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Articles 1 - 30 of 107
Full-Text Articles in Energy Policy
Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta
Mind The Hazard: Modeling And Interpreting Comfort With Personalized Sensing, Yufei Zhang, Matteo Favero, Patrick Chwalek, Sailin Zhong, Denis Lalanne, A. Joseph Paradiso, Clayton Miller, Andrew Sonta
Research Collection College of Integrative Studies
Recent advances in personalized sensing and comfort feedback have spurred the development of data-driven comfort models tailored to individual needs. However, because current models treat sequential comfort feedback independently, they are subject to unstable predictions and limited interpretability, hindering their deployment in building management. This study introduces a dynamic modeling framework that utilizes a Neural Ordinary Differential Equations-based Continuous-time Markov Chain to model the transitions in comfort states over time. Our modeling approach, developed through a field study utilizing smart glasses and mobile app feedback, tracks occupants' comfort transitions across daily activities and contexts. The results demonstrate that this model …
Online Planning Of Power Flows For Power Systems Against Bushfires Using Spatial Context, Jianyu Xu, Qiuzhuang Sun, Yang Yang, Huadong Mo, Daoyi Dong
Online Planning Of Power Flows For Power Systems Against Bushfires Using Spatial Context, Jianyu Xu, Qiuzhuang Sun, Yang Yang, Huadong Mo, Daoyi Dong
Research Collection College of Integrative Studies
A power station or transmission line can be affected due to bushfires, increasing operation costs. We study a fundamental but challenging problem of planning the optimal power flow (OPF) for power systems under bushfires. We develop a model to capture the stochastic nature of bushfire spread based on Moore’s neighborhood model and propose an online optimization modeling framework to sequentially plan power flows in the electricity network. Our framework assumes that bushfire spread is non-stationary over time and that the spread and containment probabilities are unknown. To address these challenges, we develop a contextual online learning algorithm that treats the …
Cross-Domain Disaggregation Of Electricity For Heating In All-Electric School Buildings – Learning From School Buildings With District Heating, Synne Krekling Lien, Ada Canaydin, Clayton Miller, Chun Fu, Hussain Kazmi, Jayaprakash Rajasekharan
Cross-Domain Disaggregation Of Electricity For Heating In All-Electric School Buildings – Learning From School Buildings With District Heating, Synne Krekling Lien, Ada Canaydin, Clayton Miller, Chun Fu, Hussain Kazmi, Jayaprakash Rajasekharan
Research Collection College of Integrative Studies
Electric heating is widespread in Norwegian buildings and significantly contributes to peak loads in the electricity grid. Non-residential buildings are typically heated either by district heating or a combination of electrical heating appliances. Despite its widespread use, most buildings lack sub-meters for electric heating. As a result, the true potential for energy efficiency and load flexibility from heating appliances in buildings remains unknown. Non-intrusive load monitoring and disaggregation techniques offer alternatives to sub-metering by using data-driven methods to extract electricity use for appliances from time-series data. However, little research has been conducted on disaggregating electrical heating loads from low-resolution data, …
Poster Abstract: Field Evaluation Of Body Thermoregulation-Based Dynamic Bedroom Air Temperature Control To Improve Sleep, Wenhao Zhang, Stefano Schiavon, Clayton Miller
Poster Abstract: Field Evaluation Of Body Thermoregulation-Based Dynamic Bedroom Air Temperature Control To Improve Sleep, Wenhao Zhang, Stefano Schiavon, Clayton Miller
Research Collection College of Integrative Studies
Sleep is essential for human health and well-being. Previous lab-based studies have shown that dynamically adjusting bedroom temperature according to body thermoregulation can improve sleep quality and thermal satisfaction. However, such strategies have not been tested in real-world settings, and there is a lack of practical solutions developed for residential buildings. In this work, we test a body thermoregulation-based dynamic air conditioning (AC) control strategy designed for typical Singapore homes and evaluated it in a pilot field deployment. The preliminary findings suggest that the proposed strategy can be successfully implemented in real bedroom settings and may improve sleep outcomes.
