Title: BFO-based firefly algorithm for multi-objective optimal allocation of generation by integrating renewable energy sources

Authors: Swaraj Banerjee; Dipu Sarkar

Addresses: Department of Electrical and Electronics Engineering, National Institute of Technology, Dimapur, Nagaland, India ' Department of Electrical and Electronics Engineering, National Institute of Technology, Dimapur, Nagaland, India

Abstract: Among the rapid evolution of modernisation of alternative energy, the electric power system can be made out of a few Renewable Energy Resources (RES). This paper presents a modern and proficient technique for clearing up the ELD issue. To resolve this issue we have amalgamated two meta-heuristic optimisation algorithms, e.g., the Bacterial Foraging Optimisation (BFO) algorithm and the Firefly Optimisation Algorithm (FA) by incorporating both the renewable energies, such as solar and wind power. The quality of the proposed methodology is tried and approved on the standard IEEE 3, 6 and the 10-unit systems by solving some cases as the fuel cost minimisation, whole generation cost minimisation, emission minimisation, and at the same time the system transmission loss. The attained results are contrasted and the MOPSO and the hybrid BOA algorithms. The results show that the proposed methodology gives an accurate solution for some category of objective functions.

Keywords: ELD; economic load dispatch; solar energy; wind power; fuel and total generation cost; BFO; bacterial foraging optimisation; firefly optimisation algorithm.

DOI: 10.1504/IJGUC.2021.112477

International Journal of Grid and Utility Computing, 2021 Vol.12 No.1, pp.67 - 80

Received: 07 Sep 2019
Accepted: 11 Dec 2019
Published online: 19 Jan 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article