Article
Multidisciplinary Sciences
Markus Schaffer, Torben Tvedebrink, Anna Marszal-Pomianowska
Summary: This study provides three years of data from 3,021 commercial smart heat meters in Danish residential buildings, which have undergone screening, interpolation, and imputation processes, aiming to facilitate the development of data-driven approaches in the building sector.
Article
Construction & Building Technology
Jaume Palmer Real, Christoffer Rasmussen, Rongling Li, Kenneth Leerbeck, Ole Michael Jensen, Kim B. Wittchen, Henrik Madsen
Summary: Buildings play a significant role in total energy consumption and have the potential to be used as thermal storage capacity for the future energy grid. A data-driven method is proposed to analyze the thermal dynamics of thermostatically controlled buildings with night setback, which can classify buildings based on their thermal response. The method was applied to 39 different Danish residential buildings, showing that the simplified model captures the main processes governing heat transfer.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Sajad M. R. Khani, Fariborz Haghighat, Karthik Panchabikesan, Milad Ashouri
Summary: The study uses a data mining-based framework to provide practical insights into occupants' energy behavior in residential buildings, introducing new indicators OAI and REII, and demonstrating its utility in a three-bedroom apartment.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Construction & Building Technology
Hao Zhou, Juan Yu, Yang Zhao, Chenchen Chang, Jiajun Li, Borong Lin
Summary: The study focused on extracting occupant presence information from indoor environment data, and found that incorporating information of light and AC operations significantly improved recognition accuracy.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Julien Leprince, Clayton Miller, Wim Zeiler
Summary: This study presents a generic multidimensional data mining framework tailored to building data using the structure of data cubes. Using 3053 energy meters, the method is applied to automated pattern identification. Results emphasize the importance of application and insight-driven mining for effective dimensional-frame targeting.
ENERGY AND BUILDINGS
(2021)
Article
Energy & Fuels
Karol Bandurski, Andrzej Gorka, Halina Koczyk
Summary: This paper explores the potential use of data from heat meters for analyzing occupant interactions with space-heating systems. The study finds that most households did not use the automatic adjustment function, possibly due to the weaknesses of the heating interface and the technical specificity of the system.
Article
Energy & Fuels
Prateek Munankarmi, Jeff Maguire, Sivasathya Pradha Balamurugan, Michael Blonsky, David Roberts, Xin Jin
Summary: Demand-side management (DSM) strategies, such as energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid by reducing costs, enhancing reliability, and helping customers reduce utility bills. Utilizing EE upgrades and enabling DF through a home energy management system (HEMS) in homes can reduce HVAC energy use, utility bills, and peak demand while increasing load flexibility in the community.
Article
Construction & Building Technology
Jihyun Seo, Seohoon Kim, Sungjin Lee, Hakgeun Jeong, Taeyeon Kim, Jonghun Kim
Summary: To achieve carbon neutrality, the South Korean government has been retrofitting existing buildings to reduce energy consumption. This study developed a model that can predict heating energy demand using only preliminary survey information, outperforming existing models in terms of speed and accuracy.
BUILDING AND ENVIRONMENT
(2022)
Article
Computer Science, Information Systems
Hyunyong Lee, Hyunseok Jang, Seung-Hun Oh, Nac-Woo Kim, Seongcheol Kim, Byung-Tak Lee
Summary: Demand response (DR) is a voluntary program that encourages electricity consumers to reduce usage during high load periods. Involving residential customers is crucial for the success of DR programs. Researchers have addressed the non-equal incentive problem through mathematical and experimental methods, proposing a new indirect incentive calculation method based on single groups, showing improved accuracy in baseline estimation.
Article
Business
Anastasia Griva
Summary: This study mines customer satisfaction segments using data from a CS survey in 140 e-commerce stores. It presents examples of how one store utilized the segments for automated marketing actions. The findings contribute to decision making and industry benchmarking.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2022)
Article
Energy & Fuels
Alain Poulin, Marie-Andree Leduc, Michael Fournier
Summary: In this paper, the challenges of modeling a baseline in residential winter demand response programs with individual performance-based incentives are explored. Through statistical comparison of over a thousand residential load profiles, it was found that adjusted arithmetic models achieved similar performances to more complex regression models without the need for weather data.
Article
Green & Sustainable Science & Technology
C. Prades-Gil, J. D. Viana-Fons, X. Masip, A. Cazorla-Marin, T. Gomez-Navarro
Summary: Climate change will have an impact on human health, particularly in urban areas. Energy planning is crucial for the development of sustainable and resilient cities. Urban building energy models can assist in energy planning by predicting heating and cooling demand and evaluating the consequences of different planning actions.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Computer Science, Interdisciplinary Applications
Peter Melville-Shreeve, Sarah Cotterill, David Butler
Summary: The study investigated toilet water demand in buildings on a university campus using smart meters. Results showed that toilet use was influenced by building occupants and weekday vs. weekend patterns. The findings suggest the potential for using captured data for forecasting, alarm systems, and other tools to optimize water management strategies.
JOURNAL OF HYDROINFORMATICS
(2021)
Article
Automation & Control Systems
Yang Chen, Chunyu Chen, Xiao Zhang, Mingjian Cui, Fangxing Li, Xinan Wang, Shengfei Yin
Summary: Customer baseline load (CBL) reconstruction is a critical problem in residential demand response. This study proposes a regression-based estimation scheme using stacked autoencoders (SAEs) under the federated learning (FL) framework to target the CBL reconstruction of residential prosumers. The experimental results show that the proposed FL-based cascaded SAE outperforms the baseline on all tests and achieves significant improvement in reducing reconstruction error, while also enhancing privacy-preserving knowledge-sharing ability.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Nuclear Science & Technology
Biswajit Biswal, Andrew Duncan, Zaijing Sun
Summary: This study analyzes the data collected by ISD sensors to identify frequent episodes and abnormal frequent episodes, which may serve as early indicators of ISD system failures.
NUCLEAR ENGINEERING AND TECHNOLOGY
(2022)