Enhancing Urban Energy Modeling: A Case Study Of Data Acquisition, Enrichment, And Evaluation In Berlin, Felix Rehmann, Martín Mosteiro-Romero, Clayton Miller, Rita Streblow
Enhancing Urban Energy Modeling: A Case Study Of Data Acquisition, Enrichment, And Evaluation In Berlin, Felix Rehmann, Martín Mosteiro-Romero, Clayton Miller, Rita Streblow
Research Collection College of Integrative Studies
Urban Building Energy Modeling (UBEM) has become a critical tool for developing local heating and cooling plans, as required by the European Union. Despite growing interest, the reproducibility and reliability of UBEM studies remain limited due to data scarcity and workflow complexity. This paper presents a comprehensive framework to evaluate the data pipeline in UBEM, with a particular focus on data acquisition, enrichment, simulation, calibration, and information application. The approach applies three distinct UBEM workflows (CityEnergyAnalyst, DistrictGenerator, and SimStadt) to the Mierendorffinsel district in Berlin, Germany. We compare the based on quantitative performance metrics and qualitative framework criteria. The results …
Revealing Building Operating Carbon Dynamics For Multiple Cities, Winston Yap, Abraham Noah Wu, Clayton Miller, Filip Biljecki
Revealing Building Operating Carbon Dynamics For Multiple Cities, Winston Yap, Abraham Noah Wu, Clayton Miller, Filip Biljecki
Research Collection College of Integrative Studies
Achieving carbon neutrality is a critical yet elusive goal for many cities, hindered by limited understanding of the relationship between building emissions and their surroundings. To address this challenge, we present a generalizable open science framework that integrates building energy-consumption data, multi-modal geospatial inputs and graph deep learning to quantify building operating emissions and their links to urban form and socio-economic factors. Applying this approach to five cities with diverse climates and planning contexts—Melbourne, New York City (Manhattan), Seattle, Singapore and Washington DC—we demonstrate that our models explain 78.4% of the variation in building operating carbon emissions across cities, achieving …
International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer
International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer
Research Collection College of Integrative Studies
Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this …
Recommender Systems And Reinforcement Learning For Human-Building Interaction And Context Aware Support: A Text Mining-Driven Review Of Scientific Literature, Wenhao Zhang, Matias Quintana, Clayton Miller
Recommender Systems And Reinforcement Learning For Human-Building Interaction And Context Aware Support: A Text Mining-Driven Review Of Scientific Literature, Wenhao Zhang, Matias Quintana, Clayton Miller
Research Collection College of Integrative Studies
The indoor environment significantly impacts human health and well-being; enhancing health and reducing energy consumption in these settings is a central research focus. With the advancement of Information and Communication Technology (ICT), recommendation systems and reinforcement learning (RL) have emerged as promising approaches to induce behavioral changes to improve the indoor environment and energy efficiency of buildings. This study aims to employ text mining and Natural Language Processing (NLP) techniques to thoroughly examine the connections among these approaches in the context of human-building interaction and occupant context-aware support. The study analyzed 27,595 articles from the ScienceDirect database, revealing extensive use …
Data And Digitalization In Energy Efficiency Policy Design: The Case Of Singapore, Ishani Mukherjee, Diandrea Ho
Data And Digitalization In Energy Efficiency Policy Design: The Case Of Singapore, Ishani Mukherjee, Diandrea Ho
Research Collection School of Social Sciences
Overarching and broad policy goals for enhancing energy efficiency have existed globally over the last 50 years as a response to rising energy demands, heightening costs, and construction levels of residential and commercial buildings, and the associated rises in greenhouse gas emissions from energy use (Levine et al., 2007; World Bank, 2010). Buildings, in particular, have been widely recognized as offering the greatest potential for reducing energy use and related greenhouse gas emissions, followed by reduced energy consumption in manufacturing, appliances, electronic goods, and end-users of electricity (Levine, 2007; IEA, 2010). And while significant technological strides have been made globally …
