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A collaborative voltage optimization utilizing flexibility of community heating systems for high PV penetration

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  • Shen, Lu
  • Dou, Xiaobo
  • Long, Huan
  • Li, Chen
  • Chen, Kang
  • Zhou, Ji

Abstract

The increasing penetration of photovoltaic generation exacerbates the risk of voltage violations in distribution networks. One viable tactic for increasing the flexibility of regional distribution networks is to use the thermal inertia of community heating systems (CHSs). However, the slow heat dynamics in the heating network brings difficulties in synchronous joint operation decisions of the integrated system. In this paper, we propose a novel power-to-temperature sensitivity model (PTSM), equating the whole CHS to a flexible electric load with thermodynamic characteristics. It denotes the direct relationship between the average water temperature change and the electric power consumed by ground-source heat pumps (GSHPs). A robust collaborative voltage optimization model is then developed from the perspective of power distribution system operators. The PTSM provides accurate prediction of CHS temperature variations to construct the operation constraints of GSHPs. This mixed integer programming problem is solved by the column-and-constraint generation algorithm. The test results of an actual residential community demonstrate that the PTSM can ensure the prediction errors of the CHS average temperature within ±0.4 °C in case of the optimal time resolution and aggregated heating load location. An IEEE 69-bus distribution network with several CHSs is studied to show that, the flexibility of CHSs can achieve an extra 17.25% reduction of the daily voltage deviation. The proposed method has significant advantages in computation time and robustness.

Suggested Citation

  • Shen, Lu & Dou, Xiaobo & Long, Huan & Li, Chen & Chen, Kang & Zhou, Ji, 2021. "A collaborative voltage optimization utilizing flexibility of community heating systems for high PV penetration," Energy, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012378
    DOI: 10.1016/j.energy.2021.120989
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    2. Wu, Hao & Xie, Yunyun & Xu, Yan & Wu, Qiuwei & Yu, Chen & Sun, Jinsheng, 2022. "Resilient scheduling of MESSs and RCs for distribution system restoration considering the forced cut-off of wind power," Energy, Elsevier, vol. 244(PB).

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