Thermal Unit Commitment Solution using Priority List Method and Genetic-Imperialist Competitive Algorithm
Keywords:
Economic load dispatch, Genetic-imperialist competitive algorithm, Priority list, Spinning reserve, Thermal unit commitment.Abstract
A novel strategy including a Priority List (PL) based method and a heuristic algorithm which is named Genetic-Imperialist Competitive Algorithm (GICA) has been proposed in this paper to solve thermal Unit Commitment Problem (UCP). This problem has been confined by some constraints like minimum down time, minimum up time, spinning reserve, load demand, and limited output power of the generating units. The optimization process is carried out in three steps. At first, a strategy based PL is used to find units priority, in second step the GICA employed to solve Economic Load Dispatch (ELD), and finally a correction strategy tried to find and replace better solutions. The accuracy and effectiveness of the proposed method is verified by two different case studies with 4 and 10 generation units system. The comparison of results with some other methods shows that proposed three step method has a better performance and achieve better solution in an admissible time interval.
References
Allen J. Wood; Bruce F. Wollenberg. Power generation, operation, and control, New York: John wiley & sons, 1996
Yang Tingfang; Ting, T.O., "Methodological Priority List for Unit Commitment Problem," in Computer Science and Software Engineering, 2008 International Conference on, vol.1, no., pp.176-179, 12-14 Dec. 2008
Ouyang, Z.; Shahidehpour, S.M., "An intelligent dynamic programming for unit commitment application," in Power Systems, IEEE Transactions on, vol.6, no.3, pp.1203-1209, Aug 1991
Zhuang, Fulin; Galiana, F.D., "Towards a more rigorous and practical unit commitment by Lagrangian relaxation," in Power Systems, IEEE Transactions on, vol.3, no.2, pp.763-773, May 1988
Morales-Espana, G.; Latorre, J.M.; Ramos, A., "Tight and Compact MILP Formulation for the Thermal Unit Commitment Problem," in Power Systems, IEEE Transactions on, vol.28, no.4, pp.4897-4908, Nov. 2013
Moghimi Hadji, M.; Vahidi, B., "A Solution to the Unit Commitment Problem Using Imperialistic Competition Algorithm," in Power Systems, IEEE Transactions on , vol.27, no.1, pp.117-124, Feb. 2012
Saber, A.Y.; Senjyu, T.; Yona, A.; Funabashi, T., "Unit commitment computation by fuzzy adaptive particle swarm optimisation," in Generation, Transmission & Distribution, IET, vol.1, no.3, pp.456-465, May 2007
Logenthiran, T.; Srinivasan, D., "Particle Swarm Optimization for unit commitment problem," in Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on , vol., no., pp.642-647, 14-17 June 2010
Xiang Yu; Xueqing Zhang, "Unit commitment using Lagrangian relaxation and particle swarm optimization," in International Journal of Electrical Power & Energy Systems, vol.61, pp.510-522, 2014
Mantawy, A.H.; Abdel-Magid, Y.L.; Selim, S.Z., "A simulated annealing algorithm for unit commitment," in Power Systems, IEEE Transactions on , vol.13, no.1, pp.197-204, Feb 1998
Vo Ngoc Dieu; Ongsakul, W., "Enhanced merit order and augmented Lagrange Hopfield network for ramp rate constrained unit commitment," in Power Engineering Society General Meeting, 2006. IEEE, vol., no., pp., 2006
Aditya parashar; Kuldeep Kumar Swankar, "A Genetic Algorithm Approach to Solve Unit Commitment Problem, "in IOSR Journal of Electrical and Electronics Engineering, vol.7, pp.60
Ganguly, D.; Sarkar, V.; Pal, J., "A new genetic approach for solving the unit commitment problem," in Power System Technology, 2004. PowerConf 2004. 2004 International Conference on , vol.1, no., pp.542-547 Vol.1, 21-24 Nov. 2004
Senjyu, T.; Yamashiro, H.; Uezato, K.; Funabashi, T., "A unit commitment problem by using genetic algorithm based on unit characteristic classification," in Power Engineering Society Winter Meeting, 2002. IEEE , vol.1, no., pp.58-63 vol.1, 2002
Boris Pavez-Lazo; Jessica Soto-Cartes, "A deterministic annular crossover genetic algorithm optimisation for the unit commitment problem," in Expert Systems with Applications, vol.38, pp. 6523-29, 2011
Juste, K.A.; Kita, H.; Tanaka, E.; Hasegawa, J., "An evolutionary programming solution to the unit commitment problem," in Power Systems, IEEE Transactions on , vol.14, no.4, pp.1452-1459, Nov 1999
Saravanan, B.; Vasudevan, E.R.; Kothari, D.P., "A solution to unit commitment problem using Invasive Weed Optimization algorithm," in Power, Energy and Control (ICPEC), 2013 International Conference on , vol., no., pp.386-393, 6-8 Feb. 2013
Chung, C.Y.; Han Yu; Kit Po Wong, "An Advanced Quantum-Inspired Evolutionary Algorithm for Unit Commitment," in Power Systems, IEEE Transactions on , vol.26, no.2, pp.847-854, May 2011
K. Chandrasekaran; S. Hemamalini; Sishaj P. Simon; Narayana Prasad Padhy, "Thermal unit commitment using binary/real coded artificial bee colony algorithm," in Electric Power Systems Research, vol.84, pp. 109-119, 2012
Mhanna S.N.; Jabr R.A. "Application of semi definite programming relaxation and selective pruning to the unit commitment problem." in Electric Power Systems Research, vol.90, pp.85
Provas Kumar Roy; Ranadhir Sarkar, "Solution of unit commitment problem using quasi-oppositional teaching learning based algorithm. " in Electrical Power and Energy Systems, vol.60, pp.96
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