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Application of Data-Driven Method for HVAC System
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Application of Data-Driven Method for HVAC System

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (25 May 2023) | Viewed by 26879

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Yabin Guo

E-Mail Website
Guest Editor
School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: fault detection and diagnosis of HVAC systems; data-driven method; data mining; building energy saving
Dr. Zhanwei Wang

E-Mail Website
Guest Editor
Institute of Building Energy and Thermal Science, Henan University of Science and Technology, Luoyang 471023, China
Interests: fault detection and diagnosis for HVAC&R systems; energy conservation in buildings
Dr. Yunpeng Hu

E-Mail Website
Guest Editor
Department of Building Environment and Energy Engineering, Wuhan Business University, Wuhan, Hubei, China
Interests: fault detection and diagnosis for HVAC&R systems
Dr. João M. M. Gomes

E-Mail Website
Guest Editor
Department of Electrical Engineering, ISE, University of Algarve, 8005-139 Faro, Portugal
Interests: building energy savings; fault detection for electrical energy systems; HVAC control systems; renewable energies

Special Issue Information

Dear Colleagues,

To confront the global energy shortage problem, the development of energy saving strategies and establishing the stable operation of HVAC systems are crucial steps forward. Taking a data-driven approach to HVAC system data analysis could be essential for identifying new solutions to these challenges.

At present, big data technology, as a hot research topic, has found wide application in various fields. Data-driven methods are useful in many aspects of HVAC systems, such as in fault detection and diagnosis, energy consumption prediction, optimal control, and mining HVAC operation data to obtain valuable information. They may also be employed in in-depth experimental and environmental data analysis. The application potential of data-driven methods thus ought to be further explored.

This Special Issue, entitled “Application of data-driven method for HVAC System”, is dedicated to providing an overview of the latest achievements in the application of data-driven methods for HVAC systems. Topics of interest include, but are not limited to:

  • Fault detection and diagnosis of HVAC systems;
  • Energy consumption prediction;
  • Model predictive control;
  • Data mining and analysis of HVAC systems;
  • Data mining and analysis of building environment;
  • Energy conservation;
  • Energy saving.

Dr. Yabin Guo
Dr. Zhanwei Wang
Dr. Yunpeng Hu
Dr. João M. M. Gomes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fault detection
  • fault diagnosis
  • air-conditioning and refrigeration systems
  • data-driven method
  • machine learning
  • data mining
  • energy saving
  • building environment
  • smart building
  • energy conservation

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Published Papers (14 papers)

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Editorial

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4 pages, 190 KiB  
Editorial
Application of Data-Driven Methods for Heating Ventilation and Air Conditioning Systems
by Yabin Guo, Yaxin Liu, Zhanwei Wang and Yunpeng Hu
Processes 2023, 11(11), 3133; https://doi.org/10.3390/pr11113133 - 2 Nov 2023
Viewed by 1035
Abstract
At present, with the continuous global energy crisis, buildings, as a significant factor in energy consumption, have significant importance in achieving the energy-saving operation of buildings [...] Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)

