Genetic Optimization for Combined Heat and Power Dispatch

Lahouari Abdelhakem-Koridak(1), Mostefa Rahli(2*), Fatima Zohra Benayed(3)

(1) Electrical department, University of Sciences and Technology of Oran, Algeria
(2) Electrical department, University of Sciences and Technology of Oran, Algeria
(3) Electrical department, University of Sciences and Technology of Oran, Algeria
(*) Corresponding author


DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)

Abstract


This paper presents a stochastic optimization approach to cogeneration of producing and using same electricity and heat from a single primary energy within the same installation, the genetic algorithms are more suitable for the economic dispatch and cogeneration. Genetic Algorithms (GA) are inspired by the concept of natural selection developed by Charles Darwin. The vocabulary used is directly modeled on the theory of evolution and genetics. The performance of the proposed algorithm is validated by illustration on IEEE standard networks. The results of the proposed approach are compared with other optimization methods. From numerical results, we see that the GA is able to provide a better solution in less effort calculation.
Copyright © 2014 Praise Worthy Prize - All rights reserved.

Keywords


Load Flow; Economic Dispatching Optimization; Cogeneration; Genetic Algorithm

Full Text:

PDF


References


D.E. Goldberg, Genetic Algorithm in Search Optimisation and Machine Learning (Addison-Wesley, (1989).

M.Rahli et P.Pirotte, Dispatching Economique par une Nouvelle Méthode de Programmation Non Linéaire à la Répartition Economique des Puissances Actives dans un Réseaux d’Energie Electrique, (CIMASI’96, Casablanca, Maroc, 14-16 novembre 1996, pp 325-330).

M.Rahli, Contribution à l’Etude de la Répartition Optimale des Puissances Actives dans un Réseau d’Energie Electrique,(thèse de doctorat, 06 janvier 1996, USTO. Algérie).

L. Abdelhakem-Koridak, M. Rahli et R. Ouidir, Application des Algorithmes Génétiques à la Répartition Optimale des Puissances dans un Réseau d’Energie Electrique , ( CIMASI’2002, du 23 au 25 Octobre 2002 Casablanca, Maroc).

M.A. Abido , A Niched Pareto genetic algorithm for Multiobjective Environmental/Economic Dispatch, (Electrical Power and Energy Systems N°25, 2003, 97-105).
http://dx.doi.org/10.1016/s0142-0615(02)00027-3

Yokoyama R, Bae SH, Morita T, Sasaki H, Multiobjective Generation Dispatch Based on Probability Security Criteria, (IEEE Trans Power Syst 1988; 3(1): 317–24).
http://dx.doi.org/10.1109/59.43217

Farag A, Al-Baiyat S, Cheng TC., Economic Load Dispatch Multiobjective Optimization Procedures Using Linear Programming Techniques , ( IEEE Trans Power Syst 1995; 10(2):731–8).
http://dx.doi.org/10.1109/59.387910

A .Immanuel Selva Kumar, K.Dhanushkodi, J. Jaya Kumar et C. Kumar Charlie Paul , Particle Swarm Optimization Solution to Emission and Economic Dispatch Problem,( 0-7803-7651-X/ 03/ 2003 IEEE ).
http://dx.doi.org/10.1109/tencon.2003.1273360

L. Abdelhakem-Koridak, M. Rahli et R. Ouidir, Optimisation par l’Algorithmes Génétiques du Coût de Production dans un Réseau d’Energie Electrique, (CIMNA1,du 14 au 15 Novembre 2003, Beyrouth Liban).

L. Slimani : Contribution à l’application de l’optimisation par des méthodes métaheuristiques à l’écoulement de puissance optimal dans un environnement de l’électricité dérégulé, Thèse de Doctorat en sciences soutenue 22/12/2009, Université de Batna, Algérie

L. Abdelhakem-Koridak, M. Rahli , Application d’un Algorithme Génétique à la Fonction Multi Objective Environnement/ Economique de la Production d’Energie Electrique, 5ème conférence régionale des comités CIGRE des pays arabes, du 21au 23 juin 2004, Algérie.

