Article
Construction & Building Technology
Nicola Cibin, Alessandro Tibo, Hessam Golmohamadi, Arne Skou, Michele Albano
Summary: Heat pump controllers optimize the operation of building thermal dynamics by estimating the dynamic thermal characteristics of heat pumps. In this paper, two grey-box models are used to estimate the thermal characteristics of residential buildings, and the FlexOffer concept is used to generate heat flexibility considering uncertain weather variables.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Lin Lin, Guodong Chen, Xiaochen Liu, Xiaohua Liu, Tao Zhang
Summary: This paper investigates the cooling load characteristics in airport terminal buildings and categorizes the indoor areas based on their distinct characteristics. The study reveals the significant impact of outdoor temperature, outdoor relative humidity, and air change rate on cooling loads. The Bayesian calibration analysis identifies the differences in main parameters as the key factors causing the discrepancy between measurement and design. The paper also discusses the potential for flexible cooling load adjustment across different area categories.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Operations Research & Management Science
Hongzhou Li, Andrea Appolloni, Yijie Dou, Vincenzo Basile, Maria Kopsakangas-Savolainen
Summary: This study estimates China's energy use efficiency during the first two decades of the twenty-first century, taking into account pollutant emissions. The results, obtained using an SFA-based model, show that the environmental energy efficiency is 0.7812, which contrasts with findings based on commonly used indicators, indicating the need for more sophisticated metrics to evaluate energy efficiency and environmental performance.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Petar Skvorc, Hrvoje Kozmar
Summary: Wind energy harnessing on tall buildings in urban environments is a rapidly developing renewable energy technology. This technology is influenced by terrain type, local wind characteristics, urban environment, and building architecture. The study outlines key points related to urban wind energy harnessing by critically assessing existing literature, highlighting the importance of urban wind environment, wind resource assessment, and wind-turbine design, with a case study analyzing the combined influence of these features. Vertical axis wind turbines are generally more efficient in turbulent flow and less noisy, making them a better choice for tall buildings in urban environments, although there are also successful examples of horizontal axis wind turbines.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Construction & Building Technology
Jaime Gonzalez-Dominguez, Gonzalo Sanchez-Barroso, Justo Garcia-Sanz-Calcedo, Nuno de Sousa Neves
Summary: The energy consumption of healthcare buildings is excessively high due to their continuous operation and demand for electro-medical equipment. This study applied the Cox proportional hazards model to predict the probability of energy overconsumption in healthcare buildings based on different functional variables. The results showed that variables related to facilities and demographics have a significant influence on energy consumption, and their impact was quantified in the study.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Horace Guy, Simon Vittoz, Giulia Caputo, Thimothee Thiery
Summary: This paper analyzes the 2021 energy consumption data of over 20000 commercial buildings in Europe and calibrates a Bayesian multilevel modeling to predict the full distribution of energy use intensity. The modeling takes into account the country, building typology, and climate factors to accurately represent the diversity of the commercial building stock. The originality of the approach lies in its combined use of Bayesian multilevel modeling and a model structure that independently learns specific effects. The modeling shows good predictive power even for combinations of features with limited representative data.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Xue Liu, Hao Tang, Yong Ding, Da Yan
Summary: This study investigates the performance and interpretability of machine learning-based energy usage models through the comparison of feature selection methods and analysis of model interpretability. The results suggest that the wrapper method is effective in improving model accuracy.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Emin Acikkalp, Arif Hepbasli, Ana I. Palmero-Marrero, David Borge-Diez
Summary: Different definitions of Zero-Energy Building (ZEB) have been proposed, including zero energy, zero carbon, zero exergy, and zero cost. This study introduces the concept of net zero extended exergy buildings, which combines extended exergy and net zero exergy building concepts to measure the exergetic footprint. The proposed methodology is applied to a building, and the results indicate the required peak power and electrical energy for meeting the electricity demand.
JOURNAL OF BUILDING ENGINEERING
(2023)
Editorial Material
Multidisciplinary Sciences
Katharine Sanderson
Summary: The built environment presents a significant opportunity for implementing a circular economy, with standardization, smart design, and implementation being crucial for enabling this transition.
Article
Thermodynamics
Wenqiang Cao, Junqi Yu, Mengyao Chao, Jingqi Wang, Siyuan Yang, Meng Zhou, Meng Wang
Summary: In this paper, an integrated energy consumption prediction model considering spatial characteristics in time series data is proposed to predict the short-term energy consumption of educational buildings. The influence of features on the model is analyzed using the cooperative game theory SHAP method, and the optimal number of features is determined by ablation analysis. The results show that the proposed model achieves higher prediction accuracy compared to other models, with reduced RMSE and MAE values.
Article
Energy & Fuels
Adamantios Bampoulas, Fabiano Pallonetto, Eleni Mangina, Donal P. Finn
Summary: This paper addresses the challenge of assessing uncertainty in energy flexibility predictions by developing a methodology that quantifies the flexibility of multiple thermal and electrical systems considering different types of uncertainty associated with building energy use. A Bayesian convolutional neural network is developed to capture aleatoric and epistemic uncertainty related to energy conversion device operation and temperature deviations resulting from exploiting building flexibility. The developed prediction models utilise residential occupancy patterns and a sliding window technique and achieve excellent performance, with coefficients of determination between 0.93 and 0.99.
