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
Mohamed M. Ouf, June Young Park, H. Burak Gunay
Summary: Occupant-centric control (OCC) strategies rely on algorithms to predict occupant patterns and preferences for optimizing building operations. This study presents a framework for testing OCCs in a simulation environment before field implementation, using synthetic occupant behavior models to compare different configurations efficiently.
BUILDING SIMULATION
(2021)
Review
Construction & Building Technology
Jose Rodriguez, Nelson Fumo
Summary: This paper explores the historical perspective of cooling and heating control, the general description of thermal zones in HVAC systems, and the zoning methods for residential HVAC systems. The study aims to review current research on zoning in HVAC systems and suggests the use of intelligent zoning strategies based on user behavior and modeling with white box and data-based models.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Davide Brunetti, Cristina Gena, Fabiana Vernero
Summary: This paper provides an overview of smart interactive technologies in the factory setting, with a focus on the visions of Industry 4.0 and 5.0. The importance of designing these technologies with a human-centric approach is emphasized, and guidelines are provided to assist future designers and adopters in making informed choices and implementing user-centric solutions.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Dan Zhao, Hancheng Lu, Yongqiang Gui, Yazheng Wang
Summary: The article introduces the user-centric networking (UCN) and reconfigurable intelligent surface (RIS) technologies, where the integration of RIS in UCN can enhance service quality and energy efficiency. A novel UCN architecture with RIS integration is proposed, and joint optimization of passive beamforming and power allocation is performed to maximize the total rate of all users.
IEEE COMMUNICATIONS MAGAZINE
(2021)
Article
Construction & Building Technology
Eikichi Ono, Kuniaki Mihara, Khee Poh Lam, Adrian Chong
Summary: Incorporating data-driven thermal comfort models into occupant-centric HVAC controls is crucial for meeting occupants' preferences in thermal comfort. A mismatch between the occupancy resolutions of thermal comfort modeling and HVAC controls can lead to decreased voting for no change in thermal and air movement preferences, but also increased energy savings when considering a suitable comfort model for the HVAC control.
BUILDING AND ENVIRONMENT
(2022)
Review
Construction & Building Technology
Amir Tabadkani, Astrid Roetzel, Hong Xian Li, Aris Tsangrassoulis
Summary: The importance of occupant-centric control strategies in controlling shading systems is emphasized in this research, as it can enhance user satisfaction and comfort. Automatic control strategies may lead to users being unable to intervene in the operation of shading systems.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Thermodynamics
Wenli Zhang, Guoqiang Cui, Yufei Wang, Chao Zheng, Qingyu Zhu
Summary: This study proposes a high-precision human comfort prediction method for indoor personnel based on time-series analysis as the control strategy for HVAC systems. The method includes the data pre-processing module, the class imbalance processing module, and the human comfort network model module. The Human-Comfort Bi-directional Long Short-Term Memory (HC-BiLSTM) network and the Synthetic Minority Oversampling Technique for Time-series (SMOTE-TS) algorithm are utilized to achieve better prediction accuracy and solve the class imbalance problem in the dataset. The experimental results on a public dataset collected in Pennsylvania, USA, show that the proposed method achieves the highest accuracy in known related research, with 0.9482 and 0.9659 on Macro-averaging and Micro-averaging, respectively.
BUILDING SIMULATION
(2023)
Article
Energy & Fuels
Meng Kong, Bing Dong, Rongpeng Zhang, Zheng O'Neill
Summary: Sensing technologies in buildings have advanced rapidly in the past two decades, with occupancy sensing systems being developed to track occupant behavior. Occupancy-based building system control can improve energy efficiency and occupant comfort, with studies showing potential energy savings and comfort maintenance. A study integrating three state-of-the-art occupancy sensing technologies into HVAC system control found that occupancy-based control can maintain good thermal comfort and indoor air quality satisfaction, with weekly energy savings averaging between 17% and 24%.
