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Generation-scheduling-coupled battery sizing of stand-alone hybrid power systems

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  • Shang, Ce
  • Srinivasan, Dipti
  • Reindl, Thomas

Abstract

Properly sizing the battery energy storage system (BESS) of a stand-alone hybrid power system is an important step to guarantee its reliability and low cost. This study applies the technique of storage-integrated generation scheduling using metaheuristics to the BESS sizing, which helps to achieve the optimal scheduling scheme for each sizing plan, as its advantage over the rule-based sizing method. Such technique incorporates the storage dispatch with the scheduling of the dispatchable generators, and is formulated and solved as an optimisation with metaheuristics. Compared with existing approaches of storage-integrated generation scheduling, the metaheuristics-enabled approach proposed here relieves the modelling complexity of the optimisation, by using fewer decisions variables. Different degrees of solar and wind, as the renewable energy, are penetrated into the system, together with traditional diesel generators. The mixed-coded non-dominated sorting genetic algorithm II (NSGA-II) is employed as the main numeric tool, which shows the advantage of mixed-coded modelling over the real-coded modelling for the generation scheduling problem. The numeric evaluation of the system planning adopts the levelised cost of electricity (LCOE) as the economic indicator, to guide the real system planning and operation.

Suggested Citation

  • Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2016. "Generation-scheduling-coupled battery sizing of stand-alone hybrid power systems," Energy, Elsevier, vol. 114(C), pages 671-682.
  • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:671-682
    DOI: 10.1016/j.energy.2016.07.123
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Amrollahi, Mohammad Hossein & Bathaee, Seyyed Mohammad Taghi, 2017. "Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response," Applied Energy, Elsevier, vol. 202(C), pages 66-77.
    2. Zhu, Jianyun & Chen, Li & Wang, Bin & Xia, Lijuan, 2018. "Optimal design of a hybrid electric propulsive system for an anchor handling tug supply vessel," Applied Energy, Elsevier, vol. 226(C), pages 423-436.
    3. Ping Liu & Zexiang Cai & Peng Xie & Xiaohua Li & Yongjun Zhang, 2019. "A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process," Energies, MDPI, Open Access Journal, vol. 12(8), pages 1-19, April.
    4. Azuatalam, Donald & Paridari, Kaveh & Ma, Yiju & Förstl, Markus & Chapman, Archie C. & Verbič, Gregor, 2019. "Energy management of small-scale PV-battery systems: A systematic review considering practical implementation, computational requirements, quality of input data and battery degradation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 555-570.
    5. Baghaee, H.R. & Mirsalim, M. & Gharehpetian, G.B. & Talebi, H.A., 2016. "Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system," Energy, Elsevier, vol. 115(P1), pages 1022-1041.
    6. Mendoza-Vizcaino, Javier & Raza, Muhammad & Sumper, Andreas & Díaz-González, Francisco & Galceran-Arellano, Samuel, 2019. "Integral approach to energy planning and electric grid assessment in a renewable energy technology integration for a 50/50 target applied to a small island," Applied Energy, Elsevier, vol. 233, pages 524-543.
    7. Nojavan, Sayyad & Majidi, Majid & Esfetanaj, Naser Nourani, 2017. "An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management," Energy, Elsevier, vol. 139(C), pages 89-97.
    8. Abdelkafi, Achraf & Masmoudi, Abdelkarim & Krichen, Lotfi, 2018. "Assisted power management of a stand-alone renewable multi-source system," Energy, Elsevier, vol. 145(C), pages 195-205.
    9. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2017. "Generation and storage scheduling of combined heat and power," Energy, Elsevier, vol. 124(C), pages 693-705.

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