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Modelling of 4th generation district heating systems integrated with different thermal energy storage technologies – Methodology

Energy Conversion and Management, ISSN: 0196-8904, Vol: 276, Page: 116545
2023
  • 15
    Citations
  • 0
    Usage
  • 49
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    15
    • Citation Indexes
      15
  • Captures
    49
  • Mentions
    1
    • News Mentions
      1
      • 1

Most Recent News

Findings from Loughborough University Reveals New Findings on Energy Conversion and Management (Modelling of 4th Generation District Heating Systems Integrated With Different Thermal Energy Storage Technologies - Methodology)

2023 FEB 23 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Daily News -- Researchers detail new data in Energy - Energy Conversion

Article Description

A model was established that allows the simulation and analysis of the performance of a district heating (DH) system supplied with heat generated from renewable sources (RHS) and a selection of different types of thermal energy storage (TES) systems. The model uses hourly weather data, building specifications and occupancies to calculate i) hourly domestic heat demands for both space and domestic hot water heating and ii) hourly heat produced by RHS. The heat flow to and from sources to loads and TES systems is calculated on an hourly basis. The model calculates hourly heat losses from dwellings, TES and pipes, and takes into consideration recent research related to latent and thermochemical heat storage systems. The model developed enables the analysis of the effects of different district heating system operating parameters (including installed capacity and penetration of different RHS, thermal energy storage capacity, number and distribution of TES) on system cost and system energy efficiency. The ultimate goal of developing the model was the determination of a system specification and operating conditions that i) minimises cost and ii) maximises the overall energy efficiency of the network while ensuring that domestic heat demands are met on an hourly basis for a specified time-period in an existing or planned town or urban area.

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