AUTHORS: A. N. Afandi
Download as PDF
ABSTRACT: This paper presents an application of the novel evolutionary algorithm for assessing an economic power system operation throughout a combined economic and emission dispatch problem required by various technical limitations. Moreover, this problem considers pollutant production and fuel consumption problems for covering environmental protection and fuel usage aspects as a constrained objective function. Running out simulations show, minimum costs depend on various weighting factors implemented in the defined problem. Reducing the total fuel cost focused on the dispatching priority and the pollutant target based on the emission production have different implications as its contribution on the economic operation. The increased power demand leads to generated powers, costs and emission discharges associated with its parameters and schedules.
KEYWORDS: economic dispatch, emission dispatch, intelligent computation, load demand, weighting factors
REFERENCES:
[1] Mohamed E. El-Hawary, Introduction to Electrical Power Systems, New Jersey: John Wiley & Sons, 2008, p.3.
[2] Yunzhi Cheng, Weiping Xiao, Wei-Jen Lee and Ming Yang, A new approach for emissions and security constrained economic dispatch, in Proc. NAPS IEEE Conference, 2009, pp. 1-5.
[3] R. Gopalakrishnan, A.Krishnan, A novel combined economic and emission dispatch problem solving technique using nondominated ranked genetic algorithm, European Journal of Scientific Research, Vol. 64, Nov. 2011, pp. 141-151.
[4] H. Chahkandi Nejad, R. Jahani, M. Mohammad Abadi, GAPSO-based Economic Load Dispatch of Power System, Australian Journal of Basic and Applied Sciences, Vol. 5, July 2011, pp. 606-611.
[5] S. Subramanian, and S. Ganesa, A simplified approach for ED with piecewise quadratic cost functions, International Journal of Computer and Electrical Engineering, Vol. 2, Oct. 2010, pp. 793-798.
[6] A. A. El-Keib, H. Ma, and J. L. Hart, Environmentally constrained ED using the lagrangian relaxation method, IEEE Trans. Power Systems, Vol. 9, Nov. 1994, pp. 1723- 1729.
[7] Ahmed Farag, Samir Al-Baiyat, T.C. Cheng, Economic load dispatch multiobjective optimization procedures using linear programming techniques, IEEE Trans. Power Systems, Vol. 10, May 1995, pp. 731-738.
[8] Yong Fu, Mohammad Shahidehpour, Zuyi Li, Security constrained unit commitment with AC constraints, IEEE Trans. Power Systems, Vol. 20, Aug. 2005, pp. 153-155.
[9] T. Yalcinoz and M. J. Short, Large-scale ED using an improved hopfield neural network, IEE Proc. Gener. Transm. Distrib. Vol. 144, March 1997, pp. 181-185.
[10] Y. Abdelaziz, S. F. Mekhamer, M. A. L. Badr, and M. Z. Kamh, ED using an enhanced hopfield neural network, Electric Power Components and Systems, Vol. 36, July 2008, pp. 719-732.
[11] Z.-L. Gaing, Particle swarm optimization to solving the ED considering the generator constraints, IEEE Trans. Power Systems, Vol. 18, Aug. 2003, pp.1187-1195.
[12] A.N. Afandi, Hajime Miyauchi, Improved Artificial Bee Colony Algorithm Considering Harvest Season for Computing Economic Disatch on Power System, IEEJ Transactions on Electrical and Electronic Engineering, Vol. 9, Issue 3, May 2014, pp. 251-257.
[13] Fahad S. Abu-Mouti and M.E.El-Hawary, Optimal distributed generation allocation and sizing in distribution system via artificial bee colony algorithm, IEEE Journal & Magazines, Vol. 26, Oct. 2011, pp. 2090-2101.
[14] K. Sathish Kumar, V.Tamilselvan, N.Murali, R.Rajaram, N.Shanmuga Sundaram and T.Jayabarathi, Economic load dispatch with emission constraints using various PSO algorithm, WSEAS Transaction on Power System, Vol. 9, Sept. 2008, pp. 598-607.
[15] A.N. Afandi, Hajime Miyauchi, Solving combined economic and emission dispatch using harvest season artificial bee colony algorithm considering food source placements and modified rates, International Journal on Electrical Engineering and Informatics, Vol. 6, No. 2, June 2014, pp. 266-279.
[16] M. A. Abido, Enviranmental/economic power dispatch using multiobjective evolutionary algorithm, IEEE Trans. Power Systems, Vol. 18, Nov. 2003, pp. 1529-1537.
[17] A.N. Afandi, Optimal scheduling power generations using HSABC algorithm considered a new penalty factor approach, IEEE Conference on Power Engineering and Renewable Energy, December 9-11, 2015, Bali, Indonesia.
WSEAS Transactions on Business and Economics, ISSN / E-ISSN: 1109-9526 / 2224-2899, Volume 14, 2017, Art. #36, pp. 354-359
Copyright © 2017 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0