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Distributed Generation and Load Modeling in Microgrids

Author

Listed:
  • Mohammad AlMuhaini

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

  • Abass Yahaya

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

  • Ahmed AlAhmed

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia)

Abstract

Solar PV and wind energy are the most important renewable energy sources after hydroelectric energy with regard to installed capacity, research spending and attaining grid parity. These sources, including battery energy storage systems, and well-established load modeling have been pivotal to the success of the planning and operation of electric microgrids. One of the major challenges in modeling renewable-based DGs, battery storage, and loads in microgrids is the uncertainty of modeling their stochastic nature, as the accuracy of these models is significant in the planning and operation of microgrids. There are several models in the literature that model DG and battery storage resources for microgrid applications, and selecting the appropriate model is a challenging task. Hence, this paper examines the most common models of the aforementioned distributed energy resources and loads and delineates the mathematical rigor required for characterizing the models. Several simulations are conducted to demonstrate model performance using manufacturers’ datasheets and actual atmospheric data as inputs.

Suggested Citation

  • Mohammad AlMuhaini & Abass Yahaya & Ahmed AlAhmed, 2023. "Distributed Generation and Load Modeling in Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4831-:d:1091680
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    References listed on IDEAS

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    1. Camilo I. Martínez-Márquez & Jackson D. Twizere-Bakunda & David Lundback-Mompó & Salvador Orts-Grau & Francisco J. Gimeno-Sales & Salvador Seguí-Chilet, 2019. "Small Wind Turbine Emulator Based on Lambda-Cp Curves Obtained under Real Operating Conditions," Energies, MDPI, vol. 12(13), pages 1-17, June.
    2. Andrew Kusiak, 2016. "Renewables: Share data on wind energy," Nature, Nature, vol. 529(7584), pages 19-21, January.
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    Cited by:

    1. Ozcel Cangul & Roberto Rocchetta & Murat Fahrioglu & Edoardo Patelli, 2023. "Optimal Allocation and Sizing of Decentralized Solar Photovoltaic Generators Using Unit Financial Impact Indicator," Sustainability, MDPI, vol. 15(15), pages 1-24, July.

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