Research

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14 pages, 8183 KiB  
Article
An Experimental Study on Temperature, Relative Humidity, and Concentrations of CO and CO2 during Different Cooking Procedures
by Xi Chen, Yahui Gao, Liu Yang, Yang Liu, Miaomiao Qin, Jialing Xia and Peng Wang
Processes 2023, 11(9), 2648; https://doi.org/10.3390/pr11092648 - 4 Sep 2023
Cited by 1 | Viewed by 1486
Abstract
In order to explore the indoor air quality during different cooking procedures, a very common kitchen in China is selected for experimental research. An indoor air quality meter is used to measure the temperature, relative humidity, and CO and CO2 concentrations of [...] Read more.
In order to explore the indoor air quality during different cooking procedures, a very common kitchen in China is selected for experimental research. An indoor air quality meter is used to measure the temperature, relative humidity, and CO and CO2 concentrations of the indoor air above the stove when people cook four different dishes under different ventilation patterns in the kitchen. The results indicate that the heat and gas consumed during cooking are closely related to the temperature and concentrations of CO and CO2. Some cooking procedures such as boiling water are related to the indoor air temperature and relative humidity in the kitchen. In addition, in kitchens without mechanical ventilation, natural ventilation shows a more significant positive effect on controlling temperature, relative humidity, and concentrations of CO and CO2 during cooking procedures. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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22 pages, 4267 KiB  
Article
Optimization of Cost–Carbon Reduction–Technology Solution for Existing Office Parks Based on Genetic Algorithm
by Zhenlan Dou, Lu Jin, Yinhui Chen and Zishuo Huang
Processes 2023, 11(8), 2452; https://doi.org/10.3390/pr11082452 - 15 Aug 2023
Cited by 2 | Viewed by 1279
Abstract
With limited investment costs, how to fully utilize the carbon-reduction capacity of a campus in terms of buildings, equipment, and energy is an important issue when realizing the low-carbon retrofit of office parks. To this end, this paper establishes a mathematical optimization model [...] Read more.
With limited investment costs, how to fully utilize the carbon-reduction capacity of a campus in terms of buildings, equipment, and energy is an important issue when realizing the low-carbon retrofit of office parks. To this end, this paper establishes a mathematical optimization model for the decarbonization-based retrofit of existing office parks, based on the genetic algorithm, taking into account the relationship between cost, energy-consumption, and carbon-emissions, and taking the maximum carbon reduction of the park over its whole life as the optimization goal. The validity of the model was verified in conjunction with a case study of an office park in Nanchang, China. The case study shows that, compared with current typical parks, the carbon reduction through an office park’s decarbonization retrofit has a non-linear correlation with the investment cost, and when the total investment cost of the park is above CNY 60 million, the increase in carbon reduction with the increase in the investment cost is gradually weakened, and the park achieves the maximum carbon reduction of 236,087 t when the investment cost reaches CNY 103 million. Under the current technical and economic conditions, the investment-cost–carbon-reduction benefits of different carbon-reduction technologies are different, the carbon-reduction benefit of increasing renewable energy utilization is the best, and the carbon-reduction benefit of upgrading the energy efficiency of the park’s supply-and-use system is lower than that of renewable energy utilization, but better than that of upgrading the performance of the building envelope system. In addition, the configuration of the parameters of the same low-carbon technology in different forms of buildings varies significantly, due to differences in the building form and daily use. The model established in this paper is able to give a comprehensive optimized building–equipment–energy configuration plan for existing office parks, when maximizing carbon reduction under different investment costs, which guides the park’s decarbonization retrofit. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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20 pages, 17832 KiB  
Article
Experimental Study on Convection and Heat Conduction Heating of an Air-Conditioned Bed System under Winter Lunch Break Mode
by Junjie Jin, Peiyao Duan, Yu Liu, Honglin Chen and Tingting Yu
Processes 2023, 11(8), 2391; https://doi.org/10.3390/pr11082391 - 9 Aug 2023
Viewed by 2544
Abstract
In this paper, an experimental study of a system for heating an air-conditioned bed during a 2 h lunch was carried out. The results show that the power consumption of heat conduction heating was only 0.34 kW·h and that the average heat dissipation [...] Read more.