Article
Thermodynamics
Daniel Leiria, Hicham Johra, Anna Marszal-Pomianowska, Michal Zbigniew Pomianowski
Summary: This article introduces a new methodology to disaggregate the energy demand for space heating and domestic hot water production from single hourly smart heat meters in Denmark. The new approach can be easily applied to different building types without detailed knowledge about the dwellings and occupants. The paper presents and compares various algorithms to separate and estimate the space heating and domestic hot water demand. The validation using a dataset of 28 Danish apartments shows that the best method to identify data points related to domestic hot water production events is the maximum peaks approach. The combination of a Kalman filter and Support Vector Regression is found to be the best algorithm to estimate the space heating and domestic hot water demand separately, outperforming the current Danish compliances.
Article
Construction & Building Technology
Xing Lu, Saptarshi Bhattacharya, Himanshu Sharma, Veronica Adetola, Zheng O'Neill
Summary: This paper investigates the impacts of nonidealities from occupancy counting and presence sensors on occupancy-centric controls (OCCs) and proposes a Bayesian Optimization (BO)-based smart sampling approach to efficiently identify the most impactful sensor nonideality sets. The results show that sensor bias and latency can increase HVAC and whole building energy consumption, and higher false positive rates of presence sensors have a direct impact on energy consumption.
ENERGY AND BUILDINGS
(2022)
Article
Thermodynamics
Domenico Altieri, Martin K. Patel, Joel Lazarus, Giovanni Branca
Summary: Low-cost optimization measures have the potential to significantly reduce the need for invasive and costly retrofitting interventions. However, due to the lack of data collection processes and optimal implementation strategies, these measures are often underutilized. This study used a unique dataset of 92 residential buildings to identify the most effective actions for energy savings. By training an Artificial Neural Network and analyzing sensitivity indices, the study quantifies the impact of each measure on energy consumption variability and identifies the most probable intervals of energy savings.
Review
Construction & Building Technology
Shiyu Han, Runming Yao, Nan Li
Summary: Energy conservation policies of buildings (ECPB) involve national plans, laws, and regulations to improve energy efficiency and reduce carbon emissions. However, increasing the effectiveness of national policy is challenging due to historical, social, economic, and environmental complexities. Future policy designs should be careful and scientific, building on past achievements and addressing existing problems.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Construction & Building Technology
Samiran Khorat, Debashish Das, Rupali Khatun, Sk Mohammad Aziz, Prashant Anand, Ansar Khan, Mattheos Santamouris, Dev Niyogi
Summary: Cool roofs can effectively mitigate heatwave-induced excess heat and enhance thermal comfort in urban areas. Implementing cool roofs can significantly improve urban meteorology and thermal comfort, reducing energy flux and heat stress.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Qi Li, Jiayu Chen, Xiaowei Luo
Summary: This study focuses on the vertical wind conditions as a main external factor that limits the energy assessment of high-rise buildings in urban areas. Traditional tools for energy assessment of buildings use a universal vertical wind profile estimation, without taking into account the unique wind speed in each direction induced by the various shapes and configurations of buildings in cities. To address this limitation, the study developed an omnidirectional urban vertical wind speed estimation method using direction-dependent building morphologies and machine learning algorithms.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Xiaojun Luo, Lamine Mahdjoubi
Summary: This paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy allocation and transmission among multiple domestic buildings. Machine learning is used to predict energy generation and consumption patterns, and the proposed framework establishes optimal and automated energy allocation through peer-to-peer energy transactions. The approach contributes to the reduction of greenhouse gas emissions and enhances environmental sustainability.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ying Yu, Yuanwei Xiao, Jinshuai Chou, Xingyu Wang, Liu Yang
Summary: This study proposes a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Case studies show that the proposed design significantly improves the performance of building clusters, reduces energy storage capacity, and shortens the payback period.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Felix Langner, Weimin Wang, Moritz Frahm, Veit Hagenmeyer
Summary: This paper compares two main approaches to consider uncertainties in model predictive control (MPC) for buildings: robust and stochastic MPC. The results show that compared to a deterministic MPC, the robust MPC increases the electricity cost while providing complete temperature constraint satisfaction, while the stochastic MPC slightly increases the electricity cost but fulfills the thermal comfort requirements.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Somil Yadav, Caroline Hachem-Vermette
Summary: This study proposes a mathematical model to evaluate the performance of a Double Skin Facade (DSF) system and its impact on indoor conditions. The model considers various design parameters and analyzes their effects on the system's electrical output and room temperature.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ruijun Chen, Holly Samuelson, Yukai Zou, Xianghan Zheng, Yifan Cao
Summary: This research introduces an innovative resilient design framework that optimizes building performance by considering a holistic life cycle perspective and accounting for climate projection uncertainties. The study finds that future climate scenarios significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density being major factors. By using ensemble learning and optimization algorithms, predictions for carbon emissions, cost, and indoor discomfort hours can be made, and the best resilient design scheme can be selected. Applying this framework leads to significant improvements in building life cycle performance.
ENERGY AND BUILDINGS
(2024)