A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

Tabatabaei, Seyed Amin

doi:10.2991/ict4s-16.2016.2

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…One option is to provide feedback about thermal characteristics and the functioning of the heating system. By monitoring the estimated characteristic of the house over time, a probable malfunctioning in the heating system [29] can be distinguished from a high loss rate due to house characteristics. In the first case, a warning can be provided to check the heating system, while, in the latter case, advice can be given to check the frame of doors and windows for unwanted infiltrations.…”

Section: Discussionmentioning

confidence: 99%

A Data Analysis Technique to Estimate the Thermal Characteristics of a House

Tabatabaei

Ham²,

Klein

et al. 2017

Energies

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Almost one third of the energy is used in the residential sector, and space heating is the largest part of energy consumption in our houses. Knowledge about the thermal characteristics of a house can increase the awareness of homeowners about the options to save energy, for example by showing that there is room for improvement of the insulation level. However, calculating the exact value of these characteristics is not possible without precise thermal experiments. In this paper, we propose a method to automatically estimate two of the most important thermal characteristics of a house, i.e., the loss rate and the heat capacity, based on collected data about the temperature and gas usage. The method is evaluated with a data set that has been collected in a real-life case study. Although a ground truth is lacking, the analyses show that there is evidence that this method could provide a feasible way to estimate those values from the thermostat data. More detailed data about the houses in which the data was collected is required to draw stronger conclusions. We conclude that the proposed method is a promising way to add energy saving advice to smart thermostats.

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Section: Discussionmentioning

confidence: 99%

A Data Analysis Technique to Estimate the Thermal Characteristics of a House

Tabatabaei

Ham²,

Klein

et al. 2017

Energies

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Comparing Gray Box Methods to Derive Building Properties from Smart Thermostat Data

Baasch

Wicikowski

Faure

et al. 2019

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

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Digitalization and sustainability: A systematic literature analysis of ICT for Sustainability research

Santarius¹,

Wagner²

2023

GAIA - Ecological Perspectives for Science and Society

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Close scrutiny of the ICT for Sustainability conference proceedings on digitalization and sustainability reveals a bias on (technological) efficiency solutions. This bias is mirrored in blind spots in the public discourse and the political debate. The sustainable transformation of society calls for more comprehensive research ‐ and research funding ‐ to fill the gaps and integrate efficiency, consistency, and sufficiency strategies on the levels of life-cycle, enabling, and structural effects.In order to govern processes of digitalization for the purpose of the common good, it is important to understand the opportunities and risks of information and communications technology (ICT) for a sustainable transformation of society. In this article, we systematically review 215 publications from the ICT for Sustainability (ICT4S) conference corpus in order to investigate the state of debate. We analyze to what extent research covers sustainability implications of ICT, 1. regarding different levels of actions and effects, as well as 2. regarding the three different strategies of sustainability ‐ efficiency, consistency, and sufficiency. We find that ICT4S research has a one-sided focus on digital efficiency improvements and on life-cycle impacts of ICT devices and applications. There is far less research on digitalization’s potential to advance sufficiency-oriented practices, and questions of how to foster digital sustainability transformations at macro- and structural level are only marginally treated. We draw conclusions for funding and science politics.

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A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

Cited by 3 publications

References 15 publications

A Data Analysis Technique to Estimate the Thermal Characteristics of a House

A Data Analysis Technique to Estimate the Thermal Characteristics of a House

Comparing Gray Box Methods to Derive Building Properties from Smart Thermostat Data

Digitalization and sustainability: A systematic literature analysis of ICT for Sustainability research

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