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Intelligent Demand Side Management for Exhaustive Techno-Economic Analysis of Microgrid System

Author

Listed:
  • Bishwajit Dey

    (Department of Electrical and Electronics Engineering, GIET University, Gunupur 765022, India)

  • Soham Dutta

    (Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India)

  • Fausto Pedro Garcia Marquez

    (Ingenium Research Group, Universidad Castilla-La Mancha, 13071 Ciudad Real, Spain)

Abstract

In a typical microgrid (MG) structure, the requisite of load varies from hour to hour. On the basis of the rise and fall of the load demand curve, the power system utilities fix the rate of electric power at different times of the day. This process is known as time-of-usage (TOU)-based pricing of electricity. The hourly basis load demand can be categorized into elastic hourly load demand and inelastic hourly load demand. For the duration of the peak hours, when the utility charges more, the elastic loads are shifted to low demand hours by the demand side management (DSM) to save the cost. This rebuilds the total demand model on the pillars of demand price elasticity. Keeping in view the fact that the total load in an hour in an MG structure consists of 10% to 40% of elastic loads, the paper proposes an intelligence-technique-based DSM to achieve reduction in the overall cost of using loads in an MG structure. Seven different cases are studied which cover diverse grid participation and electricity market pricing strategies, including DSM programs. The results obtained for all the MGs showcase the applicability and appropriateness of using the proposed DSM strategy in terms of cost savings.

Suggested Citation

  • Bishwajit Dey & Soham Dutta & Fausto Pedro Garcia Marquez, 2023. "Intelligent Demand Side Management for Exhaustive Techno-Economic Analysis of Microgrid System," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:1795-:d:1038933
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    References listed on IDEAS

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    1. Yang, Xiaohui & Leng, Zhengyang & Xu, Shaoping & Yang, Chunsheng & Yang, Li & Liu, Kang & Song, Yaoren & Zhang, Liufang, 2021. "Multi-objective optimal scheduling for CCHP microgrids considering peak-load reduction by augmented ε-constraint method," Renewable Energy, Elsevier, vol. 172(C), pages 408-423.
    2. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    3. Makbul A.M. Ramli & H.R.E.H. Bouchekara & Abdulsalam S. Alghamdi, 2019. "Efficient Energy Management in a Microgrid with Intermittent Renewable Energy and Storage Sources," Sustainability, MDPI, vol. 11(14), pages 1-28, July.
    4. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    5. Basu, M. & Chowdhury, A., 2013. "Cuckoo search algorithm for economic dispatch," Energy, Elsevier, vol. 60(C), pages 99-108.
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