A Dynamic Urban Digital Twin Integrating Longitudinal Thermal Imagery For Microclimate Studies, Vasantha Ramani, Marcel Ignatius, Joie Lim, Filip Biljecki, Clayton Miller
A Dynamic Urban Digital Twin Integrating Longitudinal Thermal Imagery For Microclimate Studies, Vasantha Ramani, Marcel Ignatius, Joie Lim, Filip Biljecki, Clayton Miller
Research Collection College of Integrative Studies
Recently, the concept of a digital twin for the built environment has received significant attention due to its potential benefits to urban planners, engineers, and designers. The development of tools that aid in integrating real-world physical systems with digital capabilities is essential for advancing digital twin technology. In this work, we present one such digital twin tool that integrates the longitudinal thermal envelope data of buildings on the campus of the National University of Singapore with a virtual 3D model. Thermal images of the buildings were captured using a neighborhood-scale infrared observatory for a few months. The temperature profile of …
Mitigating Operational Greenhouse Gas Emissions In Ageing Residential Buildings Using An Urban Digital Twin Dashboard, Pradeep Alva, Martín Mosteiro-Romero, Clayton Miller, Rudi Stouffs
Mitigating Operational Greenhouse Gas Emissions In Ageing Residential Buildings Using An Urban Digital Twin Dashboard, Pradeep Alva, Martín Mosteiro-Romero, Clayton Miller, Rudi Stouffs
Research Collection College of Integrative Studies
With the increasing stock of ageing infrastructure and resource constraints in Singapore, related risks and carbon emissions can be mitigated through long-term resilience planning, automated building inspection, and effective maintenance. Sustainable actions are needed to maintain Singapore's ageing infrastructure. Hence, a state-of-the-art control and management system is required in the form of smart city digital tools. We introduce an Urban Digital Twin (UDT)—GHG App for decision-makers in Singapore's operational building greenhouse gas (GHG) emission mitigation and decarbonisation initiatives. Based on multiple-criteria decision analysis (MCDA), a Potential for Intervention (PFI) map was created to rejuvenate the building system. Decision-makers can use …
From Personal Comfort To District Performance: Using Smartwatch And Wifi Data For Occupant-Driven Operation, Martín Mosteiro-Romero, Matias Quintana, Clayton Miller, Rudi Stouffs
From Personal Comfort To District Performance: Using Smartwatch And Wifi Data For Occupant-Driven Operation, Martín Mosteiro-Romero, Matias Quintana, Clayton Miller, Rudi Stouffs
Research Collection College of Integrative Studies
This work proposes the use of a data-driven, agent-based model of building occupants’ activities and thermal comfort in an urban university campus in order to assess how district operation strategies can be leveraged to support the transition to flexible work arrangements. The results show that when users are given the flexibility to pursue more comfortable workspaces, they are still comfortable only 58% of the time.
Introducing The Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat And Noise With Digital Twin Metrics, Clayton Miller, Matias Quintana, Mario Frei, Xuan Yun Chua, Chun Fu, Bianca Picchetti, Winston Yap, Adrian Chong, Filip Biljecki
Introducing The Cool, Quiet City Competition: Predicting Smartwatch-Reported Heat And Noise With Digital Twin Metrics, Clayton Miller, Matias Quintana, Mario Frei, Xuan Yun Chua, Chun Fu, Bianca Picchetti, Winston Yap, Adrian Chong, Filip Biljecki
Research Collection College of Integrative Studies
The productivity and satisfaction of humans in the built environment is impacted significantly by their exposure to high temperature and various noise sources. This paper outlines the city-scale collection of 12,009 smartwatch-driven micro-survey responses that were collected alongside 2,825,243 physiological and environmental measurements from 106 people using the open-source Cozie-Apple platform combined with geolocation-driven urban digital twin metrics from the Urbanity Python package. This paper introduces a machine learning competition that will be launched for participants to compete in training models on the various contextual data to predict noise distraction and source as well as thermal preference across a diversity …
Are Corporations Responding To Civil Society Pressure?: A Multilevel Analysis Of Corporate Emissions, Annika Rieger
Are Corporations Responding To Civil Society Pressure?: A Multilevel Analysis Of Corporate Emissions, Annika Rieger
Research Collection School of Social Sciences
