 1, pp. 68-76, Feb. 2006.
S. Li, S. M. Shahidehpour, and C. Wang, “Promoting the application of expert systems in short-term unit commitment,” IEEE Trans. Power Syst., vol. 3, pp. 286–292, Mar. 1993.
S. Saneifard, N. R. Prasad, and H. A. Smolleck, “A fuzzy logic approach to unit commitment,” IEEE Trans. Power Syst., vol. 12, pp. 988–995, May 1997.
H. Sasaki, M. Watanabe, J. Kubokawa, N. Yorina, and R. Yokoyama, “A solution method of unit commitment by artificial neural network,” in Proc. IEEE Power Eng. Soc. Summer Meeting, 1991.
D. C.Walters and G. B. Sheble, “Genetic algorithm solution of economic dispatch with valve point loading,” IEEE Trans. Power Syst., vol. 8, no. 3, pp. 1325–1332, Aug. 1993.
S. A. Kazarlis, A. G. Bakirtzis, and V. Petridis, “A genetic algorithm solution to the unit commitment problem,” IEEE Trans. on Power Systems, Vol. 11, No. 1, pp. 83-92, Feb. 1996.
K. A. Juste, H. Kita, E. Tanaka, and J. Hasegawa, “An evolutionary programming solution to the unit commitment problem,” IEEE Trans. Power Syst., vol. 14, pp. 1452–1459, Nov. 1999.
N. Sinha, R. Chakrabarti, and P. K. Chattopadhyay, “Evolutionary programming techniques for economic load dispatch,” IEEE Trans. Evol. Comput., vol. 7, no. 1, pp. 83–94, Feb. 2003.
S. Chusanapiputt, D. Nualhong and S. Phoomvuthisarn, “Relativity Pheromone Updating Strategy in Ant Colony Optimization for Constrained Unit Commitment Problem”, Power System Technology, IEEE, 2006
Se-Hwan Jang, Jae Hyung Roh, Wook Kim, Tenzi Sherpa, Jin-Ho Kim and Jong-Bae Park , “A Novel Binary Ant Colony Optimization: Application to the Unit Commitment Problem of Power Systems ,” JEET, Korea, Vol. 6, no. 2, 2011.
B. Zhao, C. X. Guo, B. R. Bai and Y. J. Cao, “An improved particle swarm optimization algorithm for unit commitment,” Electrical Power & Energy Systems, Vol. 28, Issue 7, pp. 482-490, Sep. 2006.
S. Patra, S.K. Goswami, B. Goswami, “Differential Evolution Algorithm for solving unit commitment with ramp constraints”, Electric power components and systems, vol. 36, pp. 771-787, 2008.
Ali Keles, “Binary differential evolution for the unit commitment problem”, Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation, NewYork, USA, pp. 2765-2768.
R.Balamurugan, S.Subramanian, “Self-Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve-Point Effects and Multiple Fuel Options”, World Academy of Science, Engineering and Technology, pp. 466-473, vol. 27, 2007.
M. Eslamian, S. H. Hosseinian, and B. Vahidi, “Bacterial foraging based solution to the unit-commitment problem,” IEEE Trans. Power Syst., vol. 24, no. 3, pp. 1478–1488, Aug. 2009.
Moosa Moghimi Hadji, and Behrooz Vahidi, “A Solution to the Unit Commitment Problem Using Imperialistic Competition Algorithm”, IEEE Trans. Power Syst., vol. 27, no. 1, pp. 117–124, Feb. 2013.
R. Jahani, H. Chahkandi Nejad, A.H. Araskalaei and M. Hajinasiri, “A Solution to The Unit Commitment Problem Using Hybrid Genetic and particle swarm optimization Algorithms”, Australian Journal of Basic and Applied Sciences, vol. 5, no. 5, pp. 628-634, 2011.
Surekha P, N. Archana and S.Sumathi, “Unit Commitment and Economic Load Dispatch using Self Adaptive Differential Evolution” WSEAS Transactions on Power Systems, vol. 7, no. 4, Oct 2012.
K. Chandrasekaran and Sishaj P. Simon, “Multi-objective scheduling problem: Hybrid approach using fuzzy assisted cuckoo search algorithm”, Elsevier: Swarm and Evolutionary Computation, vol. 5, pp. 1–16, 2012.
Q Y Duan, V K Gupta and S Sorooshian, “ Shuffled Complex Evolution approach for effective and efficient global minimization”, Journal of Optimization Theory and Applications, vol. 76, no. 3, pp. 501–521, March. 1993.
Wei Chu, Xiaogang Gao and Soroosh Sorooshian, “A new Evolutionary search statergy for global optimization of high – dimensional problems”, Journal of Informational Science, Elsivier, vol. 181, n0. 22, pp. 4909-4927, Nov. 2011.
Ganesan, S., Subramanian, S., A novel hybrid method for thermal unit commitment problems, (2010) International Review on Modelling and Simulations (IREMOS), 3 (4), pp. 694-704.
Padmini, S., Jegatheesan, R., Dash, S.S., Hemanth, S., A new approach for solving hydrothermal unit commitment and scheduling for generating companies using particle swarm optimization, (2014) International Review on Modelling and Simulations (IREMOS), 7 (1), pp. 142-151.
Damiano, A., Gatto, G., Marongiu, I., Meo, S., Perfetto, A., Serpi, A., Single-stage grid connected PV inverter with active and reactive power flow control via PSO-PR based current controlled SVPWM, (2012) International Review of Electrical Engineering (IREE), 7 (4), pp. 4647-4654.
Esposito, F., Isastia, V., Meo, S., PSO based energy management strategy for pure electric vehicles with dual energy storage systems, (2010) International Review of Electrical Engineering (IREE), 5 (5), pp. 1862-1871.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2020 Praise Worthy Prize