Application of a new hybridization to solve economic dispatch problem on an algerian power system without or with connection to a renewable energy
Abdelkader Si Tayeb 1, 2  
,   Benyekhlef Larouci 3  
,   Daoud Rezzak 2  
,   Yahia Houam 2  
,   Hamid Bouzeboudja 1  
,   Abdelhak Bouchakour 2  
More details
Hide details
Faculty of electrical engineering. USTO, B.P 1505 El M’naouar, Oran, 31000, Algeria
Unité de Recherche Appliquée en Energies Renouvelables, URAER, Centre de Développement des Energies Renouvelables, CDER, 47133, Ghardaïa, Alegria.
Department of Electrical Engineering, University Kasdi Merbah, 30000 Ouargla, Algeria
Abdelkader Si Tayeb   

Faculty of electrical engineering. USTO, B.P 1505 El M’naouar, Oran, 31000, Algeria
Submission date: 2021-06-22
Final revision date: 2021-09-07
Acceptance date: 2021-09-08
Online publication date: 2021-09-13
Publication date: 2021-09-13
Diagnostyka 2021;22(3):101–112
The most important contribution of this article is the use of four metaheuristic approaches to tackle the problem of economic dispatching, with the goal to study the influence of the injection of a renewable energy source on the electricity cost in the Algerian network, and minimizing the production cost of electrical energy while accounting for transmission losses. A Genetic Algorithm (GA) (a real coding) and Egyptian Vulture Optimization Algorithm (EVOA), as well as two hybridizations between the metaheuristics: Classic and Modern hybridization (C.H.GA-EVOA, M.H.GA-EVOA), are presented in this work. These techniques are used to address optimization difficulties of two Algerian electricity networks. The first has three system units, whereas the second has fifteen system units. The second electricity network is connected to a solar energy source. The findings obtained are compared with other techniques to validate the high performance of the suggested methods for addressing the economic dispatch issue. This study demonstrates that EVOA and C.H.GA-EVOA provide trustworthy results, and that M.H.GA-EVOA surpasses them.
Irina C, Elias K. Recent methodologies and approaches for the economic dispatch of generation in power systems. Int trans Electr Energ Syst. 2013;23:1002-27. https:// doi: 10.1002/etep.1635.
Belkacem M, Kamel S. Interactive gravitational search algorithm and pattern search algorithm s for practical dynamic economic dispatch. Int T Electr Energy. 2015; 25:2289-09.
Si Tayeb, A. Bouzeboudja, H. Laroussé B, Naama B, Rezzak D. Egyptian Vulture Optimization For Combined Economic and Emission Dispatch New Meta- heuristic Algorithm. Journal of Electrical Engineering. 2017 17: 4-54.
Haiwang Z, Qing X, Yang W, Chongqing K. Dynamic economic dispatch considering transmission losses using quadratically constrained quadratic Program method. Power Syst IEEE Trans. 2013; 28(3):2232-41. https:// doi: 10.1109/TPWRS.2013.2254503.
Bouallag K, Djekidel R, Bessedik S. Optimisation de la tension induite sur une canalisation enterrée à partir de lignes électriques HT à l'aide de l'algorithme Grasshopper (GOA). DIAGNOSTYKA.2021;22(2):105-115.
Ding T, Bo R, Li F, Sun H. A Bi-Level branch and bound method for economic dispatch with disjoint prohibited zones considering network losses. IEEE Trans Power Syst. 2015;30 (6):2841-55. https://doi : 10.1109/TPWRS.2014.2375322.
Ehsan A, Mahmood J. An improved cuckoo search algorithm for power economic load dispatch” Int T Electr Energy. 2015; 25:958-75. https://doi : 10.1002/etep.1878.
Stambouli AB. Algerian renewable energy assessment: the challenge of sustainability. Energy Policy.2011;39(8),4507-4519. ttps://
Palanichamy C, Babu NS. Analytical solution for combined economic and emissions dispatch. Electr Power Syst Res. 2008;78(7):1129-37. https://doi:10.1016/j.epsr.200....
Adarsh BR, Raghunathan T, Jayabarathi T, Yang X-S. Economic dispatch using chaotic bat algorithm. Energy. 2016; 666-75.
Gwo-Ching L. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power. Energy. 2011; 36, 2, 1018-1029.
Basu M, Chowdhury A. Cuckoo search algorithm for economic dispatch. Energy. 2013;113:99-108.
Si Tayeb, A. Bouzeboudja, H. Application of a New Meta-heuristic Algorithm using Egyptian Vulture Optimization for Economic. PRZEGLĄD ELEKTROTECHNICZNY, R. 95 NR 6.2019. http://doi:10.15199/48.2019.06....
He X, Rao Y, Huang J. A novel algorithm for economic load dispatch of power systems. Neurocomputing. 2016; 171(1):1454-61.
Basu M. Kinetic gas molecule optimization for nonconvex economic dispatch problem. Int J Elec Power 2016; 80:325-32.
Slimani L, Bouktir T .Optimal Power Flow Solution of the Algerian Electrical Network using Differential Evolution Algorithm. TELKOMNIKA. 2012; 10,2: 199-210. https:// doi: 10.11591/telkomnika.v10i2.672.
