Monitoring and improving substation efficiency of District Heating System (DHS)
The urgent need for Europe to reduce energy dependence and improve self-reliance, together with the EU’s targets for greenhouse gas emission reductions by 2030, necessitates innovative approaches in the energy sector. This study focuses on district heating (DH) systems, which currently rely heavily...
| Autor: | |
|---|---|
| Formato: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/446057 |
| Acesso em linha: | https://hdl.handle.net/2117/446057 |
| Access Level: | acceso abierto |
| Palavra-chave: | Renewable energy sources Heat storage Energies renovables Calor--Emmagatzematge Àrees temàtiques de la UPC::Energies::Recursos energètics renovables |
| Resumo: | The urgent need for Europe to reduce energy dependence and improve self-reliance, together with the EU’s targets for greenhouse gas emission reductions by 2030, necessitates innovative approaches in the energy sector. This study focuses on district heating (DH) systems, which currently rely heavily on fossil fuels, accounting for approximately 90% of their energy source. A critical intervention identified is the reduction of distribution temperatures especially the return water temperature, which can significantly increase energy efficiency and promote the integration of renewable energy sources into the heating grid. Specifically, in Italy, it was found that the average return temperatures in DH networks exceed the optimal target of 50°C which is the requirement for the 3rd generation District heating system [17]. The research methodology included three phases: analysis of operational data from the local company data base platform, fault detection and diagnostics to figure out the problems, and the development of an automatic visualization tool, which has SQL-based database that refreshes automatically on a daily basis. A total of 172 substations were examined, revealing that 32 ex- hibited consistently high return temperatures at night. For confidentiality reasons, the names of substations have been redacted in this report. On-site evaluations of the five of the highest- temperature stations uncovered issues such as scaling, leaks, and customer-side setpoint tam- pering. The establishment of a digital platform not only minimized the necessity for physical in- spections but also facilitated enhanced monitoring and operational efficiency. This pilot project within the Cinisello network serves as a scalable optimization framework applicable across the wider portfolio of district heating networks. |
|---|