☆ 4.6 Article Proceedings Paper

Data-driven assessment for the supervision of District Heating Networks

ENERGY REPORTS (2022)

Data driven model for heat load prediction in buildings connected to District Heating by using smart heat meters

Mikel Lumbreras et al.

Summary: This paper introduces a data-driven model for characterizing and predicting heating demand in buildings connected to a District Heating network. The model utilizes various climatic variables, time factors, and data from smart meters to accurately forecast heat loads. With low computational cost and high accuracy, the model is suitable for deployment over large building datasets.

ENERGY (2022)

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Article Energy & Fuels

Use of smart meters as feedback for district heating temperature control

Hjorleifur G. Bergsteinsson et al.

Summary: Smart meters provide a new method for temperature control in district heating systems by estimating temperatures at artificial critical points using end-user data. This eliminates the need for physical critical points or sensors and increases control flexibility and accuracy.

ENERGY REPORTS (2021)

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Article Construction & Building Technology