Review
Green & Sustainable Science & Technology
Wuxia Zhang, Yupeng Wu, John Kaiser Calautit
Summary: The presence, activities, and behaviour of occupants greatly influence building performance and energy efficiency. Traditional HVAC systems often rely on assumed occupancy levels and fixed schedules, or manual adjustments by occupants based on their comfort needs. However, the unpredictable and variable occupancy patterns can lead to over- or under-conditioning of spaces, affecting indoor air quality and comfort. Therefore, machine learning models and methodologies are increasingly being used to forecast occupancy behaviour in buildings, aiming to improve the design and operation of building systems.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Engineering, Electrical & Electronic
Izhar, Wei Xu, Lung-Jieh Yang, Yi-Kuen Lee
Summary: This paper presents an optimized CMOS compatible MEMS thermoresistive calorimetric air velocity sensor for measuring small air velocity in indoor environments. The sensor achieved high sensitivity and accuracy in the small air velocity range through optimized dimensions and manufacturing processes. Experimental results demonstrate that the sensor is suitable for integration into smart HVAC systems.
IEEE SENSORS JOURNAL
(2021)
Article
Green & Sustainable Science & Technology
Shahira Assem Abdel-Razek, Hanaa Salem Marie, Ali Alshehri, Omar M. Elzeki
Summary: Room occupancy prediction based on indoor environmental quality is crucial for energy efficiency and interior design. This research evaluated the accuracy of room occupancy recognition using different datasets. The results showed that KNN performed the best among the classification models tested. By using SHAP, the interpretability of the models was improved.
Article
Engineering, Electrical & Electronic
Zelin Nie, Wei Cheng, Guanghui Zhou, Xuefeng Chen, Chao-Bo Yan, Feng Gao
Summary: Nuclear power is the largest source of clean energy in the world. However, there is a capacity shortage in the nuclear power market. To improve the working environment of nuclear power plants, heating, ventilation, and air conditioning (HVAC) systems should be implemented. It is also recommended to combine nuclear power with ice storage to provide supplemental cooling during peak demand times.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Review
Construction & Building Technology
Saman Taheri, Paniz Hosseini, Ali Razban
Summary: Intelligent buildings use predictive technologies to optimize HVAC systems, reducing energy consumption while maintaining comfort. Model predictive control is an effective management method that can enhance energy efficiency by considering multiple objectives.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Dana Miller, Paul Raftery, Mia Nakajima, Sonja Salo, Lindsay T. Graham, Therese Peffer, Marta Delgado, Hui Zhang, Gail Brager, David Douglass-Jaimes, Gwelen Paliaga, Sebastian Cohn, Mitch Greene, Andy Brooks
Summary: The study found that using ceiling fans and air conditioning together in commercial buildings can save a significant amount of compressor energy consumption and improve occupant comfort. This system can automatically control the operation of ceiling fans and air conditioning based on temperature changes, providing better energy efficiency compared to using air conditioning alone.
ENERGY AND BUILDINGS
(2021)
Article
Computer Science, Interdisciplinary Applications
Wooyoung Jung, Ghang Lee
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2016)
Article
Energy & Fuels
Farrokh Jazizadeh, Wooyoung Jung
Article
Construction & Building Technology
Wooyoung Jung, Farrokh Jazizadeh
BUILDING AND ENVIRONMENT
(2018)
Article
Construction & Building Technology
Wooyoung Jung, Farrokh Jazizadeh
BUILDING AND ENVIRONMENT
(2019)
Article
Chemistry, Analytical
Wooyoung Jung, Farrokh Jazizadeh, Thomas E. Diller
Article
Energy & Fuels
Wooyoung Jung, Farrokh Jazizadeh
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)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Wooyoung Jung, Matthew Chan, Farrokh Jazizadeh, Thomas E. Diller
COMPUTING IN CIVIL ENGINEERING 2019: SMART CITIES, SUSTAINABILITY, AND RESILIENCE
(2019)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Wooyoung Jung, Farrokh Jazizadeh
ADVANCED COMPUTING STRATEGIES FOR ENGINEERING, PT II
(2018)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Wooyoung Jung, Farrokh Jazizadeh
BUILDSYS'17: PROCEEDINGS OF THE 4TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILT ENVIRONMENTS
(2017)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.