EconPapers    
Economics at your fingertips  
 

Techno-Economic Feasibility Analysis of Grid-Connected Microgrid Design by Using a Modified Multi-Strategy Fusion Artificial Bee Colony Algorithm

Sweta Singh, Adam Slowik, Neeraj Kanwar and Nand K. Meena
Additional contact information
Sweta Singh: Department of Electrical Engineering, Manipal University Jaipur, Janpur 303007, India
Adam Slowik: Department of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland
Neeraj Kanwar: Department of Electrical Engineering, Manipal University Jaipur, Janpur 303007, India
Nand K. Meena: School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK

Energies, 2021, vol. 14, issue 1, 1-20

Abstract: The present work investigates the techno-economic solution that can address the problem of rural electrification. To maintain a continuous power supply to this village area, a grid-connected microgrid system was designed that consists of solar photovoltaic (SPV) and battery energy storage systems (BESS). The recently introduced multi-strategy fusion artificial bee colony (MFABC) algorithm was hybridized with the simulated annealing approach and is referred to as the MFABC+ algorithm. This was employed to determine the optimal sizing of different components comprising the integrated system as well as to maximize the techno-economic objectives. For validation, the simulation results obtained by the MFABC+ algorithm are compared with the results obtained using HOMER software, the particle swarm optimization algorithms and the original MFABC algorithm. It was revealed that the MFABC+ algorithm has a better convergence rate and the potential ability to provide compromising results in comparison to these existing optimization tools. It was also discovered through the comprehensive evaluation that the proposed system has the potential capability to meet the electricity demand of the village for 24 × 7 at the lowest levelized cost of electricity.

Keywords: energy management; levelized cost of electricity; microgrid; nature-inspired optimization algorithm; renewable energy; rural electrification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/1/190/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/1/190/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:1:p:190-:d:473625

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:190-:d:473625