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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Sweta Singh & Adam Slowik & Neeraj Kanwar & Nand K. Meena, 2021. "Techno-Economic Feasibility Analysis of Grid-Connected Microgrid Design by Using a Modified Multi-Strategy Fusion Artificial Bee Colony Algorithm," Energies, MDPI, vol. 14(1), pages 1-20, January.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:190-:d:473625
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    References listed on IDEAS

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    2. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.

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