Article
Construction & Building Technology
Hussain Syed Asad, Hang Wan, Hewage Kasun, Sadiq Rehan, Gongsheng Huang
Summary: This paper proposes a distributed real-time optimal control scheme for HVAC systems, which breaks down the centralized problem into independent sub-problems and distributes the computation load to local computation units. The proposed scheme improves energy efficiency by using a dual decomposition mechanism and a projected sub-gradient method.
ENERGY AND BUILDINGS
(2022)
Article
Computer Science, Artificial Intelligence
Lijie Wang, Jiahong Xu, Yang Liu, C. L. Philip Chen
Summary: This article investigates the optimal consensus control problem for multiagent systems with input constraints. It proposes a single critic neural network with time-varying activation function for approximate optimal control and an improved learning law for weight update. It also designs an effective dynamic event-triggering mechanism to improve the utilization rate of communication resource. A simulation example is provided to support the effectiveness of the proposed method and the superiority of the designed mechanism.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Civil
Rui Chen, Christos G. Cassandras
Summary: We have developed an event-driven Receding Horizon Control scheme for a Mobility-on-Demand System in a transportation network, which reduces the complexity of the vehicle assignment problem and enables real-time implementation. Simulation results demonstrate the effectiveness of the RH controller in terms of real-time implementation and performance compared to known greedy heuristics.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Qinglai Wei, Zehua Liao, Ruizhuo Song, Pinjia Zhang, Zhuo Wang, Jun Xiao
Summary: This article solves the optimal control scheme for ice-storage air conditioning (IAC) system using a data-based adaptive dynamic programming (ADP) method for the first time. The developed ADP method improves system efficiency and reduces operation costs according to numerical results. The superiority of the developed algorithm is verified in comparison results.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Construction & Building Technology
Junqi Wang, Jin Hou, Jianping Chen, Qiming Fu, Gongsheng Huang
Summary: This study proposes a data-mining-powered event-driven optimal control (EDOC) for improving HVAC operation efficiency. The random forest algorithm is adopted to discover event-driven relationships in the operation data. Through simulations, the formulated EDOC strategy is shown to increase energy savings by 0.9%-4.6% compared to traditional time-driven optimal control, and it is easy to use and understand for engineers and operators to guide optimal control of building HVAC systems.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Engineering, Mechanical
Shanlin Liu, Ben Niu, Guangdeng Zong, Xudong Zhao, Ning Xu
Summary: This paper focuses on the event-triggered control problem for unknown nonlinear systems with input constraints. By introducing a nominal system and a discounted cost function, the original problem is transformed into an event-triggered optimal control problem. A data-driven model using recurrent neural networks is designed to approximate the unknown dynamics of the system. A single critic neural network is constructed to solve the Hamilton-Jacobi-Bellman equation with multiple nonlinear terms. The update law of the critic NN is designed to relax the persistence of excitation condition. The proposed event-triggered optimal controller ensures the boundedness of state variables and critic NN weight errors based on Lyapunov stability theory. The effectiveness of the control scheme is demonstrated through simulation examples.
NONLINEAR DYNAMICS
(2022)
Article
Energy & Fuels
Wenzhuo Li, Shengwei Wang, Choongwan Koo
Summary: This study introduces a real-time optimal control strategy for multi-zone VAV air-conditioning systems, utilizing a multi-agent based distributed optimization method to address large-scale mathematics programming challenges. Through schemes like temperature set-point reset, multi-objective optimization, and distributed optimization, it effectively balances thermal comfort, IAQ, and energy use while reducing programming challenges.
Article
Thermodynamics
Haidan Wang, Wenyi Wang, Yulong Song, Xu Yang, Paolo Valdiserri, Eugenia Rossi di Schio, Gangxu Yu, Feng Cao
Summary: This article proposes a novel model predictive controller for the transcritical CO2 cabin thermal management system, which can operate in real-time at the optimal discharge pressure while ensuring passenger comfort, thereby minimizing the total power consumption of the system.
APPLIED THERMAL ENGINEERING
(2023)
Article
Construction & Building Technology
Jin Hou, Xin Li, Hang Wan, Qin Sun, Kaijun Dong, Gongsheng Huang
Summary: Real-time optimal control is a critical tool for improving energy efficiency in HVAC systems, but obtaining a reliable and accurate model for optimization is challenging. This paper investigates the impact of model accuracy on optimization actions and demonstrates that event-based control can reduce negative rewards compared to time-based control.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Zhijia Huang, Xiaofeng Chen, Kaiwen Wang, Binbin Zhou
Summary: This study focuses on a hotel's central air conditioning system and uses support vector regression to establish a load-forecasting model. By optimizing energy consumption, the system achieves energy savings.