Arag_on VS, Esquivel SC, Coello Coello CA. An immune algorithm with power redistribution for solving economic dispatch problems. Inform Sciences .2015;295:609-32.
B Larouci, L Benasla, A Belmadani. Cuckoo Search Algorithm for Solving Economic Power Dispatch Problem with Consideration of Facts Devices. UPB Sci. Bull, Series C. 2017; 79-81.
Shaw B, Mukherjee V, Ghoshal SP. Solution of economic dispatch problems by seeker optimization algorithm. Expert Syst Appl. 2012; 39(1):508-519.
Zare K, Haque MT, Davoodi E. Solving non-convex economic dispatch problem with valve point effects using modified group search optimizer method. Electr Pow Syst Res. 2012; 84(1):83-9.
Secui DC. A modified symbiotic organisms search algorithm for large scale economic dispatch problem with valve-point effects. Energy. 2016; 113:366-84.
Pradhan M, Roy PK, Pal T. Grey wolf optimization applied to economic load dispatch problems. Int J Electr Power. 2016; 83:325-334.
Jayabarathi T, Raghunathan T, Adarsh BR, Suganthan PN. Economic dispatch using hybrid grey wolf optimizer. Energy. 2016; 111:630-41.
Meng A, Li J, Yin H. An efficient crisscross optimization solution to large-scale non-convex economic load dispatch with multiple fuel types and valve-point effects. Energy. 2016; 113:1147-61.
Dexuan Z , Steven L, Zongyan L, Xiangyong K. A new global particle swarm optimization for the economic emission dispatch with or without transmission losses. Energy Conversion and Management.2017;13945-70.
Secui DC. A new modified artificial bee colony algorithm for the economic dispatch problem. Energy Convers Manage. 2015; 89:43-62.
Fraga ES, Yang L, Papageorgiou LG. On the modelling of valve point loadings for power electricity dispatch. Appl Energy. 2012; 91:301-3.
Pothiya S, Ngamroo I, Kongprawechnon W. Ant colony optimisation for economic dispatch problem with non-smooth cost functions. Int J Electr Power Energy Syst. 2010; 32(5):478-87.
Niknam T. Doagou M, H Zeinoddini, Meymand H. A new particle swarm optimization for non-convex economic dispatch. Int T Electr Energy. 2010; 21(1):656-79. https://doi: 10.1002/etep.468.
Barisal AK, Prusty RC. Large scale economic dispatch of power systems using oppositional invasive weed optimization. Appl Soft Comput. 2015; 29:122-37.
Meng K, Wang HG, Dong Z, Wong KP. Quantum-inspired particle swarm optimization for valve-point economic load dispatch. IEEE T Power Syst. 2010; 25(1):215-22.
Subbraj P,Rengaraij R, Salivahanan S, Senthikumar TR. Particle swarm optimization with modified stochastic acceleration facrors solving large scale economic dispatch problem. Int J Elec Power. 2010; 32:1014-23.
Al-Betar MA, Awadallah MA, Khader AT, Bolaji ALA. Tournament-based harmony search algorithm for non-convex economic load dispatch problem. Appl Soft Comput. 2016; 47:449-59.
Dilip K, Nandhini M. Adapting Egyptian Vulture Optimization Algorithm for Vehicle Routing Problem. International Journal of Computer Science and Information Technologies. 2016; 7(3):1199-204.
Chiranjib S, Sanjeev S, Anupam S .Egyptian Vulture Optimization Algorithm – A New Nature Inspired Meta-heuristics for Knapsack Problem. IC2IT.2013 ;209:227-37.
Gaing, Z.-L. Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE T Power Sys. 2003 ; (3):1187-95. https://doi: 10.1109/TPWRS.2003.814889.
Victoire T, Jeyakumar A E. Discussion of particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE T Power Sys.2004;19(4):2121-23.
Victoire T, Jeyakumar A E. Hybrid PSO-SQP for economic dispatch with valve-point effect. Electr Pow Syst Res. 2004; 71(1):51-59.
Sinha N, Chakrabarti R, Chattopadhyay P K. Evolutionary programming techniques for economic load dispatch. IEEE T Evolut Com¬put. 2003;7(1):83-94.
Duman S, güvenç U, yörükeren N. gravitational search algorithm for economic dispatch with valve-point effects. int rev electr eng. 2010; 5(6):2890-5.
Al-Sumait J S, Al-Othman A K, Sykulski J K. Application of pattern search method to power system valve-point economic load dispatch. Int J Elec Power. 2007; 29(10):720-30.
Belmadani, A, Benasla L, Rahli M. The dynamic economic dispatch including wind power injection in the western algerian electrical power system. Acta Polytechnica Hungarica. 2011; 8(5), 191-204.
Souag S, Benhamida F. A Dynamic Power System Economic Dispatch Enhancement by Wind Integration Considering Ramping Constraint -Application to Algerian Power System. international journal of renewable energy research. 2015; 5, 3.
Yamina A G, Hamid B. Resolution of Economic Dispatch Problem of the Algerian Network using Hybrid Metaheuristic. Electrotehnică, Electronică, Automatică (EEA). 2017; 65(1),91-96.