ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-02172020-120013


Tipo di tesi
Tesi di dottorato di ricerca
Autore
D'ETTORRE, FRANCESCO
URN
etd-02172020-120013
Titolo
Hybrid heat pump-gas boiler generators for heating applications - An integrated framework for optimal sizing, control and energy flexibility potential assessment
Settore scientifico disciplinare
ING-IND/10
Corso di studi
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Relatori
tutor Prof. Testi, Daniele
supervisore Prof. Grassi, Walter
Parole chiave
  • energy flexibility
  • thermal energy storage
  • energy efficiency
  • hybrid heat pumps
  • model predictive control
  • optimal control
  • demand response
Data inizio appello
24/02/2020
Consultabilità
Non consultabile
Data di rilascio
24/02/2090
Riassunto
The hybridisation of heat pumps with traditional gas boilers is an attractive solution to improve energy efficiency and reduce greenhouse gas emissions in the building sector, with only a limited impact on power grid infrastructure. To fully benefit from synergies between the two generators, a methodological framework for optimising their design has been developed, by integrating the optimal sizing and control problems. The methodology has been applied to an office building under different climate and economic scenarios. A strong impact of the control strategy on the hybrid system sizing, which appeared strongly depended on the kind of cooperation enabled between the heat pump and the gas boiler, has been shown. The effectiveness of the optimally designed hybrid heat pump to achieve lower operational costs (-42%) and primary energy consumption (-38%) with respect to a reference gas boiler scenario has also been highlighted. Finally, based on the results achieved, clear design guidelines for optimising the design of hybrid heat pump generators have been derived. To further investigate the potential offered by the hybrid system, its integration with a sensible thermal energy storage has been considered. A model predictive control framework has been developed to investigate to what extent the system can benefit from the implementation of load shifting strategies. Achievable cost savings (up to 8%) with respect to a traditional rule-based control strategy with no storage have been observed. A clear relation between the length of the prediction horizon and the introduced storage capacity has been shown.
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