Article
Construction & Building Technology
Zihao Wang, Yang Zhao, Chaobo Zhang, Pengyue Ma, Xuanzhang Liu
Summary: This paper proposes a hierarchical architecture to improve the energy efficiency of building HVAC systems. By breaking down the large-scale distributed optimization task into several local optimization tasks and solving the overall optimization problem recursively, it effectively reduces the computation load for system-level control. Comparison with conventional control methods shows that the proposed framework achieves significant energy savings and improved computational efficiency.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Automation & Control Systems
Shirantha Welikala, Christos G. Cassandras
Summary: In this paper, we discuss the problem of estimating the states of a distributed network of nodes through a team of cooperating agents. We propose a distributed online agent controller where each agent controls their trajectory by solving a sequence of receding horizon control problems, and we also leverage machine learning to improve the computational efficiency.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Qinglai Wei, Tao Li, Derong Liu
Summary: The article introduces a deep reinforcement learning method to address air conditioning control problems with human expressions as input, aiming to improve work efficiency by eliminating human sleepiness.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Mathematics
Flavio Munoz, Ramon Garcia-Hernandez, Jose Ruelas, Juan E. Palomares-Ruiz, Carlos Alvarez-Macias
Summary: This paper presents a discrete-time neural inverse optimal control scheme for DX air conditioning systems, which approximates the dynamic model of the system using a RHONN identifier and designs a controller based on this model. Simulation results demonstrate the effectiveness of this approach and its ability to handle disturbances.
Article
Chemistry, Analytical
Luca Muratori, Lorenzo Peretto, Beatrice Pulvirenti, Raffaella Di Sante, Giovanni Bottiglieri, Federico Coiro
Summary: This study aims to reduce energy consumption in the cabin of an electric crane by controlling the air recirculation. A control strategy was tested and the optimal position of CO2 sensors inside the cabin was discussed. The uncertainty of indirect measurement of leakage flow was also investigated.
Article
Construction & Building Technology
Zhuangbo Feng, Xilian Luo, Junqi Wang, Shi-Jie Cao
Summary: This research aims to propose an energy-efficient environment control system for the protection and display of historical earthen sites. By optimizing the design parameters of ventilation and air conditioning, water and heat transfer between the sites and the environment can be effectively controlled. The proposed numerical strategy can provide a useful tool for similar physical environments.
ENERGY AND BUILDINGS
(2022)
Editorial Material
Construction & Building Technology
Junqi Wang, Chuck Wah Yu, Shi-Jie Cao
INDOOR AND BUILT ENVIRONMENT
(2022)
Article
Automation & Control Systems
Teng Long, Qing-Shan Jia
Summary: The article introduces a novel architecture consisting of hydrogen production stations, fast-charging stations, and commercial electric vehicles to optimize hydrogen energy dispatch and EV charging location selection. Case studies confirm the effectiveness of the architecture in reducing operating costs and improving performance by at least 13%.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2022)
Article
Construction & Building Technology
Haorui Wang, Junqi Wang, Zhuangbo Feng, Chuck Wah Yu, Shi-Jie Cao
Summary: The study developed an efficient Ventilation Mode with Deflector and Slot air outlets (VMDS) to achieve efficient indoor ventilation performance for large halls. The VMDS utilizes a deflector with slot air outlets to enhance ventilation performance. Numerical simulation and comprehensive evaluation were conducted to compare VMDS with three other side air supply modes. Results show that VMDS effectively reduces indoor air pollutant concentrations and transmission of infectious diseases in large spaces, while meeting energy efficiency and thermal comfort requirements.
INDOOR AND BUILT ENVIRONMENT
(2023)
Editorial Material
Construction & Building Technology
Junqi Wang, Chuck Wah Yu, Shi-Jie Cao
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Construction & Building Technology
Miao Yang, Chang Xi, Junqi Wang, Zhuangbo Feng, Shi-jie Cao
Summary: This paper proposes an interactive design framework for outdoor environmental paving (O-EP) and indoor ventilated atrium skylight orientation (I-VA), and investigates their impact on building carbon abatement and comfort. The results show that different combinations have significant differences, with the combination of water bodies of O-EP and 135 degrees of I-VA achieving higher carbon abatement rate and comfort than the worst combination by 17.5% and 15% respectively. Correlation analysis indicates that carbon abatement rate is significantly correlated with O-EP, while comfort is significantly correlated with O-EP in warmer seasons and with I-VA in cooler seasons.
ENERGY AND BUILDINGS
(2023)
Article
Chemistry, Physical
Zhiheng Zhang, Junqi Wang, You Li, Shuoyan Zhang, Lei Xiao, Jing Wang, Junjie Qi
Summary: In this study, MoX2 (X = S, Se, Te) nanostructures hybridized with TaS2 nanosheets were synthesized on self-supported carbon cloth electrode via a facile hydrothermal method. The MoSe2/TaS2/CC electrode with a Mo/Se ratio of 1:1.5 exhibited the best HER performance, achieving benchmark current densities of 10 mA/cm2 at overpotentials of 75 mV and Tafel slope values of 54.7 mV/dec. The MoX2 materials in this study showed durability and air stability, and the unique hybrids, including 1T and 2H phases of MoS2 and MoSe2, semimetallic 1T'-MoTe2 petal clusters, and strong interface interaction between MoX2 and conductive TaS2 nanosheets, contributed to superior HER catalytic performance.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Construction & Building Technology
Junqi Wang, Mingsong Ni, Jianping Chen
Summary: Due to global urbanization, the stock of older communities has been increasing and living conditions have continued to deteriorate. This study proposes an environmental renovation strategy to improve the outdoor environment of old communities by optimizing greenery and implementing wind deflectors.
