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Off-Grid Rural Electrification in India Using Renewable Energy Resources and Different Battery Technologies with a Dynamic Differential Annealed Optimization

Author

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  • Polamarasetty P Kumar

    (Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam 532127, India)

  • Vishnu Suresh

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
    Hitachi ABB Power Grids Research, ul. Pawia 7, 31-154 Kraków, Poland)

  • Michal Jasinski

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

  • Zbigniew Leonowicz

    (Faculty of Electrical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland)

Abstract

Several families in India live in remote places with no access to grid-connected power supply due to their remoteness. The study area chosen from the Indian state of Odisha does not have an electrical power supply due to its distant location. As a result, this study analyzed the electrification process using Renewable Energy (RE) resources available in the locality. However, these RE resources are limited by their dependency on weather conditions and time. So, a robust battery storage system is needed for a continuous power supply. Hence, the Nickel Iron (Ni-Fe), Lithium-Ion (Li-Ion) and Lead Acid (LA) battery technologies have been analyzed to identify a battery technology that is both technologically and economically viable. Using the available RE resources in the study area, such as photovoltaic and biomass energy resources, as well as the various battery technologies, three configurations have been modelled, such as Photovoltaic Panels (PVP)/Biomass Generator(BIOMG)/BATTERY (Ni-Fe) , PV/BIOMG/BATTERY (Li-Ion) and PVP/BMG/BATTERY (LA) . These three configurations have been examined using nine prominent metaheuristic algorithms, in which the PVP/BIOMG/BATTERY (Ni-Fe) configuration provided the optimal Life Cycle Cost value of 367,586 USD. Among the all metaheuristic algorithms, the dynamic differential annealed optimization algorithm was given the best Life Cycle Cost values for all of the three configurations.

Suggested Citation

  • Polamarasetty P Kumar & Vishnu Suresh & Michal Jasinski & Zbigniew Leonowicz, 2021. "Off-Grid Rural Electrification in India Using Renewable Energy Resources and Different Battery Technologies with a Dynamic Differential Annealed Optimization," Energies, MDPI, vol. 14(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5866-:d:636814
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    References listed on IDEAS

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    1. Patel, Alpesh M. & Singal, Sunil Kumar, 2019. "Optimal component selection of integrated renewable energy system for power generation in stand-alone applications," Energy, Elsevier, vol. 175(C), pages 481-504.
    2. Chauhan, Anurag & Saini, R.P., 2016. "Discrete harmony search based size optimization of Integrated Renewable Energy System for remote rural areas of Uttarakhand state in India," Renewable Energy, Elsevier, vol. 94(C), pages 587-604.
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    Cited by:

    1. Zbigniew Leonowicz & Michal Jasinski, 2022. "Machine Learning and Data Mining Applications in Power Systems," Energies, MDPI, vol. 15(5), pages 1-2, February.
    2. Michał Jasiński & Arsalan Najafi & Tomasz Sikorski & Paweł Kostyła & Jacek Rezmer, 2022. "Operation of an Energy Storage System Integrated with a Photovoltaic System and an Industrial Customer under Different Real and Pseudo-Real Profiles," Energies, MDPI, vol. 15(21), pages 1-27, November.

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