Article
Economics
Simon Moeller, Amelie Bauer
Summary: Insulation and sealing of building envelopes are effective strategies to improve energy efficiency and reduce energy consumption. However, these measures may also result in energy performance gaps, where actual consumption exceeds calculated demand. The interactions between occupants and buildings play a crucial role in contributing to these gaps, leading to unintended negative consequences for energy consumption.
Article
Construction & Building Technology
Nikhil Singh Yaduvanshi, June Young Park
Summary: This research examines the impact of citizen involvement in residential building retrofits in the United States, focusing on single-family houses. The study highlights the importance of the residential sector in greenhouse gas emissions and the potential of energy retrofits to mitigate this impact. Through a comprehensive review of 66 retrofit programs and text mining on social media data, the research identifies various citizen involvement approaches and citizen perceptions of retrofit practices. The concept of Citizen Building Scientist is introduced to represent proactive and environmentally aware citizens who actively participate in and share knowledge for sustainable practices.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Huijeong Kim, Sangwoo Ham, Marlen Promann, Hemanth Devarapalli, Geetanjali Bihani, Tatiana Ringenberg, Vanessa Kwarteng, Ilias Bilionis, James E. Braun, Julia Taylor Rayz, Leigh Raymond, Torsten Reimer, Panagiota Karava
Summary: This paper presents a cloud-based eco-feedback and gaming platform that aims to promote energy conserving thermostat-adjustment behaviors. The platform integrates personalized eco-feedback design and a collaborative social game to assist residents in enhancing their thermostat use while promoting community-level energy savings. The results from a field study show the positive effect of the intervention in thermostat-adjustment behaviors, indicating the significant potential of the platform in nudging households' energy conservation behaviors.
BUILDING AND ENVIRONMENT
(2022)
Article
Green & Sustainable Science & Technology
Arezoo Shirazi, Sidney Newton, Pernille H. Christensen
Summary: Australia's building energy use is a significant contributor to energy consumption and greenhouse gas emissions. Smart and sustainable building management practices can improve efficiency and sustainability. This study examined the energy consumption and management of a university building in Sydney, Australia, using mobile phone applications and portable sensors.
Article
Green & Sustainable Science & Technology
Shady Jami, Nima Forouzandeh, Zahra Sadat Zomorodian, Mohammad Tahsildoost, Maryam Khoshbakht
Summary: This study highlights the importance of considering occupant energy behavior in assessing energy efficiency in buildings. By analyzing different OEB scenarios, the study shows the varying impacts of energy conservation measures on energy savings, and provides a decision-making tool for prioritizing ECMs.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Energy & Fuels
Raad Z. Homod, Hayder Ibrahim Mohammed, Aissa Abderrahmane, Omer A. Alawi, Osamah Ibrahim Khalaf, Jasim M. Mahdi, Kamel Guedri, Nabeel S. Dhaidan, A. S. Albahri, Abdellatif M. Sadeq, Zaher Mundher Yaseen
Summary: This study proposes a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adds a pre-cooling coil in the air handling unit (AHU) to alleviate the coupling issue in HVAC systems. The DCLTML algorithm shows promising results in controlling HVAC systems, with significant energy savings and improved environmental comfort.
Article
Construction & Building Technology
Nour Haidar, Nouredine Tamani, Yacine Ghamri-Doudane, Alain Boujou
Summary: Optimizing building energy consumption is crucial for reducing environmental impact. Information technology can be used to deploy sensors in buildings and collect data on energy consumption and occupant behavior. A graph mining-based optimization method that combines behavior prediction and reinforcement learning is introduced to predict user behavior, detect errors, and refine the model.
BUILDING AND ENVIRONMENT
(2023)
Review
Green & Sustainable Science & Technology
Guofeng Qiang, Shu Tang, Jianli Hao, Luigi Di Sarno, Guangdong Wu, Shaoxing Ren
Summary: Green building (GB) strategies are crucial for reducing energy wastage in the building sector. Building Automation Systems (BAS) play a significant role in improving energy efficiency in GB. This study reviews articles published from 2008 to 2022, highlighting BAS applications, challenges, and future research directions in the BAS-GB domain. The findings emphasize the need for comprehensive integration of BAS and GB, considering uncertainties, long-term prediction, sustainability goals, and privacy and security concerns.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Engineering, Electrical & Electronic
Xun Dou, Yunfan Shao, Jun Wang, Qinran Hu
Summary: The paper addresses the challenge of energy trading in intelligent building clusters, proposing a heat-electricity joint bidding strategy for IBs in IBC. The results show that this method can improve the overall operating economy of IBC by 2.4% compared to independent bidding strategies.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
M. N. Uddin, Q. Wang, Hsi Hsien Wei, Hung Lin Chi, Meng Ni
Summary: This study introduces a new framework for automatic assessment of occupants' comfort and building indoor performance using BIM and the SD-ABM platform. The framework is able to predict occupant presence, comfort level, temperatures, and CO2 concentration in office spaces. Further research is needed to assess the efficiency of the framework.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Anurag Verma, Surya Prakash, Anuj Kumar
Summary: This article proposes an AI-based multi-agent topology building management and information system for energy-efficient buildings. By minimizing energy consumption and maximizing comfort level, the system achieves both high comfort level and energy efficiency.
IETE JOURNAL OF RESEARCH
(2023)
Article
Construction & Building Technology
Joao Gabriel Carrico de Lima Montenegro Duarte, Bruno Ramos Zemero, Ana Carolina Dias Barreto de Souza, Maria Emilia de Lima Tostes, Ubiratan Holanda Bezerra
Summary: This study aimed to improve energy efficiency in buildings through the use of BIM technology. A case study was conducted on two classrooms in an educational building in the Amazon region, evaluating and implementing energy-saving strategies to enhance the overall energy performance of the building.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Construction & Building Technology
Canjun Li, Han Zhu, Xiangchao Lian, Yuxin Liu, Xiaohan Li, Yanbo Feng
Summary: To achieve occupant-centric building and control, it is important to consider occupant behavior characteristics and develop operational strategies accordingly. By studying the time-lag of shading behavior, an advanced prediction model was proposed, improving prediction accuracy. Furthermore, an operational logic that meets energy savings and comfort requirements was derived by describing the dynamic distribution of office room occupancy.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Seyedeh Samaneh Ghazimirsaeid, Mansour Selseleh Jonban, Manthila Wijesooriya Mudiyanselage, Mousa Marzband, Jose Luis Romeral Martinez, Abdullah Abusorrah
Summary: This paper presents an effective energy management system (EMS) based on multi-agent systems (MAS) for the integration of distributed energy resources (DER) in electrical microgrids. The proposed model significantly improves overall energy efficiency and individual building profits, while promoting demand response (DR) load programs, reducing market clearing prices (MCP) and optimizing the management of building devices.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Liang Yu, Zhanbo Xu, Tengfei Zhang, Xiaohong Guan, Dong Yue
Summary: This paper investigates the coordination control problem of personal comfort systems (PCSs) and heating, ventilation, and air conditioning (HVAC) systems in a shared office space. The goal is to minimize energy consumption while maintaining comfortable individual thermal environment for each occupant. A real-time control algorithm based on attention-based multi-agent deep reinforcement learning is proposed. Simulation results show significant reductions in energy consumption and improvements in thermal comfort deviation.
BUILDING AND ENVIRONMENT
(2022)
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)