BFO-based firefly algorithm for multi-objective optimal allocation of generation by integrating renewable energy sources. (1st January 2021)

• Record Type: Journal Article
• Authors: Banerjee, Swaraj; Sarkar, Dipu
• Is Part Of: International journal of grid and utility computing. Volume 12:Number 1(2021)
• Page Start: 67
• Page End: 80
• Publication Date: 2021-01-01
• Subjects: ELD -- economic load dispatch -- solar energy -- wind power -- fuel and total generation cost -- BFO -- bacterial foraging optimisation -- firefly optimisation algorithm; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

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.