Champion the energy data revolution

Webborn, Ellen; Oreszczyn, Tadj

doi:10.1038/s41560-019-0432-0

Cited by 17 publications

(10 citation statements)

References 7 publications

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“…Quantitatively speaking, the contribution of ICTs would range between 0.23 and 3.3% of the European CO 2 reduction target with respect to the 1.5°C minimal realistic warming goal at 2100. Smart metering has the potential to revolutionize access to energy consumption data but, as highlighted by (Webborn and Oreszczyn, 2019), a coordinated effort is needed between legislation, funding bodies and researchers to unlock its potential. From this perspective, the European Union issued Directives 2009/72/EC, 2009/73/EC, and Directive 2012/27/EC that insisted on making smart meters available to the majority of households in the EU by 2020.…”

Section: Smart Metersmentioning

confidence: 99%

How Smart is the Grid?

Cascio

Girardin

et al. 2021

Front. Energy Res.

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Ancient Romans called urbs the set of buildings and infrastructures, and civitas the Roman citizens. Today instead, while the society is surfing the digital tsunami, urbs and civitas tend to become much closer, almost merging, that we might attempt to condensate these into a single concept: smart grid. Internet of things, artificial intelligence, blockchain, and quantum cryptography are only a few of the technologies that are likely to contribute to determining the final portrait of the future smart grid. However, to understand the effective sustainability of complex grids, specific tools are required. To this end, in this article, a new taxonomic framework has been developed starting from a general analysis of the emerging solutions, identifying intersectoral synergies and limitations with respect to the ‘smart grid’ concept. Finally, from the scenario portrayed, a set of issues involving engineering, regulation, security, and social frameworks have been derived in a theoretical fashion. The findings are likely to suggest the urgent need for multidisciplinary cooperation to address engineering and ontological challenges gravitating around the smart grid concept.

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Section: Smart Metersmentioning

confidence: 99%

How Smart is the Grid?

Cascio

Girardin

et al. 2021

Front. Energy Res.

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“…In Sections 5.2 and 5.3 we present the results from the harmonized survey questions and discuss the representativeness of the SERL sample. The supplementary files contain a table showing the frequencies of each response option to the survey questions (merged or rounded where necessary for statistical disclosure control 5 ). The survey data-related documentation in the supplementary files are:…”

Section: Survey Datamentioning

confidence: 99%

“…Identifying households in fuel poverty, or those at risk of missing out on green policy incentives, would help to ensure a just transition that benefits sections of society who might otherwise be left behind [4]. To understand these and other related issues, a nationallyrepresentative empirical database of building, occupant and high-resolution energy data is imperative [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

“…Various additional data, such as indoor temperatures, weather, demographic information, and EPC data are also included with some datasets. However, what has previously been lacking for UK researchers is a large, nationally representative, longitudinal sample with contextual data linked at the household level [5], [16]. The SERL Observatory is also unique in collecting data before, during and after COVID-19 lockdowns, which allows for the impact and potential development of a 'new normal' to be investigated.…”

Section: Introductionmentioning

confidence: 99%

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The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for Over 13,000 GB Households

Webborn¹,

Few²,

McKenna³

et al. 2021

Preprint

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The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes was collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data was collected, the variables available and the representativeness of the sample compared to national estimates. It is intended as a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it.

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“…Managing increases and time shifts in energy demand from the electrification of heat and transport will become increasingly important as electrification becomes more mainstream [3]. Such challenges call for a strong, nationally-representative empirical evidence base of high-resolution energy, building and occupant data [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Increasing response rates and improving research design: Learnings from the Smart Energy Research Lab in the United Kingdom

Webborn

McKenna

Elam

et al. 2022

Energy Research & Social Science

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Highlights:-We test recruitment strategies to improve response to a smart energy meter study -A conditional monetary incentive increases response and reduces sample bias -A push-to-web approach reduces response but significantly increases online sign up -Multiple reminders are useful but a 4 th mailing is unlikely to be cost-effective -Motivational headlines and message structure impact response rates

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Champion the energy data revolution

Cited by 17 publications

References 7 publications

How Smart is the Grid?

How Smart is the Grid?

The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for Over 13,000 GB Households

Increasing response rates and improving research design: Learnings from the Smart Energy Research Lab in the United Kingdom

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