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Control assessment in coupled local district heating and electrical distribution grids: Model predictive control of electric booster heaters

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  • Leitner, Benedikt
  • Widl, Edmund
  • Gawlik, Wolfgang
  • Hofmann, René

Abstract

Intelligent control schemes are essential for the implementation of smart energy systems, where district heating and electric networks are tightly interconnected. The increasing complexity of such networked infrastructure has resulted in the need to test and assess control algorithms before field deployment. This work presents a method to assess advanced control schemes for thermal-electric appliances with explicit consideration of coupled heat and power networks. It is based on closed loop simulation of high-fidelity physical system models, using dynamic thermal-hydraulic district heating and electric distribution network models, and low-fidelity time-discrete advanced control models. Co-simulation is used to perform coupled simulations of the different involved domains and tools. A test case is presented where a model predictive control scheme for grid friendly operation of domestic hot water electric booster heaters is implemented in a low-temperature district heating and low-voltage electric distribution network. Test case results show that the control is able to reduce peaks in district heating and electric networks compared to a simple reference controller. A comparison between using perfect and naive forecasts shows that control performance highly depends on the availability of accurate predictions. The results underline the versatility of the method to assess different control schemes in integrated networks.

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  • Leitner, Benedikt & Widl, Edmund & Gawlik, Wolfgang & Hofmann, René, 2020. "Control assessment in coupled local district heating and electrical distribution grids: Model predictive control of electric booster heaters," Energy, Elsevier, vol. 210(C).
  • Handle: RePEc:eee:energy:v:210:y:2020:i:c:s0360544220316480
    DOI: 10.1016/j.energy.2020.118540
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    References listed on IDEAS

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    Cited by:

    1. Hou, Juan & Li, Haoran & Nord, Natasa & Huang, Gongsheng, 2023. "Model predictive control for a university heat prosumer with data centre waste heat and thermal energy storage," Energy, Elsevier, vol. 267(C).
    2. Saloux, Etienne & Candanedo, José A., 2021. "Model-based predictive control to minimize primary energy use in a solar district heating system with seasonal thermal energy storage," Applied Energy, Elsevier, vol. 291(C).
    3. Lakshmanan, Venkatachalam & Sæle, Hanne & Degefa, Merkebu Zenebe, 2021. "Electric water heater flexibility potential and activation impact in system operator perspective – Norwegian scenario case study," Energy, Elsevier, vol. 236(C).
    4. Hermansen, Rune & Smith, Kevin & Thorsen, Jan Eric & Wang, Jiawei & Zong, Yi, 2022. "Model predictive control for a heat booster substation in ultra low temperature district heating systems," Energy, Elsevier, vol. 238(PA).
    5. Lizárraga-Morazán, Juan Ramón & Picón-Núñez, Martín, 2023. "Optimal sizing and control strategy of low temperature solar thermal utility systems," Energy, Elsevier, vol. 263(PC).

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