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A regional power grid operation and planning method considering renewable energy generation and load control

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  • Zeng, Yuan
  • Zhang, Ruiwen
  • Wang, Dong
  • Mu, Yunfei
  • Jia, Hongjie

Abstract

The active development and application of renewable energy, such as wind power and solar power, has become an inevitable tendency, which will promote the increase of the proportion of renewable energy generation accordingly in regional power grids. The intermission and randomness of renewable energy generation lead to enormous challenges in the operation and planning of power systems. One of the current methods to accommodate and reduce renewable energy fluctuation is conventional storage devices, e.g. battery energy storage devices, but this approach has the limitation of a high operating cost, which hinders the technology from popularizing. We present a novel load control algorithm employing the technology of residential thermostatically controlled appliances to maximize renewable energy usage in regional power grids. The thermal dynamics of the thermostatically controlled loads are modeled as a simplified first-order equivalent thermal parameter model. The new load control algorithm, based on the state-queueing model with modified colored power algorithm, is developed to manage activities of residential thermostatically controlled appliances, which allows customers to set different colors as the response levels of their appliances. Such an algorithm can ensure both the comfort level and the fairness of customers. Both a practical case and a real case are applied to demonstrate the effectiveness and practicability of the proposed algorithm.

Suggested Citation

  • Zeng, Yuan & Zhang, Ruiwen & Wang, Dong & Mu, Yunfei & Jia, Hongjie, 2019. "A regional power grid operation and planning method considering renewable energy generation and load control," Applied Energy, Elsevier, vol. 237(C), pages 304-313.
    • Handle: RePEc:eee:appene:v:237:y:2019:i:c:p:304-313
    DOI: 10.1016/j.apenergy.2019.01.016
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    8. Chen, C.Q. & Diao, Y.H. & Zhao, Y.H. & Ji, W.H. & Wang, Z.Y. & Liang, L., 2019. "Thermal performance of a thermal-storage unit by using a multichannel flat tube and rectangular fins," Applied Energy, Elsevier, vol. 250(C), pages 1280-1291.
    9. Song, Yuguang & Chen, Fangjian & Xia, Mingchao & Chen, Qifang, 2022. "The interactive dispatch strategy for thermostatically controlled loads based on the source–load collaborative evolution," Applied Energy, Elsevier, vol. 309(C).
    10. Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.
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    12. Hosseinnia, Hamed & Modarresi, Javad & Nazarpour, Daryoush, 2020. "Optimal eco-emission scheduling of distribution network operator and distributed generator owner under employing demand response program," Energy, Elsevier, vol. 191(C).

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