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An efficient way to schedule dispersed generators for a microgrid system's economical operation under various power market conditions and grid involvement

Author

Listed:
  • Srikant Misra

    (GIET University)

  • P. K. Panigrahi

    (GIET University)

  • Bishwajit Dey

    (IIT (Indian School of Mines)
    Adani University, Shantigram)

Abstract

A microgrid is a collection of distributed energy resources (DERs) It might encompass both traditional and unconventional energy sources. The way a microgrid functions determines whether it is categorized as either islanded or grid-connected. The focus of this study is to explore five different optimal scheduling operation scenarios for Distributed Energy Resources (DERs) with the aim of achieving economic benefits for a low voltage microgrid system. The scenarios being studied are developed using several approaches to grid participation and pricing strategies within the power market. The optimization tool used in the research was the Crow Search Algorithm (CSA), a widely recognized and recently developed algorithm known for its speed and efficiency. The results of the study indicate that the microgrid's most profitable operational scenario involved active participation of the grid in the purchase and sale of electricity, utilizing a dynamic pricing approach based on time-of-usage (TOU). Based on numerical data, the Crow Search Algorithm method produced solutions of superior quality in less time compared to several other algorithms with similar designs that were employed in the study. The CSA approach was able to achieve this consistently, regardless of the scale of the problem being addressed.

Suggested Citation

  • Srikant Misra & P. K. Panigrahi & Bishwajit Dey, 2023. "An efficient way to schedule dispersed generators for a microgrid system's economical operation under various power market conditions and grid involvement," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1799-1809, October.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:5:d:10.1007_s13198-023-01983-4
    DOI: 10.1007/s13198-023-01983-4
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    References listed on IDEAS

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    1. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    2. Dai, Wei & Yang, Zhifang & Yu, Juan & Cui, Wei & Li, Wenyuan & Li, Jinghua & Liu, Hui, 2021. "Economic dispatch of interconnected networks considering hidden flexibility," Energy, Elsevier, vol. 223(C).
    3. Roy, Sanjoy, 2018. "The maximum likelihood optima for an economic load dispatch in presence of demand and generation variability," Energy, Elsevier, vol. 147(C), pages 915-923.
    4. Yuan, Xiaohui & Su, Anjun & Yuan, Yanbin & Nie, Hao & Wang, Liang, 2009. "An improved PSO for dynamic load dispatch of generators with valve-point effects," Energy, Elsevier, vol. 34(1), pages 67-74.
    5. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    6. Toopshekan, Ashkan & Yousefi, Hossein & Astaraei, Fatemeh Razi, 2020. "Technical, economic, and performance analysis of a hybrid energy system using a novel dispatch strategy," Energy, Elsevier, vol. 213(C).
    7. Singh, Diljinder & Dhillon, J.S., 2019. "Ameliorated grey wolf optimization for economic load dispatch problem," Energy, Elsevier, vol. 169(C), pages 398-419.
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