A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to Households

Rogers, Austin; Ghosh, S.; Wilcock, Reuben; Jennings, Nicholas R.

doi:10.1145/2528282.2528284

Cited by 26 publications

(13 citation statements)

References 9 publications

(7 reference statements)

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“…In some papers (like [15]), it has been shown how it is possible to find the set point (goal temperature) of a house just by using its indoor temperature. It is used to measure the effect of lowering the set point of the house, and to estimate that to what extent a high set point affects the energy usage in a house.…”

Section: Discussion and Future Workmentioning

confidence: 99%

A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

Tabatabaei¹

2016

Proceedings of ICT for Sustainability 2016

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Abstract-Around one third of worldwide energy usage is for the residential section and 60% of the energy consumption in this domestic area is for space heating. Therefore, monitoring and controlling this part of energy usage can have a major effect on the overall energy consumption and also on the emission of green house gases. Smart thermostats can play an important role in achieving more economic energy usage in the residential section. This paper shows an innovative way to use data collected by a relatively simple thermostat to estimate the thermal properties of a building. Moreover, it will be shown that in case of malfunctioning and high usage, this method can be used to firstly find out that there is a problem, and also to identify the cause of the problem. This information can be used as feedback to the resident to help him or her to discover the problem, and also point at the cause of it. Applying this idea in a smart thermostat or a mobile application with access to the data gathered by a simple thermostat can encourage residents to limit their energy usage for space heating. And in case of a problem that leads to an increase in energy usage, it can understand its occurrence and diagnose the cause.

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Section: Discussion and Future Workmentioning

confidence: 99%

A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

Tabatabaei¹

2016

Proceedings of ICT for Sustainability 2016

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“…Calculations by Tommerup et al [15] based on single-family houses in Denmark revealed that the increase in energy consumption is about 10% per degree of indoor temperature. Some papers (e.g., [16]) show that it is possible to provide advice on the optimal set point for a house based on data of the indoor temperature only. The method measures the effect of lowering the set point of the houses and to what extent a high set point affects the energy usage in a house.…”

Section: Energy Usage For Heating Buildingsmentioning

confidence: 99%

“…Joulo [16] uses a model-based approach for providing advice about the thermal characteristics of a house. It does not use data of consumption of the heating system in the calculations but only indoor temperatures.…”

Section: Related Productsmentioning

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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“…Power TAC's research goals include using autonomous agents for the benefit of sustainable energy, and therefore, in addition to the areas shown in Figure 1, it also falls within the area of computational sustainability. The literature on computational energy sustainability has been growing rapidly and includes applications such as smart home heating, micro-storage management, wind forecasting, wind turbine optimization, energy disaggregation, solar tracking, electric vehicle charging and others [89,122,121,40,119,21,128,61,60,59,38,129,54,53,55,52,70,41,117].…”

Section: Related Workmentioning

confidence: 99%

Autonomous trading in modern electricity markets

Urieli

2016

AI Matters

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The smart grid is envisioned to be a main enabler of sustainable, clean, efficient, reliable, and secure energy supply (U.S. Department of Energy, 2003). One of the milestones in the smart grid vision will be programs for customer participation in electricity markets through demand-side management and distributed generation; electricity markets will incentivize customers to adapt their demand to supply conditions, which will help to utilize intermittent energy resources such as from solar and wind, and to reduce peak-demand.

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A Scalable Low-Cost Solution to Provide Personalised Home Heating Advice to Households

Cited by 26 publications

References 9 publications

A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

A Data Analysis Approach for Diagnosing Malfunctioning in Domestic Space Heating

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

Autonomous trading in modern electricity markets

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