Article
Construction & Building Technology
Wooyoung Jung, Zhe Wang, Tianzhen Hong, Farrokh Jazizadeh
Summary: This study introduces representative occupancy schedules in the U.S. residential buildings derived from a large smart thermostat dataset and time-series K-means clustering, and develops an open-source tool to generate a stochastic residential occupancy schedule. Over 90,000 residential occupancy schedules were estimated from the ecobee Donate Your Data dataset, and the representative occupancy schedules were identified through clustering. The derived representative occupancy schedules and the ROSS tool can help improve the energy modeling of residential buildings.
BUILDING AND ENVIRONMENT
(2023)
Article
Construction & Building Technology
Brent Huchuk, Scott Sanner, William O'Brien
Summary: The study compared three different HVAC control methods and found that MPC control had the lowest average cost, better linear model predictive capability, and did not subject occupants to the discomfort of system exploration compared to the other methods.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Ruth Tamas, William O'Brien, Mario Santana Quintero
Summary: This study examines the relationship between thermostat usability and interface characteristics and found that smart thermostats are more usable than programmable ones. Participants expressed a desire for more feedback regarding energy consumption, with half of them wanting or enjoying thermostat control through a smartphone application.
BUILDING AND ENVIRONMENT
(2021)
Article
Chemistry, Analytical
Federico Seri, Marco Arnesano, Marcus Martin Keane, Gian Marco Revel
Summary: The study introduces a sensing optimization approach for home thermostats to reduce sensing uncertainty, achieve comfort levels, and minimize retrofit payback period. Practical application demonstrates that repositioning thermostats and setting appropriate temperatures can improve control performance, save energy, and shorten payback periods.
Article
Construction & Building Technology
Xingji Yu, Laurent Georges, Lars Imsland
Summary: The article introduces grey-box models and their applications in characterizing the thermal properties of building envelopes, discussing the influence of data pre-processing and training data on deterministic and stochastic innovation form of grey-box models.
ENERGY AND BUILDINGS
(2021)
Article
Environmental Sciences
Zhe Wang, Tianzhen Hong, Han Li
Summary: With climate change leading to more frequent and intense heat waves, rotating power outages become necessary. A novel data-driven approach using smart thermostat data was proposed to inform decision making for power outage planning, tested in California to find that power outages should not exceed two hours during heat waves to mitigate overheating risks. Informing residents in advance to prepare through pre-cooling is a simple and effective strategy to expand the acceptable power outage duration.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
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
Construction & Building Technology
Sanduni Peiris, Joseph H. K. Lai, Mohan M. Kumaraswamy, Huiying (Cynthia) Hou
Summary: Transforming ordinary buildings into smart buildings (SBs), known as smart retrofitting (SR), requires retrofit works involving smart technology applications. A systematic literature review was conducted to explore the research gaps and identified six future research areas. The study provides a framework consolidating the review findings and a mapping exhibiting the nexus of future research directions.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Gowri Suryanarayana, Javier Arroyo, Lieve Helsen, Jesus Lago
Summary: The proposed data-driven methodology identifies optimal sensor placement in multi-zone buildings by utilizing statistical tests to improve control and monitoring applications. By simplifying models and using a data-driven approach, the method is applicable to various buildings while effectively reducing costs.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Hamed Bagheri-Esfeh, Mohammad Reza Dehghan
Summary: This paper investigates the determination of the optimum setpoint temperature of thermostats in various climates in Iran and proposes a new method based on neural networks and multi-objective optimization algorithms. The results show that the type and thickness of insulation materials have significant impacts on energy consumption, cost, and thermal comfort of occupants in buildings.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Christian Ankerstjerne Thilker, Peder Bacher, Hjorleifur G. Bergsteinsson, Rune Granborg Junker, Davide Cali, Henrik Madsen
Summary: This paper presents a non-linear grey-box model based on stochastic differential equations to describe the heat dynamics of a school building in Denmark equipped with a water-based heating system. The model accurately predicts indoor air temperature, return water temperature, and heat load, laying the foundation for grey-box models of buildings using different types of water-based heating systems.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Xiang Zhang, Dirk Saelens, Staf Roels
Summary: This study demonstrates the potential application of a data-driven B-splines integrated grey-box modelling technique for estimating dynamic solar gains in real buildings. Improved solutions are proposed to consider the impact of occupants.
BUILDING AND ENVIRONMENT
(2023)
Article
Construction & Building Technology
Jaewan Joe, Jin Dong, Jeffrey Munk, Teja Kuruganti, Borui Cui
Summary: This study evaluated the virtual storage capability of a residential air-conditioning system by utilizing building mass as thermal storage, through model-based predictive control. The results showed that MPC significantly saved energy costs while improving comfort levels.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Green & Sustainable Science & Technology
Ling Jia, Queena K. Qian, Frits Meijer, Henk Visscher
Summary: This study focuses on key risks in residential building retrofit projects in China's hot summer and cold winter zone, with considerations of transaction costs. By identifying top risks through interviews and a questionnaire survey, the research aims to provide guidance for effective risk management in energy retrofit projects.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Green & Sustainable Science & Technology
Wahhaj Ahmed, Muhammad Asif
Summary: The building sector plays a significant role in climate change, with the residential sector in GCC countries being particularly critical. There is a need for these countries to invest in improving the energy performance of existing unsustainable residential buildings. Existing literature on energy retrofitting in the GCC countries lacks top-down and bottom-up physical approaches, as well as the application of modern design tools like BIM. Additionally, no studies present measured and verified case studies of implemented energy retrofitting projects, highlighting a gap in existing research.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)