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Development of optimal integrated renewable energy model with battery storage for a remote Indian area

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  • Rajanna, S.
  • Saini, R.P.

Abstract

Over the past few years, renewable energy has come to be seen as a possible solution to the energy problems of people. The present work focuses on optimal sizing of an integrated renewable energy system (IRES) considering locally available different renewable energy sources namely micro hydro, solar, wind, biomass and biogas with battery system for electrification of a remote area in Karnataka state in India. Genetic algorithm (GA) has been used to minimize the total net present cost (TNPC) and cost of energy (COE) of the developed IRES model considering the three decision variables-total active sunshine area occupied by the SPV modules, total swept area required to install wind mills and state of charge (SOC) of battery system. Scenario based results of optimal sizes, TNPC and COE have been obtained based on suitable device types and time schedule of biomass generator. Based on optimization results, three IRE scenarios are proposed for the study area. Of the three, scenario-S1 for zone 2 and zone 3. While, scenario-S2 for zone 1 and zone 4 are found to be most feasible for the study area. Further, optimal time schedule, resource combination and device type for all zones have also been determined.

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  • Rajanna, S. & Saini, R.P., 2016. "Development of optimal integrated renewable energy model with battery storage for a remote Indian area," Energy, Elsevier, vol. 111(C), pages 803-817.
    • Handle: RePEc:eee:energy:v:111:y:2016:i:c:p:803-817
    DOI: 10.1016/j.energy.2016.06.005
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    9. 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.
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    12. Rajanna, S. & Saini, R.P., 2016. "Employing demand side management for selection of suitable scenario-wise isolated integrated renewal energy models in an Indian remote rural area," Renewable Energy, Elsevier, vol. 99(C), pages 1161-1180.
    13. Suresh Vendoti & M. Muralidhar & R. Kiranmayi, 2021. "Techno-economic analysis of off-grid solar/wind/biogas/biomass/fuel cell/battery system for electrification in a cluster of villages by HOMER software," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 351-372, January.
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    16. Ossai, Chinedu I., 2017. "Optimal renewable energy generation – Approaches for managing ageing assets mechanisms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 269-280.
    17. Talaat, M. & Elkholy, M.H. & Farahat, M.A., 2020. "Operating reserve investigation for the integration of wave, solar and wind energies," Energy, Elsevier, vol. 197(C).
    18. Das, Pronob & Das, Barun K. & Rahman, Mushfiqur & Hassan, Rakibul, 2022. "Evaluating the prospect of utilizing excess energy and creating employments from a hybrid energy system meeting electricity and freshwater demands using multi-objective evolutionary algorithms," Energy, Elsevier, vol. 238(PB).
    19. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    20. Alexander Lavrik & Yuri Zhukovskiy & Pavel Tcvetkov, 2021. "Optimizing the Size of Autonomous Hybrid Microgrids with Regard to Load Shifting," Energies, MDPI, vol. 14(16), pages 1-19, August.
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    22. Zhang, Weiping & Maleki, Akbar & Rosen, Marc A. & Liu, Jingqing, 2018. "Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage," Energy, Elsevier, vol. 163(C), pages 191-207.

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