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

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 de...

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Veröffentlicht in:Energy (Oxford) 2020-11, Vol.210, p.118540, Article 118540
Hauptverfasser: Leitner, Benedikt, Widl, Edmund, Gawlik, Wolfgang, Hofmann, René
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Sprache:eng
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Zusammenfassung: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. •Closed-loop simulation of dynamic heat and power network models with advanced control.•Introduction of grid-friendly model predictive control for electric booster heaters.•Example heat and power networks with multiple distributed electric booster heaters.•Performance comparison of perfect and naive forecasting.•Results show reduced peaks in heat and power network and high self-consumption of PV.
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2020.118540