Previous research in the world-society tradition associates improvements in nation-level environmental outcomes with greater civil society integration. However, research in the world-systems tradition indicates these improvements depend on a nation’s position in the global political-economic hierarchy. To test whether these patterns are present at the organizational level, I estimate a multilevel model using corporate emissions data from the Carbon Disclosure Project and include interactions between world-system position and three measures of civil society integration: number of NGOs, proportion of corporations with climate-management incentives, and number of corporate UN Global Compact signatories. I find that the relationship between civil society pressure …
Financing Just Energy Transitions In Southeast Asia: Application Of The Just Transition Transaction To Indonesia, Vietnam, And Philippines, Abhinav Jindal, Gireesh Shrimali, Bharat Gangwani, Rajiv B. Lall
Financing Just Energy Transitions In Southeast Asia: Application Of The Just Transition Transaction To Indonesia, Vietnam, And Philippines, Abhinav Jindal, Gireesh Shrimali, Bharat Gangwani, Rajiv B. Lall
Sim Kee Boon Institute for Financial Economics
This paper investigates the applicability of the Just Transition Transaction (JTT), initially developed as a financial mechanism for South Africa's energy transition, to Southeast Asian (SEA) countries, including Indonesia, Vietnam, and the Philippines, which heavily rely on coal. Utilizing South Africa as a reference case study, we deconstruct the JTT and develop a novel framework of necessary and conducive features for evaluating its suitability for supporting a just energy transition in SEA. Our findings suggest that the JTT is well-suited for Indonesia and Vietnam but not as well suited for the Philippines. Recommendations for specific research avenues in estimating baselines …
Creating Synthetic Energy Meter Data Using Conditional Diffusion And Building Metadata, Chun Fu, Hussain Kazmi, Matias Quintana, Clayton Miller
Creating Synthetic Energy Meter Data Using Conditional Diffusion And Building Metadata, Chun Fu, Hussain Kazmi, Matias Quintana, Clayton Miller
Research Collection College of Integrative Studies
Advances in machine learning and increased computational power have driven progress in energy-related research. However, limited access to private energy data from buildings hinders traditional regression models relying on historical data. While generative models offer a solution, previous studies have primarily focused on short-term generation periods (e.g., daily profiles) and a limited number of meters. Thus, the study proposes a conditional diffusion model for generating high-quality synthetic energy data using relevant metadata. Using a dataset comprising 1,828 power meters from various buildings and countries, this model is compared with traditional methods like Conditional Generative Adversarial Networks (CGAN) and Conditional Variational …
Opening The Black Box: Towards Inherently Interpretable Energy Data Imputation Models Using Building Physics Insight, Antonio Liguori, Matias Quintana, Chun Fu, Clayton Miller, Jérôme Frisch, Christoph Van Treeck
Opening The Black Box: Towards Inherently Interpretable Energy Data Imputation Models Using Building Physics Insight, Antonio Liguori, Matias Quintana, Chun Fu, Clayton Miller, Jérôme Frisch, Christoph Van Treeck
Research Collection College of Integrative Studies
Missing data are frequently observed by practitioners and researchers in the building energy modeling community. In this regard, advanced data-driven solutions, such as Deep Learning methods, are typically required to reflect the non-linear behavior of these anomalies. As an ongoing research question related to Deep Learning, a model's applicability to limited data settings can be explored by introducing prior knowledge in the network. This same strategy can also lead to more interpretable predictions, hence facilitating the field application of the approach. For that purpose, the aim of this paper is to propose the use of Physics-informed Denoising Autoencoders (PI-DAE) for …
Navigating Geopolitical Crises For Energy Security: Evaluating Optimal Subsidy Policies Via A Markov Switching Dsge Model, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Navigating Geopolitical Crises For Energy Security: Evaluating Optimal Subsidy Policies Via A Markov Switching Dsge Model, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Sim Kee Boon Institute for Financial Economics