H.V. Larsen, H. Palsson, H.F. Ravn, “Probabilistic Production Simulation Including Combined Heat andPower Plants”, Electric Power Systems Research, Vol. 48, pp. 45-56, 1998.
http://dx.doi.org/10.1016/s0378-7796(98)00080-7

R. Lahdelma, H. Hakonen, “An Efficient Linear Programming Algorithm for Combined Heat and PowerProduction”, European Journal of Operational Research, Vol. 148, pp. 141-151, 2003.
http://dx.doi.org/10.1016/s0377-2217(02)00460-5

T. Bouktir and L. Slimani, “Optimal power flow of the Algerian Electrical Network Using Genetic Algorithms”, WSEAS Tra ns on Circuit and Systems, Issue 6, Vol 3, pp. 1478-1482, August 2004, ISSN: 1109-2734, WSEAS Press

A. Rong, H. Hakonen, R. Lahdelma, “An Efficient Linear Model and Optimization Algorithm for Multisite Combined Heat and Power Production”, European Journal of Operational Research, Vol. 168, pp. 612-632, 2006.
http://dx.doi.org/10.1016/j.ejor.2004.06.004

Y.H. Song, C.S. Chou, T.J. Stonham, “Combined Heat and Power Dispatch by Improved Ant Colony Search Algorithm”, Electric Power Systems Research, Vol. 52, pp. 115-121, 1999.
http://dx.doi.org/10.1016/s0378-7796(99)00011-5

C.T. Su, C.L. Chiang, “An Incorporated Algorithm for Combined Heat and Power Economic Dispatch”, Electric Power Systems Research, Vol. 69, pp 187-195, 2004.
http://dx.doi.org/10.1016/j.epsr.2003.08.006

A.Vasebi, M. Fesanghary, S.M.T. Bathaee, “Combined Heat and Power Economic Dispatch by Harmony Search Algorithm”, International Journal of Electrical Power Energy Systems, Vol. 29, pp. 713-719, 2007.
http://dx.doi.org/10.1016/j.ijepes.2007.06.006

T. Guo, M.I. Henwood, M. Van Ooijen, “An Algorithm for Heat and Power Dispatch”, IEEE Transactions on Power Systems, Vol. 11, No. 4, pp 1778-1784, 1996.
http://dx.doi.org/10.1109/59.544642

D. Karaboga and B. Basturk. 2008. on the performance of artificial bee colony (ABC) algorithm. Applied soft computing, 8: pp 687-697.
http://dx.doi.org/10.1016/j.asoc.2007.05.007

Guo Qiang Li., Peifeng Niu. and Xingjun Xiao. 2012. Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Applied soft computing, 12: pp 320-332.
http://dx.doi.org/10.1016/j.asoc.2012.12.026

Basu. 2011. Bee colony optimization for combined heat and power economic dispatch. Expert system with applications, 38: pp 13527-13531.
http://dx.doi.org/10.1016/j.eswa.2012.05.029

Wang KP and Fung CC. 1995. Simulated annealing based economic dispatch algorithm. Proc Inst Electr.Eng, C. 140: pp 509-515.

M. Benyahia, M. Rahli, L. Benasla, Continuous Genetic Algorithm to Solve Economic Environnemental Dispatch (EED), (2008) International Review of Automatic Control (IREACO), 1. (3), pp. 341-346.

Singh, P., Kothari, D.P., Singh, M., Feasibility of interconnected distribution network for the integration of distributed energy resources using GA approach, (2013) International Review of Electrical Engineering (IREE), 8 (1), pp. 314-320.

Bagriyanik, F.G., Aygen, Z.E., Bagriyanik, M., Minimization of power transmission losses in series compensated systems using genetic algorithm, (2011) International Review of Electrical Engineering (IREE), 6 (2), pp. 810-817.

Sebt-Ahmadi, S.M., Ebrahimi, S., Pirnazari, A., Ranjbar, A.-M., An optimal hybrid power generation scheme in a power system - A practical experience, (2013) International Review of Electrical Engineering (IREE), 8 (5), pp. 1566-1577.

El-Arini, M.M.M., Othman, A.M., Said, T., Particle swarm optimization and genetic algorithm for convex and non-convex economic dispatch, (2014) International Review of Electrical Engineering (IREE), 9 (1), pp. 127-135.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2020 Praise Worthy Prize