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Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China

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  • Zhou, Jianguo
  • Xu, Zhongtian

Abstract

This paper proposes an optimal sizing design and cost-benefit evaluation framework for stand-alone renewable microgrid system to serve rural community load usage in Northeast China. The microgrid system combines Photovoltaic arrays (PV), Wind turbines (WT), Tidal turbines (Tid), Battery (Bat) storage and hydrogen storage, respectively. The optimal component sizing is determined based on the actual local hourly meteorological data and load demand during a year using Chameleon swarm algorithm (CSA), with minimum Total net present cost (TNPC) of the microgrid system as the optimization objective and the reliability constraint is considered as Loss of power supply probability (LPSP). Meanwhile, a cost-benefit index is further introduced for conveniently evaluating the overall effectiveness of the microgrid systems. The results of the simulation experiments under the benchmark scenario reveal that the PV/WT/Tid/Bat system is the most viable approach for local load supply among different versions of the microgrid. Additionally, a thorough sensitivity investigation of the optimal sizing of two exemplary microgrid systems based on different energy storage is carried out under different techno-economic scenarios. This study can provide a more efficient and clean electrification scheme and insightful reference for investment in the power-starved Northeast China.

Suggested Citation

  • Zhou, Jianguo & Xu, Zhongtian, 2023. "Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China," Renewable Energy, Elsevier, vol. 202(C), pages 1110-1137.
    • Handle: RePEc:eee:renene:v:202:y:2023:i:c:p:1110-1137
    DOI: 10.1016/j.renene.2022.12.005
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    2. Kassab, Fadi Agha & Celik, Berk & Locment, Fabrice & Sechilariu, Manuela & Liaquat, Sheroze & Hansen, Timothy M., 2024. "Optimal sizing and energy management of a microgrid: A joint MILP approach for minimization of energy cost and carbon emission," Renewable Energy, Elsevier, vol. 224(C).
    3. Álvarez-Arroyo, César & Vergine, Salvatore & de la Nieta, Agustín Sánchez & Alvarado-Barrios, Lázaro & D’Amico, Guglielmo, 2024. "Optimising microgrid energy management: Leveraging flexible storage systems and full integration of renewable energy sources," Renewable Energy, Elsevier, vol. 229(C).
    4. Zhao, Anjun & Jiao, Yang & Quan, Wei & Chen, Yiren, 2024. "Net zero carbon rural integrated energy system design optimization based on the energy demand in temporal and spatial dimensions," Renewable Energy, Elsevier, vol. 222(C).
    5. Spyridon Chapaloglou & Babak Abdolmaleki & Elisabetta Tedeschi, 2023. "Optimal Generation Capacity Allocation and Droop Control Design for Current Sharing in DC Microgrids," Energies, MDPI, vol. 16(12), pages 1-17, June.
    6. Güven, Aykut Fatih, 2024. "Integrating electric vehicles into hybrid microgrids: A stochastic approach to future-ready renewable energy solutions and management," Energy, Elsevier, vol. 303(C).

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