In this paper, an experimental study of a system for heating an air-conditioned bed during a 2 h lunch was carried out. The results show that the power consumption of heat conduction heating was only 0.34 kW·h and that the average heat dissipation was 81.3 W, while the power consumption of convection heating was 1.43 kW·h, accompanied by an average heat dissipation of 748.7 W. Regardless of the power consumption or the heat dissipation, the convection heating was significantly higher than the heat conduction heating. As a result, the room air temperature increased from 12.3 °C to 17.3 °C under convection heating, but only increased from 14.4 °C to 15.2 °C under heat conduction heating. The study results indicate that when using heat conduction heating, water temperatures in the range of 38~40 °C could meet the thermal comfort needs of the human body; however, a higher temperature range was required when using convection heating. In contrast, the grade of the hot water required for heat conduction heating was lower. It was also found that the temperature under convection heating rises faster, but it tends to lead to a dry feeling after a long time, while the conductive heating showed a slower temperature rise. There was a cool feeling for 20 min when the heating started, and then the thermal comfort improved. The air-conditioning system in this paper was investigated in a heating experiment in the winter lunch break mode and compared with convection heating. The heat conduction heating resulted in better thermal comfort and higher energy efficiency. It is suggested to adopt the heat conduction heating mode in the winter heating operation of this system. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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21 pages, 3439 KiB  
Article
Fault Diagnosis Based on Fusion of Residuals and Data for Chillers
by Zhanwei Wang, Boyang Liang, Jingjing Guo, Lin Wang, Yingying Tan, Xiuzhen Li and Sai Zhou
Processes 2023, 11(8), 2323; https://doi.org/10.3390/pr11082323 - 2 Aug 2023
Cited by 2 | Viewed by 1036
Abstract
Feature data refer to direct measurements of specific features, while feature residuals represent the deviations between these measurements and their corresponding benchmark values. Both types of information offer unique insights into the system’s behavior. However, conventional diagnostic systems often struggle to effectively integrate [...] Read more.
Feature data refer to direct measurements of specific features, while feature residuals represent the deviations between these measurements and their corresponding benchmark values. Both types of information offer unique insights into the system’s behavior. However, conventional diagnostic systems often struggle to effectively integrate and utilize both types of information concurrently. To address this limitation and improve diagnostic performance, a hybrid method based on the Bayesian network (BN) is proposed. This method enables the parallel fusion of feature residuals and feature data within a unified diagnostic model, and a comprehensive framework for developing this hybrid method is also given. In the hybrid BN, the symptom layer consists of residual nodes representing feature residuals and data nodes representing measured feature data. By applying the proposed method to two chillers and comparing it with state-of-the-art existing methods, we demonstrate its effectiveness and superiority. The results highlight that the proposed method not only accommodates the absence of either type of information but also leverages both of them to enhance diagnostic performance. Compared to using a single type of node, the hybrid method achieves a maximum improvement of 24.5% in diagnostic accuracy, with significant enhancements in F-measure observed for refrigerant leakage fault (34.5%) and excessive lubricant fault (32.8%), respectively. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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23 pages, 77173 KiB  
Article
Research on Passive Design Strategies for Low-Carbon Substations in Different Climate Zones
by Shuizhong Zhao, Jiangfeng Si, Gang Chen, Hong Shi, Yusong Lei, Zhaoyang Xu and Liu Yang
Processes 2023, 11(6), 1814; https://doi.org/10.3390/pr11061814 - 14 Jun 2023
Cited by 2 | Viewed by 1282
Abstract
In the energy-saving design of substations, the building envelope thermal parameters, window-to-wall ratio, and shape factor are three crucial influencing factors. They not only affect the building’s appearance but also have an important impact on the total building energy consumption. In this paper, [...] Read more.
In the energy-saving design of substations, the building envelope thermal parameters, window-to-wall ratio, and shape factor are three crucial influencing factors. They not only affect the building’s appearance but also have an important impact on the total building energy consumption. In this paper, we applied the energy consumption simulation software DeST-c to study the influence of the above three elements on the total energy consumption of the building in a representative city with different thermal zones. The optimal envelope thermal parameters, optimal window-to-wall ratio, and optimal shape factor were derived through combination with economic analysis. Finally, the sensitivity analysis of different elements was carried out to determine the suitable passive design solutions for substations in different climate zones. It was found that the thickness of roof insulation has the greatest influence on the energy consumption of substation buildings among all envelopes. The optimal window-to-wall ratios were 0.4, 0.4~0.5, 0.3, 0.3~0.4, and 0.5 for severe cold, cold, hot summer and cold winter, hot summer and warm winter, and mild regions, respectively; and the optimal shape factors were 0.29, 0.30, 0.23, 0.31, and 0.33, respectively. The conclusions of this study can provide architects with energy-saving design strategies and suggestions for substations in different climate zones, and provide references for building energy-saving designs and air conditioning and heating equipment selection. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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19 pages, 4315 KiB  