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Construction & Building Technology
Jue Liu, Li Bao, Biyun Ye, Junqi Wang
Summary: With the advancement of urbanization, the energy consumption of public buildings is rapidly increasing. It is crucial to achieve sustainable development in buildings. The study proposes a progressive design approach for energy-saving and low carbon emission in building envelopes. The method was applied to an archive building in Nanjing, China, leading to significant reductions in energy consumption and CO2 emissions. This progressive design method provides a reference for future green building design and promotes the sustainable development of green and low-carbon buildings.
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Chemistry, Multidisciplinary
Lanhe Zhang, Sen Wang, Junqi Wang, Hong Jiang, Qiang Liu, Xin Cheng, Xiaohui Xu
Summary: A novel fluorescent composite anti-corrosion coating was prepared, which could simultaneously indicate corrosion sites and corrosion degree according to change of fluorescence intensity. Tri-HDI/GO/SR/AP coating was prepared by blending method, and its structure, physical properties, anti-corrosion ability and fluorescence intensity were analyzed. Results showed that Tri-HDI/GO/SR/AP coating was not significantly damaged during the corrosion simulation experiment, and the fluorescence intensity of the coating decreased with the increase of corrosion degree. Based on structure characterization and electrochemical analysis, it was found that Tri-HDI/GO/SR/AP coating has positive anti-corrosion performance, and the corrosion location and corrosion degree can be determined according to the changes of luminescence intensity.
JOURNAL OF THE CHINESE CHEMICAL SOCIETY
(2023)
Article
Construction & Building Technology
Chen Ren, Hao-Cheng Zhu, Junqi Wang, Zhuangbo Feng, Gang Chen, Fariborz Haghighat, Shi-Jie Cao
Summary: This paper aims to develop intelligent operation, maintenance, and control systems in public buildings by coupling intelligent ventilation and air purification systems. The optimal deployment of sensors is determined by Fuzzy C-mean (FCM) and CO2 concentration fields are predicted using artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators, and the optimal ventilation rates and number of generators are decided. The results showed reduced CO2 concentration, infection risk, and energy consumption, as well as high removal efficiency with a certain number of negative ion generators. The study contributes to the development of intelligent systems for infection prevention and energy sustainability.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Energy & Fuels
Chang Xi, Chen Ren, Ruijun Zhang, Junqi Wang, Zhuangbo Feng, Fariborz Haghighat, Shi-Jie Cao
Summary: Urban heat islands and heat waves caused by climate change can lead to increased carbon emissions and human health risks. Transportation contributes significantly to urban heat islands and greenhouse gas emissions, but nature-based solutions (NBS) can effectively mitigate these issues. This study quantitatively investigated the design of roadside green belts, considering traffic-generated heat. A new method called the urban traffic coupling source (UTCS) method was proposed to address the dynamic and complex diffusion of traffic heat. The impact of roadside green belts' locations and types on the thermal environment of motorized and non-motorized areas in cities was studied. The results showed that placing trees and shrubs near non-motorized lanes and sidewalks can effectively reduce temperatures in those areas. Furthermore, the study provided guidelines for the sustainable design of roadside green belts to enhance urban climate and achieve carbon neutrality.
Article
Environmental Sciences
Chen Ren, Junqi Wang, Zhuangbo Feng, Moon Keun Kim, Fariborz Haghighat, Shi-Jie Cao
Summary: To prevent the spread of respiratory infections in hospital wards, it is crucial to reduce the transmission risk of airborne pollutants. Ventilation modes are considered an important strategy, but their design is challenging. This study investigated the relationship between ventilation openings and infected patient locations, and found that the relative distance between outlets and infected patients is a critical factor. The results showed that stratum ventilation had the best infection risk mitigation effect, and the average infection risk was reduced to below 7% when the relative distance between outlets and infected patients was less than 0.25 times the cubic root of the ward volume. This study provides guidance for the systematic ventilation system design in hospitals during epidemics.
ENVIRONMENTAL POLLUTION
(2023)
Article
Construction & Building Technology
Jue Liu, Xinyi She, Junqi Wang
Summary: This paper proposes a two-level optimization framework for the layout and form design of building clusters. The effectiveness of the framework is demonstrated through a case design project. The results show that the layout of a building cluster has significant impacts on the outdoor thermal environment during different seasons.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Qiming Fu, Ke Li, Jianping Chen, Junqi Wang, You Lu, Yunzhe Wang
Summary: In this paper, the authors proposed a deep-forest-based DQN method (DF-DQN) for energy consumption prediction, which achieves higher prediction accuracy and shorter computation time compared to other methods. The DF-DQN method replaces the action space, introduces deep forest for mapping, and constructs new states using state class probabilities.