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Bi-Layer Planning of Integrated Energy System by Incorporating Power-to-Gas and Ground Source Heat Pump for Curtailed Wind Power and Economic Cost Reduction

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  • Tingling Wang

    (School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Tianyu Huo

    (School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Huihang Li

    (School of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

Abstract

The popularization of renewable energy is limited by wasteful problems such as curtailed wind power and high economic costs. To tackle these problems, we propose a bi-layer optimal planning model with the integration of power to gas and a ground source heat pump for the existing integrated energy system. Firstly, the inner layer optimizes the daily dispatch of the system, with the minimum daily operation cost including the penalty cost of curtailed wind power. Then, the enumeration method of outer-layer optimization determines the device capacity of various schemes. After that, optimal planning can be achieved with the minimum daily comprehensive cost. The result of this example shows that the improved system can reduce curtailed wind power and system costs, thus improving the overall economy. Finally, the influences of algorithms and gas prices on planning optimization are studied.

Suggested Citation

  • Tingling Wang & Tianyu Huo & Huihang Li, 2024. "Bi-Layer Planning of Integrated Energy System by Incorporating Power-to-Gas and Ground Source Heat Pump for Curtailed Wind Power and Economic Cost Reduction," Energies, MDPI, vol. 17(6), pages 1-22, March.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1447-:d:1358700
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    References listed on IDEAS

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    Cited by:

    1. Laugs, Gideon A.H. & Benders, René M.J. & Moll, Henri C., 2024. "Maximizing self-sufficiency and minimizing grid interaction: Combining electric and molecular energy storage for decentralized balancing of variable renewable energy in local energy systems," Renewable Energy, Elsevier, vol. 229(C).

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