Article
Operation Pattern Recognition of the Refrigeration, Heating and Hot Water Combined Air-Conditioning System in Building Based on Clustering Method
by Yabin Guo, Jiangyan Liu, Changhai Liu, Jiayin Zhu, Jifu Lu and Yuduo Li
Processes 2023, 11(3), 812; https://doi.org/10.3390/pr11030812 - 8 Mar 2023
Cited by 4 | Viewed by 1515
Abstract
Air-conditioning system operation pattern recognition plays an important role in the fault diagnosis and energy saving of the building. Most machine learning methods need labeled data to train the model. However, the difficulty of obtaining labeled data is much greater than that of [...] Read more.
Air-conditioning system operation pattern recognition plays an important role in the fault diagnosis and energy saving of the building. Most machine learning methods need labeled data to train the model. However, the difficulty of obtaining labeled data is much greater than that of unlabeled data. Therefore, unsupervised clustering models are proposed to study the operation pattern recognition of the refrigeration, heating and hot water combined air-conditioning (RHHAC) system. Clustering methods selected in this study include K-means, Gaussian mixture model clustering (GMMC) and spectral clustering. Further, correlation analysis is used to eliminate the redundant characteristic variables of the clustering model. The operating data of the RHHAC system are used to evaluate the performance of proposed clustering models. The results show that clustering models, after removing redundant variables by correlation analysis, can also identify the defrosting operation mode. Moreover, for the GMMC model, the running time is reduced from 27.80 s to 10.04 s when the clustering number is 5. The clustering performance of the original feature set model is the best when the number of clusters of the spectral clustering model is two and three. The clustering hit rate is 98.99%, the clustering error rate is 0.58% and the accuracy is 99.42%. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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20 pages, 910 KiB  
Article
Peak Load Shifting Control for a Rural Home Hotel Cluster Based on Power Load Characteristic Analysis
by Weilin Li, Yonghui Liang, Jianli Wang, Zhenhe Lin, Rufei Li and Yu Tang
Processes 2023, 11(3), 682; https://doi.org/10.3390/pr11030682 - 23 Feb 2023
Viewed by 1512
Abstract
The large-scale rural home hotel clusters have brought huge pressure to the rural power grid. However, the load of rural home hotels not only has the inherent characteristics of rural residential buildings but is also greatly impacted by the occupancy rate, which is [...] Read more.
The large-scale rural home hotel clusters have brought huge pressure to the rural power grid. However, the load of rural home hotels not only has the inherent characteristics of rural residential buildings but is also greatly impacted by the occupancy rate, which is very different from conventional buildings. Therefore, the existing peak shifting strategies are difficult to apply to rural home hotels. In view of the above problems, this study took a typical visitor village in Zhejiang Province as the research object, which had more than 470 rural home hotels. First, through a basic information survey and power load data collection, the characteristics of its power load for heating, cooling and transition months were studied, and a “No Visitors Day” model was proposed, which was split to obtain the seasonal load curve for air conditioning. Then, combined with the characteristics of the air conditioning power load and the natural conditions of the rural house, a cluster control peak-load-shifting system using phase change energy storage was proposed, and the system control logic was determined and established. Finally, the collected power load data was brought into the model for actual case analysis to verify its feasibility and the effect of peak-load shifting. The results showed that due to the influence of the number of tourists, the electricity loads on weekends and holidays were higher, especially the electricity load of air conditioning equipment in the heating and cooling seasons. An actual case was simulated to verify the peak-shifting effect of the proposed regulation strategy; it was found that the maximum peak load of the cluster was reduced by 61.6%, and the peak–valley difference was 28.6% of that before peak shifting. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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25 pages, 33065 KiB  
Article
Cooling and Water Production in a Hybrid Desiccant M-Cycle Evaporative Cooling System with HDH Desalination: A Comparison of Operational Modes
by Lanbo Lai, Xiaolin Wang, Gholamreza Kefayati and Eric Hu
Processes 2023, 11(2), 611; https://doi.org/10.3390/pr11020611 - 16 Feb 2023
