Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data

Weigert, Andreas; Hopf, Konstantin; Günther, Sebastian A.; Staake, Thorsten

doi:10.1016/j.enpol.2022.113156

Cited by 9 publications

(4 citation statements)

References 41 publications

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“…In the same literature analysis, there were recent studies that investigated how the socio-political environment characteristics could affect consumption; for example, in [11], using fixed effects, the impact of federal policies on smart meter use in the United States was considered, and an energy efficiency campaign in Switzerland [22] was estimated.…”

Section: Fixed Effects Methodology and Consumption Within The Householdmentioning

confidence: 99%

Analysis and Modeling of Residential Energy Consumption Profiles Using Device-Level Data: A Case Study of Homes Located in Santiago de Chile

Verdejo,

Fucks Jara,

Castillo

et al. 2023

Sustainability

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The advancement of technology has significantly improved energy measurement systems. Recent investment in smart meters has enabled companies and researchers to access data with the highest possible temporal disaggregation, on a minute-by-minute basis. This research aimed to obtain data with the highest possible temporal and spatial disaggregation. This was achieved through a process of energy consumption measurements for six devices within seven houses, located in different communes (counties) of the Metropolitan Region of Chile. From this process, a data panel of energy consumption of six devices was constructed for each household, observed in two temporal windows: one quarterly (750,000+ observations) and another semi-annual (1,500,000+ observations). By applying a panel data econometric model with fixed effects, calendar-temporal patterns that help explain energy consumption in each of these two windows have been studied, obtaining explanations of over 80% in some cases, and very low in others. Sensitivity analyses show that the results are robust in a short-term temporal horizon and provide a practical methodology for analyzing energy consumption determinants and load profiles with panel data. Moreover, to the authors’ knowledge, these are the first results obtained with data from Chile. Therefore, the findings provide key information for the planning of production, design of energy market mechanisms, tariff regulation, and other relevant energy policies, both at local and global levels.

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Section: Fixed Effects Methodology and Consumption Within The Householdmentioning

confidence: 99%

Analysis and Modeling of Residential Energy Consumption Profiles Using Device-Level Data: A Case Study of Homes Located in Santiago de Chile

Verdejo,

Fucks Jara,

Castillo

et al. 2023

Sustainability

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“…Our smart meter data combine high temporal resolution data with a limited sample size, rendering the evaluation of field experiments suitable for panel data regressions. While several scholars successfully identified energy savings and related determinants based on panel data regressions [17][18][19], it has rarely been applied to self-consumption. Thus, a linear panel data regression with random effects is conducted to analyze the effect of (national-level) Google Trends for "electricity" on the participants' self-consumption, controlling for the applied nudging treatments and the solar radiation in the city of Mannheim.…”

Section: B Analytical Strategymentioning

confidence: 99%

Self-consumption rises due to energy crises? An evaluation of prosumers’ consumption behavior in 2022

Pelka

Conradie

Vries

et al. 2023

2023 19th International Conference on the European Energy Market (EEM)

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Prosumers with photovoltaic systems can reduce their electricity expenses by increasing their consumption of selfgenerated electricity. This makes them more resilient to price shocks, like the 2022 European energy crisis. We evaluate how prosumers adapt their consumption behavior in response to such political uncertainty and increasing electricity prices. The collected survey and smart meter data allow us to evaluate the perceived selfreported and measured impact on self-consumption. Saving intentions due to the energy crisis are more clearly displayed by the survey than by the measured self-consumption. While solar radiation predominantly explains self-consumption changes, Google searches on electricity-related topics have limited explanatory power. However, considering time lags and the interaction with solar radiation leads to more nuanced insights on the effect of Google searches. Depending on the level of solar radiation, the effect of Google searches ranges from decreasing the daily self-consumption by 26.45 Wh to increasing it by 69.45 Wh.

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“…space or water heating) (Hopf et al 2018). It was also shown that smart meter data could improve the efficacy of energy conservation campaigns if used to pre-select heat pump installations (Weigert et al 2022).…”

Section: Sensor Datamentioning

confidence: 99%

“…With a particular focus on heat pumps, several works demonstrated that smart meter data could be used to predict basic characteristics of heat pumps (e.g. Fei et al 2013;Hopf et al 2018;Weigert et al 2020;Brudermueller et al 2022) and even recognise heat pumps with a high saving potential (Weigert et al 2022). This study goes one step further and uses the empirical insights from on-site visits and answer the following research question: RQ2: How can heat pump owners recognise heat pump problems, and how can information systems (i.e.…”

Section: Introductionmentioning

confidence: 99%

Identification and classification of heat pump problems in the field and their implication for a user-centric problem recognition

Weigert

2022

Energy Inform

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Heat pumps are at the heart of the transition to sustainable heating in buildings. Yet, minor installation and setting errors add to unnoticed performance drops over the system’s lifetime. With the advent of smart meters that constantly measure electricity consumption, data patterns of heat pumps have become available, even for the many not connected to the Internet. These data hold the potential to monitor heat pumps continuously, identify issues, and thus assist energy consultants and heat pump owners in lifting hidden conservation potential. Yet, research and practice lack an overview of specific problems that could help in this task. In a mixed-method approach, this study investigated 228 protocols of on-site heat pump inspections in Switzerland and found 47 problem classes with varying frequencies. Based on this empirical data and expert interviews, a classification scheme for heat pump issues is proposed and validated. It uncovers the cause of problems, how and by whom they can be recognised and solved, and potential benefits. The work demonstrates that (i) several problems are likely to create smart meter patterns and that (ii) heat pump owners could be involved in the problem recognition and solving process if they get guidance (i.e. simple rules and instructions). Finally, this study discusses implications for developing information systems to automate and assist the recognition and solving of problems. Such information systems may raise not only the attention of heat pump owners but also trigger desired actions (i.e. request consultancy, inspect heat pump themselves).

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Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data

Cited by 9 publications

References 41 publications

Analysis and Modeling of Residential Energy Consumption Profiles Using Device-Level Data: A Case Study of Homes Located in Santiago de Chile

Analysis and Modeling of Residential Energy Consumption Profiles Using Device-Level Data: A Case Study of Homes Located in Santiago de Chile

Self-consumption rises due to energy crises? An evaluation of prosumers’ consumption behavior in 2022

Identification and classification of heat pump problems in the field and their implication for a user-centric problem recognition

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