This paper aims to provide insights on the design of optimal subsidy policies to enhance energy security amidst energy disruptions triggered by geopolitical conflicts. We introduce a novel Markov switching dynamic stochastic general equilibrium (MS-DSGE) model to address the limitations of existing integrated assessment models in environmental evaluation. These models often fail to adequately consider the environmental and economic impacts of geopolitical conflicts and do not prioritize energy security sufficiently in policymaking. Our application of the MS-DSGE model to the Russia–Ukraine conflict reveals significant decreases in output, social welfare, and energy consumption during disruptions. The mere anticipation of an energy …
Filling Time-Series Gaps Using Image Techniques: Multidimensional Context Autoencoder Approach For Building Energy Data Imputation, Chun Fu, Matias Quintana, Zoltan Nagy, Clayton Miller
Filling Time-Series Gaps Using Image Techniques: Multidimensional Context Autoencoder Approach For Building Energy Data Imputation, Chun Fu, Matias Quintana, Zoltan Nagy, Clayton Miller
Research Collection College of Integrative Studies
Building energy prediction and management has become increasingly important in recent decades, driven by the growth of Internet of Things (IoT) devices and the availability of more energy data. However, energy data is often collected from multiple sources and can be incomplete or inconsistent, which can hinder accurate predictions and management of energy systems and limit the usefulness of the data for decision-making and research. To address this issue, past studies have focused on imputing missing gaps in energy data, including random and continuous gaps. One of the main challenges in this area is the lack of validation on a …
A Repository Of Occupant-Centric Control Case Studies: Survey Development And Database Overview, Clara-Larissa Lorenz, Maíra André, Oliver Abele, Burak Gunay, Jakob Hahn, Philipp Hensen, Zoltan Nagy, M. Mohamed Ouf, Young June Park, Nikhil Yaduvanshi Singh, Clayton Miller
A Repository Of Occupant-Centric Control Case Studies: Survey Development And Database Overview, Clara-Larissa Lorenz, Maíra André, Oliver Abele, Burak Gunay, Jakob Hahn, Philipp Hensen, Zoltan Nagy, M. Mohamed Ouf, Young June Park, Nikhil Yaduvanshi Singh, Clayton Miller
Research Collection College of Integrative Studies
Occupant-centric controls (OCC) and operations have emerged as a key concept in shifting the focus from conventional building- (or system-) centric operations to a more occupant-centric approach. Despite the potential of OCC to meet occupants’ demands and bridge buildings’ energy performance gap, its implementation in real-world settings has been limited. In addition, there is a lack of standardization in methodologies and terms to facilitate meaningful comparisons among case studies. Therefore, this paper aims to present a repository of OCC case studies, offering a platform for standardization and presenting key information about practical implementations of these strategies in real-world scenarios. To …
Enhancing Classification Of Energy Meters With Limited Labels Using A Semi-Supervised Generative Model, Chun Fu, Hussain Kazmi, Matias Quintana, Clayton Miller
Enhancing Classification Of Energy Meters With Limited Labels Using A Semi-Supervised Generative Model, Chun Fu, Hussain Kazmi, Matias Quintana, Clayton Miller
Research Collection College of Integrative Studies
In the energy domain, the classification of power meters has become an increasingly significant area of interest, such as appliance identification and characteristics prediction, enabling targeted and efficient energy management. However, the limited availability of labeled data for power meters and the inconsistencies in labeling and naming conventions have constrained the potential of metadata for further application. This study aims to bridge the gap by employing semi-supervised Generative Adversarial Networks (SGAN) to classify 1805 power meters distributed globally. This approach explores and assesses the advantages of incorporating unlabeled power meter data into the learning process. A comparative analysis is performed …
Disrupting The Grid: Encountering Fire And Smoke Through Energy Infrastuctures, Deepti Chatti, Sayd Randle
Disrupting The Grid: Encountering Fire And Smoke Through Energy Infrastuctures, Deepti Chatti, Sayd Randle
Research Collection College of Integrative Studies
Experiences of fires are mediated by energy infrastructures and refracted through social inequality and difference. In California, a state marked by increasingly intense and frequent wildfires, the grid is a source of fire risk, with historically marginalized groups bearing the brunt of exposures to wildfire smoke. Drawing on research conducted by one of the co-authors in collaboration with California’s Karuk Tribe and Blue Lake Rancheria Tribes, this empirically grounded review article expands our understanding of grids. Extant scholarship presents the grid as a networked infrastructure mediating access to energy and one’s relationship to a collective and the state. We extend …
