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Multi-Objective Economic Emission Dispatch Solution Using Hybrid Monkey Algorithm


Affiliations
1 Faculte of technology, University Saad Dahleb Blida 09000, Algeria
2 Faculte of technology, University Saad Dahleb Blida 09000, Algeria
3 University of Kasdi Merbah Ouargla 30000, Algeria
4 University Djilali Lyabes Sidi Belabes 22000, Algeria
5 University Ziane Achour Djelfa 17000, Algeria
 

The main contribution of this paper is the application of the technique of hybridization between two meta-heuristics methods, PSO and MA, for solving the problem of economic and environmental dispatching, which is a multi-objective problem. The two contradictory objectives: fuel costs and emissions must be minimized at the same time while satisfying certain constraints of the system. In a multi objective optimization problem, to obtain good solutions, the concept of Pareto dominance is used to generate and sort dominated and non-dominated solutions. Several optimization runs of the proposed approach have been carried out on the IEEE 30 bus and a system with 6 generators. The strength of the proposed approach is tested and validated by solving several cases as: the fuel cost minimization, emission minimization, emission and cost minimization simultaneously

Keywords

Economic Power Dispatch (EPD), Combined Economic Emission Dispatch (CEED), Monkey Algorithm (MA), Particle Swarm Optimization (PSO), Hybrid Method
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  • Multi-Objective Economic Emission Dispatch Solution Using Hybrid Monkey Algorithm

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Authors

Naas Kherfane
Faculte of technology, University Saad Dahleb Blida 09000, Algeria
Fouad Khodja
Faculte of technology, University Saad Dahleb Blida 09000, Algeria
Riad Lakhdar Kherfane
University of Kasdi Merbah Ouargla 30000, Algeria
Mimoun Younes
University Djilali Lyabes Sidi Belabes 22000, Algeria
Samir Kherfane
University Ziane Achour Djelfa 17000, Algeria
Abderrahmane Amari
University Ziane Achour Djelfa 17000, Algeria

Abstract


The main contribution of this paper is the application of the technique of hybridization between two meta-heuristics methods, PSO and MA, for solving the problem of economic and environmental dispatching, which is a multi-objective problem. The two contradictory objectives: fuel costs and emissions must be minimized at the same time while satisfying certain constraints of the system. In a multi objective optimization problem, to obtain good solutions, the concept of Pareto dominance is used to generate and sort dominated and non-dominated solutions. Several optimization runs of the proposed approach have been carried out on the IEEE 30 bus and a system with 6 generators. The strength of the proposed approach is tested and validated by solving several cases as: the fuel cost minimization, emission minimization, emission and cost minimization simultaneously

Keywords


Economic Power Dispatch (EPD), Combined Economic Emission Dispatch (CEED), Monkey Algorithm (MA), Particle Swarm Optimization (PSO), Hybrid Method

References