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A robust optimal sizing of renewable-rich multi-source microgrid under uncertainties with multi-storage options

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Abstract

Adapting the power and energy systems by integrating renewable sources is necessary to address climate change. On the other hand, microgrids are gaining prominence in meeting power and energy requirements, including in remote locations. Consequently, the power system’s penetration of renewable energy-based microgrids is increasing. Planning an isolated microgrid necessitates cost-effective capacity sizing of energy sources and storage systems for maintaining continuity in power supply. Considering the variability and uncertainty of photovoltaic (PV), wind energies, and load variations, deciding the optimal size of renewable-rich, isolated microgrids is challenging. Batteries and fuel cells are potential storage solutions for managing variability. However, a more trustworthy sizing approach is necessary to maximize power availability at the lowest possible cost, even in the face of uncertainty. Moreover, providing the microgrid owner with the opportunity to choose from a range of optimal solutions is also essential. Therefore, incorporating the uncertainty handling feature with the help of robust assessment under worst-case scenarios in the multi-objective optimization method can provide a more trustworthy solution. In this connection, a novel algorithm is proposed that instills robustness in the solutions provided by traditional non-dominated sorting genetic algorithm-II (NSGA-II), which can offer multiple break-even solutions. The isolated microgrids with PV, wind as sources, and storage technologies such as Lithium-ion (Li-ion) batteries, fuel cells, and a combination of both, a less explored scenario, have been compared to determine the effective storage option over the long run while considering uncertainties in renewable energy and load variations. The NSGA-II benchmark solutions developed under these uncertainties and variations are used to validate the robustness of the solutions obtained from the proposed robust algorithm. With a good trade-off between the cost and availability aspects, the proposed algorithm is found to be superior in getting maximum availability with minimum cost under uncertainties.

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Funding

This research work is supported in part by Science and Engineering Research Board, Department of Science and Technology, Government of India, through its research grant ECR/2015/000310

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Authors and Affiliations

  1. School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Argul, Odisha, 752050, India

    P. V. N. Mohan Krishna, P. C. Sekhar & T. R. Behera

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  1. P. V. N. Mohan Krishna
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  2. P. C. Sekhar
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  3. T. R. Behera
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Contributions

PVNMK did conceptualization, implementations, and result analysis and wrote and reviewed the manuscript. PCS contributed to developing concepts, critically analyzing results, and reviewing the manuscript. TRB did implementations and contributed to the write-up of the manuscript.

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Correspondence to P. V. N. Mohan Krishna.

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Krishna, P.V.N.M., Sekhar, P.C. & Behera, T.R. A robust optimal sizing of renewable-rich multi-source microgrid under uncertainties with multi-storage options. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02331-w

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