Elastic Buildings: Calibrated District-Scale Simulation Of Occupant-Flexible Campus Operation For Hybrid Work Optimization, Martín Mosteiro-Romero, Clayton Miller, Adrian Chong, Rudi Stouffs
Elastic Buildings: Calibrated District-Scale Simulation Of Occupant-Flexible Campus Operation For Hybrid Work Optimization, Martín Mosteiro-Romero, Clayton Miller, Adrian Chong, Rudi Stouffs
Research Collection College of Integrative Studies
Before 2020, the way occupants utilized the built environment had been changing slowly towards scenarios in which occupants have more choice and flexibility in where and how they work. The global COVID-19 pandemic accelerated this phenomenon rapidly through lockdowns and hybrid work arrangements. Many occupants and employers are considering keeping some of these flexibility-based strategies due to their benefits and cost impacts.This paper explores how demand-driven control strategies in the built environment might support the transition to increased workplace flexibility by simulating various scenarios related to the operational technologies and policies of a real-world campus using a district-scale City Energy …
Experimental Assessment Of Thermal And Acoustics Interactions On Occupant Comfort In Mixed-Mode Buildings, Yuzhen Peng, Nogista Antanuri, Siu-Kit Lau, Bahador Jebelli, Kardinal Steve Jusuf, Clayton Miller, Ting Yi Teo, Xuan Yun Chua, Adrian Chong
Experimental Assessment Of Thermal And Acoustics Interactions On Occupant Comfort In Mixed-Mode Buildings, Yuzhen Peng, Nogista Antanuri, Siu-Kit Lau, Bahador Jebelli, Kardinal Steve Jusuf, Clayton Miller, Ting Yi Teo, Xuan Yun Chua, Adrian Chong
Research Collection College of Integrative Studies
Mixed-mode buildings use natural ventilation (NV) through operable building envelopes (e.g., windows) and mechanical air-conditioning (AC) systems to condition indoor spaces with the goal of energy savings without compromising occupant comfort requirements. As a result, occupants within such buildings experience different thermal and acoustic conditions. In mixed-mode buildings, however, there is no clear guideline on assessing or predicting occupants’ thermal perception (e.g., thermal sensation and acceptability) and the interaction effects between thermal and acoustic comfort. This study investigates thermal and acoustic comfort as well as their interaction effects in mixed-mode buildings under NV and AC modes. A field study was …
A Hybrid Active Learning Framework For Personal Thermal Comfort Models, Duygu Zeynep Tekler, Yue Lei, Yuzhen Peng, Clayton Miller, Adrian Chong
A Hybrid Active Learning Framework For Personal Thermal Comfort Models, Duygu Zeynep Tekler, Yue Lei, Yuzhen Peng, Clayton Miller, Adrian Chong
Research Collection College of Integrative Studies
Personal thermal comfort models are used to predict individual-level thermal comfort responses to inform design and control decisions of buildings to achieve optimal conditioning for improved comfort and energy efficiency. However, the development of data-driven thermal comfort models requires collecting a large amount of sensor-related measurements and user-labelled data (i.e., user feedback) to achieve accurate predictions, which can be highly intrusive and labour intensive in real-world applications. In this work, we propose a hybrid active learning framework to reduce data collection costs for developing data-efficient and robust personal comfort models that predict users’ thermal comfort and air movement preferences. Through …
A Review And Reflection On Open Datasets Of City-Level Building Energy Use And Their Applications, Xiaoyu Jin, Chong Zhang, Fu Xiao, Ao Li, Clayton Miller
A Review And Reflection On Open Datasets Of City-Level Building Energy Use And Their Applications, Xiaoyu Jin, Chong Zhang, Fu Xiao, Ao Li, Clayton Miller
Research Collection College of Integrative Studies
Data related to building energy use fuels the research and applications on building energy efficiency, which is an essential measure to address global energy and environmental challenges. However, in most cities, there is a lack of comprehensive and publicly accessible building energy use datasets with necessary temporal and spatial granularities to support urban building energy modeling, regional energy planning, city-level building performance benchmarking, and policymaking on building energy efficiency. Data owners and governments are facing challenges in determining which and how building energy use data should be disclosed at the city level and how to protect data privacy. This review …
