The SERL Observatory Dataset: Longitudinal Smart Meter Electricity and Gas Data, Survey, EPC and Climate Data for over 13,000 Households in Great Britain
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Jenkins, David & Simpson, Sophie & Peacock, Andrew, 2017. "Investigating the consistency and quality of EPC ratings and assessments," Energy, Elsevier, vol. 138(C), pages 480-489.
- Jacqueline Nicole Adams & Zsófia Deme Bélafi & Miklós Horváth & János Balázs Kocsis & Tamás Csoknyai, 2021. "How Smart Meter Data Analysis Can Support Understanding the Impact of Occupant Behavior on Building Energy Performance: A Comprehensive Review," Energies, MDPI, vol. 14(9), pages 1-23, April.
- Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
- Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
- Jenny Crawley & Phillip Biddulph & Paul J. Northrop & Jez Wingfield & Tadj Oreszczyn & Cliff Elwell, 2019. "Quantifying the Measurement Error on England and Wales EPC Ratings," Energies, MDPI, vol. 12(18), pages 1-19, September.
- Ellen Webborn & Tadj Oreszczyn, 2019. "Champion the energy data revolution," Nature Energy, Nature, vol. 4(8), pages 624-626, August.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Ajayi, Victor & Andrew Burlinson, Andrew & Giulietti, Monica & Waterson, Michael, 2024.
"The impact of the energy price crisis on GB consumers : a difference-in-difference experiment,"
The Warwick Economics Research Paper Series (TWERPS)
1523, University of Warwick, Department of Economics.
- Ajayi, Victor & Burlinson, Andrew & Giulietti, Monica & Waterson, Michael, 2024. "The impact of the energy price crisis on GB consumers: a difference-in-difference experiment," CAGE Online Working Paper Series 727, Competitive Advantage in the Global Economy (CAGE).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Lesley Thomson & David Jenkins, 2023. "The Use of Real Energy Consumption Data in Characterising Residential Energy Demand with an Inventory of UK Datasets," Energies, MDPI, vol. 16(16), pages 1-29, August.
- Jenny Crawley & Despina Manouseli & Peter Mallaburn & Cliff Elwell, 2022. "An Empirical Energy Demand Flexibility Metric for Residential Properties," Energies, MDPI, vol. 15(14), pages 1-18, July.
- Boza, Pal & Evgeniou, Theodoros, 2021. "Artificial intelligence to support the integration of variable renewable energy sources to the power system," Applied Energy, Elsevier, vol. 290(C).
- Cheng, Meng & Sami, Saif Sabah & Wu, Jianzhong, 2017. "Benefits of using virtual energy storage system for power system frequency response," Applied Energy, Elsevier, vol. 194(C), pages 376-385.
- McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
- Daví-Arderius, Daniel & Sanin, María-Eugenia & Trujillo-Baute, Elisa, 2017.
"CO2 content of electricity losses,"
Energy Policy, Elsevier, vol. 104(C), pages 439-445.
- Daniel Daví Arderius & María-Eugenia Sanin & Elisa Trujillo-Baute, 2016. "CO2 Content of Electricity Losses," Documents de recherche 16-08, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
- Daniel Daví-Arderius & María-Eugenia Sanin & Elisa Trujillo-Baute, 2016. "Co2 content of electricity losses," Working Papers 2016/23, Institut d'Economia de Barcelona (IEB).
- Daniel Davi-Arderius & Maria-Eugenia Sanin & Elisa Trujillo-Baute, 2017. "CO2 content of electricity losses," Post-Print hal-02878048, HAL.
- Camboni, Riccardo & Corsini, Alberto & Miniaci, Raffaele & Valbonesi, Paola, 2021.
"Mapping fuel poverty risk at the municipal level. A small-scale analysis of Italian Energy Performance Certificate, census and survey data,"
Energy Policy, Elsevier, vol. 155(C).
- Riccardo Camboni & Alberto Corsini & Raffaele Miniaci & Paola Valbonesi, 2020. "Mapping fuel poverty risk at the municipal level: A Small-Scale Analysis of Italian Energy Performance Certificate, Census and Survey data," "Marco Fanno" Working Papers 0252, Dipartimento di Scienze Economiche "Marco Fanno".
- Riccardo Camboni & Alberto Corsini & Raffaele Miniaci & Paola Valbonesi, 2020. "Mapping Fuel Poverty Risk at the Municipal Level: A Small-Scale Analysis of Italian Energy Performance Certificate, Census and Survey Data," GREDEG Working Papers 2020-33, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
- Riccardo Camboni & Alberto Corsini & Raffaele Miniaci & Paola Valbonesi, 2021. "Mapping fuel poverty risk at the municipal level. A small-scale analysis of Italian Energy Performance Certificate, census and survey data," Post-Print hal-03349930, HAL.
- Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.
- Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
- Wen, Hanguan & Liu, Xiufeng & Yang, Ming & Lei, Bo & Xu, Cheng & Chen, Zhe, 2024. "A novel approach for identifying customer groups for personalized demand-side management services using household socio-demographic data," Energy, Elsevier, vol. 286(C).
- Rongheng Lin & Budan Wu & Yun Su, 2018. "An Adaptive Weighted Pearson Similarity Measurement Method for Load Curve Clustering," Energies, MDPI, vol. 11(9), pages 1-17, September.
- Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.
- Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
- Llaria, Alvaro & Curea, Octavian & Jiménez, Jaime & Camblong, Haritza, 2011. "Survey on microgrids: Unplanned islanding and related inverter control techniques," Renewable Energy, Elsevier, vol. 36(8), pages 2052-2061.
- Katz, Jonas, 2014. "Linking meters and markets: Roles and incentives to support a flexible demand side," Utilities Policy, Elsevier, vol. 31(C), pages 74-84.
- Markard, Jochen & Hoffmann, Volker H., 2016. "Analysis of complementarities: Framework and examples from the energy transition," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 63-75.
- Hong, Jun & Johnstone, Cameron & Torriti, Jacopo & Leach, Matthew, 2012. "Discrete demand side control performance under dynamic building simulation: A heat pump application," Renewable Energy, Elsevier, vol. 39(1), pages 85-95.
- Jeroen Stragier & Laurence Hauttekeete & Lieven De Marez & Sven Claessens, 2013. "Towards More Energy Efficient Domestic Appliances? Measuring the Perception of Households on Smart Appliances," Energy & Environment, , vol. 24(5), pages 689-700, September.
- Arteconi, A. & Hewitt, N.J. & Polonara, F., 2012. "State of the art of thermal storage for demand-side management," Applied Energy, Elsevier, vol. 93(C), pages 371-389.
- Rohde, Friederike & Quitzow, Leslie, 2021. "Digitale Energiezukünfte und ihre Wirkungsmacht: Visionen der smarten Energieversorgung zwischen Technikoptimismus und Nachhaltigkeit," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 189-211.
More about this item
Keywords
smart meter data; household survey; EPC; energy data; energy demand; energy consumption; longitudinal; energy modelling; electricity data; gas data;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6934-:d:662008. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.