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Optimal Dispatching of Smart Hybrid Energy Systems for Addressing a Low-Carbon Community

Author

Listed:
  • Wei Wu

    (Department of Chemical Engineering, National Cheng Kung University, Tainan 70101, Taiwan)

  • Shih-Chieh Chou

    (Department of Chemical Engineering, National Cheng Kung University, Tainan 70101, Taiwan)

  • Karthickeyan Viswanathan

    (Department of Chemical Engineering, National Cheng Kung University, Tainan 70101, Taiwan)

Abstract

A smart hybrid energy system (SHES) is presented using a combination of battery, PV systems, and gas/diesel engines. The economic/environmental dispatch optimization algorithm (EEDOA) is employed to minimize the total operating cost or total CO 2 emission. In the face of the uncertainty of renewable power generation, the constraints for loss-of-load probability (LOLP) and the operating reserve for the rechargeable battery are taken into account for compensating the imbalance between load demand and power supplies. The grid-connected and islanded modes of SHES are demonstrated to address a low-carbon community. For forecasting load demand, PV power, and locational-based marginal pricing (LBMP), the proper forecast model, such as long short-term memory (LSTM) or extreme gradient boosting (XGBoost), is implemented to improve the EEDOA. A few comparisons show that (i) the grid-connected mode of SHES is superior to the islanded-connected mode of SHES due to lower total operating cost and less total CO 2 -eq emissions, and (ii) the forecast-assisted EEDOA could effectively reduce total operating cost and total CO 2 -eq emissions of both modes of SHES as compared to no forecast-assisted EEDOA.

Suggested Citation

  • Wei Wu & Shih-Chieh Chou & Karthickeyan Viswanathan, 2023. "Optimal Dispatching of Smart Hybrid Energy Systems for Addressing a Low-Carbon Community," Energies, MDPI, vol. 16(9), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3698-:d:1132826
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