District-Scale Surface Temperatures Generated From High-Resolution Longitudinal Thermal Infrared Images, Subin Lin, Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan, Adrian Chong, Filip Biljecki, Marcel Ignatius, Clayton Miller, Clayton Miller
District-Scale Surface Temperatures Generated From High-Resolution Longitudinal Thermal Infrared Images, Subin Lin, Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan, Adrian Chong, Filip Biljecki, Marcel Ignatius, Clayton Miller, Clayton Miller
Research Collection College of Integrative Studies
This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built environment in various aspects. While most studies focus on the city and building scales, an observatory installed on a rooftop provides high temporal and spatial resolution observations with dynamic interactions on the district scale. The rooftop infrared thermography observatory with a multi-modal platform capable of assessing a wide range of dynamic processes in urban systems was deployed in Singapore. It was placed on the top of two buildings that overlook the outdoor context of the National University of Singapore campus. …
Leveraging Campus-Scale Wi-Fi Data For Activity-Based Occupant Modeling In Urban Energy Applications, Martín Mosteiro-Romero, Clayton Miller, Matias Quintana, Adrian Chong, Rudi Stouffs
Leveraging Campus-Scale Wi-Fi Data For Activity-Based Occupant Modeling In Urban Energy Applications, Martín Mosteiro-Romero, Clayton Miller, Matias Quintana, Adrian Chong, Rudi Stouffs
Research Collection College of Integrative Studies
The widespread availability of open datasets in urban areas is transforming how urban energy systems are planned, simulated, and visualized. Urban energy models, however, require an understanding of urban dwellers, as their activities create the demands for energy in buildings. In this paper, we explore using campus-scale Wi-Fi data to identify typical occupant activity patterns as an input to an agent-based model of building occupants at the district scale. The data is taken from a Singaporean university’s Wi-Fi network at high resolution. Each record comprises a timestamp, a device identifier, the location of the device within the campus, and the …
The Building Data Genome Directory – An Open, Comprehensive Data Sharing Platform For Building Performance Research, Xiaoyu Jin, Chun Fu, Hussain Kazmi, Atilla Balint, Ada Canaydin, Matias Quintana, Filip Biljecki, Fu Xiao, Clayton Miller
The Building Data Genome Directory – An Open, Comprehensive Data Sharing Platform For Building Performance Research, Xiaoyu Jin, Chun Fu, Hussain Kazmi, Atilla Balint, Ada Canaydin, Matias Quintana, Filip Biljecki, Fu Xiao, Clayton Miller
Research Collection College of Integrative Studies
The building sector plays a crucial role in the worldwide decarbonization effort, accounting for significant portions of energy consumption and environmental effects. However, the scarcity of open data sources is a continuous challenge for built environment researchers and practitioners. Although several efforts have been made to consolidate existing open datasets, no database currently offers a comprehensive collection of building data types with all subcategories and time granularities (e.g., year, month, and sub-hour). This paper presents the Building Data Genome Directory, an open data-sharing platform serving as a one-stop shop for the data necessary for vital categories of building energy research. …
Quantifying Stranded Assets Of The Coal-Fired Power In China Under The Paris Agreement Target, Weirong Zhang, Yiou Zhou, Zhen Gong, Junjie Kang, Changhong Zhao, Zhixu Meng, Jian Zhang, Tao Zhang, Jiahai Yuan
Quantifying Stranded Assets Of The Coal-Fired Power In China Under The Paris Agreement Target, Weirong Zhang, Yiou Zhou, Zhen Gong, Junjie Kang, Changhong Zhao, Zhixu Meng, Jian Zhang, Tao Zhang, Jiahai Yuan
Research Collection School Of Computing and Information Systems
Coal-fired power plays a critical role in China's compliance with the Paris Agreement. This research quantifies China's stranded coal assets under different coal capacity expansion scenarios with an integrated approach and high-precision coal-fired power database. From a top-down perspective, firstly, the pathway of China's coal-fired power capacity consistent with the global 2 degrees C scenario is outlined and then those stranded coal-fired power plants are identified with a bottom-up perspective. Stranded value is estimated based upon a cash flow algorithm. Results show that if coal capacity stabilizes during 2020-2030, China will only incur a sizeable yet manageable stranded asset loss …