District heating networks have become widespread due to their ability to distribute thermal energy efficiently, which leads to reduced carbon emissions and improved air quality. Additional benefits can derive from novel demand side management strategies, which can efficiently balance demand and supply. However, their implementation requires detailed knowledge of heating network characteristics, which vary remarkably depending on urban layout and system amplitude. Moreover, extensive data about the energy distribution and thermal capacity of different areas are seldom available. For this purpose, the present work proposes a novel procedure to develop a fast scale-free model of large-scale district heating networks for system optimization and control. Each network community is represented and modeled as an aggregated region. Its physics-based model is identified starting from a limited amount of data available at the main substations and includes heat capacity and heat loss coefficients. The procedure is demonstrated and validated on the network of Västerås, Sweden, showing results that are in agreement with data from the literature. Thus, the model is well suited for real-time optimization and predictive control. In particular, the possibility to easily estimate the heat storage potential of network communities allows demand side management solutions to be applied in several conditions.

A control-oriented scalable model for demand side management in district heating aggregated communities / Saletti, C.; Zimmerman, N.; Morini, M.; Kyprianidis, K.; Gambarotta, A.. - In: APPLIED THERMAL ENGINEERING. - ISSN 1359-4311. - 201:(2022), p. 117681.117681. [10.1016/j.applthermaleng.2021.117681]

A control-oriented scalable model for demand side management in district heating aggregated communities

Saletti C.;Morini M.;Gambarotta A.
2022-01-01

Abstract

District heating networks have become widespread due to their ability to distribute thermal energy efficiently, which leads to reduced carbon emissions and improved air quality. Additional benefits can derive from novel demand side management strategies, which can efficiently balance demand and supply. However, their implementation requires detailed knowledge of heating network characteristics, which vary remarkably depending on urban layout and system amplitude. Moreover, extensive data about the energy distribution and thermal capacity of different areas are seldom available. For this purpose, the present work proposes a novel procedure to develop a fast scale-free model of large-scale district heating networks for system optimization and control. Each network community is represented and modeled as an aggregated region. Its physics-based model is identified starting from a limited amount of data available at the main substations and includes heat capacity and heat loss coefficients. The procedure is demonstrated and validated on the network of Västerås, Sweden, showing results that are in agreement with data from the literature. Thus, the model is well suited for real-time optimization and predictive control. In particular, the possibility to easily estimate the heat storage potential of network communities allows demand side management solutions to be applied in several conditions.
2022
A control-oriented scalable model for demand side management in district heating aggregated communities / Saletti, C.; Zimmerman, N.; Morini, M.; Kyprianidis, K.; Gambarotta, A.. - In: APPLIED THERMAL ENGINEERING. - ISSN 1359-4311. - 201:(2022), p. 117681.117681. [10.1016/j.applthermaleng.2021.117681]
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S1359431121011066-main.pdf

non disponibili

Tipologia: Versione (PDF) editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 3.57 MB
Formato Adobe PDF
3.57 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Paper_Vasteras_Part1_ATE_R1.pdf

Open Access dal 17/10/2023

Tipologia: Documento in Post-print
Licenza: Creative commons
Dimensione 1.2 MB
Formato Adobe PDF
1.2 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2904971
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 12
  • ???jsp.display-item.citation.isi??? 7
social impact