Solving the economic load dispatch based on NSGA-II and RNSGA-II

Menna Ahmed El-ziady, Emad Elbeltagi, Ibrahim El-kalla, Mohammed Abouhawwash

Abstract


Penetration of renewable energy sources becomes very crucial for replacing fossil fuel-based energy with clean energy. However, the main problems of renewable energy sources are the intermittent nature of generation and the high cost. Therefore, optimizing the unit allocated power and the total cost are the main two objectives to solve the Economic load dispatch (ELD) problem optimally for satisfying the load demand with the minimum amount of allocated power and, hence minimizing the total cost of energy and reducing the emissions of the greenhouse gases (GHG). This paper presents a new approach that applies the Pareto optimization multi-objective to solve the ELD problem based on the non-dominated sorting genetic algorithm II (NSGA-II) and the reference point RNSGA-II. The presented method has been implemented alongside the conventional genetic algorithm (GA) for validation and comparison. Also, it is validated with the particle swarm method for comparing the performance parameters of the new method. The presented method is tested with and without losses considerations. The results showed the superiority of the proposed method as compared with other methods.     

 


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DOI (PDF): https://doi.org/10.20508/ijrer.v12i1.12693.g8419

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