Cited by 2 | Viewed by 2620
Abstract
In this paper, the cooling and freshwater generation performance of a novel hybrid configuration of a solid desiccant-based M-cycle cooling system (SDM) combined with a humidification–dehumidification (HDH) desalination unit is analysed and compared in three operational modes: ventilation, recirculation, and half recirculation. The [...] Read more.
In this paper, the cooling and freshwater generation performance of a novel hybrid configuration of a solid desiccant-based M-cycle cooling system (SDM) combined with a humidification–dehumidification (HDH) desalination unit is analysed and compared in three operational modes: ventilation, recirculation, and half recirculation. The HDH unit in this system recycles the moist waste air sourced from the M-cycle cooler and rotary desiccant wheel of the SDM system to enhance water production. A mathematical model was established and solved using TRNSYS and EES software. The results of this study indicate that the recirculation mode exhibited superior cooling performance compared to the other two modes, producing up to 7.91 kW of cooling load and maintaining a supply air temperature below 20.85 °C and humidity of 12.72 g/kg under various ambient conditions. All the operational modes showed similar water production rates of around 52.74 kg/h, 52.43 kg/h, and 52.14 kg/h for the recirculation, half-recirculation and ventilation modes, respectively, across a range of operating temperatures. The recirculation mode also exhibited a higher COP compared to the other modes, as the environmental temperature and relative humidity were above 35 °C and 50%. However, it should be noted that the implementation of the recirculation mode resulted in a higher water consumption rate, with a maximum value of 5.52 kg/h when the inlet air reached 45 °C, which partially offset the benefits of this mode. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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25 pages, 10642 KiB  
Article
Data Analysis and Optimization of Thermal Environment in Underground Commercial Building in Zhengzhou, China
by Xi Zhao, Cheng Li, Jiayin Zhu, Yu Chen and Jifu Lu
Processes 2022, 10(12), 2584; https://doi.org/10.3390/pr10122584 - 4 Dec 2022
Cited by 1 | Viewed by 1800
Abstract
Underground commercial buildings have received increasing attention as an emerging place of consumption. However, previous studies on underground commercial buildings have mainly focused on the impact of a specific environment on comfort or energy consumption. Few studies have been conducted from the perspective [...] Read more.
Underground commercial buildings have received increasing attention as an emerging place of consumption. However, previous studies on underground commercial buildings have mainly focused on the impact of a specific environment on comfort or energy consumption. Few studies have been conducted from the perspective of functional use. The purpose of this paper is to investigate, in terms of functional angles, the indoor thermal environment and air quality of an underground commercial building in Zhengzhou, China, and put forward an optimal control strategy of ventilation organization. The results showed that the relative humidity of the underground shopping mall was generally above 60%, and the average temperature of 29.1 °C led to a thermal comfort problem in the catering area in summer. Meanwhile, the concentration of CO2 exceeded the allowed figures during the peak of the customer flow rate, and PM2.5 concentration in the catering area also exceeded the standard, by 43.3% and 33.3%, respectively. Furthermore, to solve the indoor thermal environment and air quality problems found in the field measurements, this study assessed the air distribution by adopting three different air supply schemes for the catering area. Optimization results showed that compared with the ceiling supply, the side supply scheme kept the air temperature 0.4 °C cooler in summer and 0.5 °C warmer in winter. The temperature uniformity increased by 5.4% and 3.7%, and the velocity uniformity increased by 6.5% and 8.8%, respectively. This study can provide theoretical support for thermal environment construction and ventilation organization control of underground commercial buildings. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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19 pages, 6099 KiB  
Article
Pollution Dispersion and Predicting Infection Risks in Mobile Public Toilets Based on Measurement and Simulation Data of Indoor Environment
by Ruixin Li, Gaoyi Liu, Yuanli Xia, Olga L. Bantserova, Weilin Li and Jiayin Zhu
Processes 2022, 10(11), 2466; https://doi.org/10.3390/pr10112466 - 21 Nov 2022
Cited by 4 | Viewed by 2454
Abstract
Since the 21st century, in several public health emergencies that have occurred across the world, the humid enclosed environment of the toilet has become one of the places where bacteria, viruses, and microorganisms breed and spread. Mobile public toilets, as a supplement of [...] Read more.
Since the 21st century, in several public health emergencies that have occurred across the world, the humid enclosed environment of the toilet has become one of the places where bacteria, viruses, and microorganisms breed and spread. Mobile public toilets, as a supplement of urban fixed public toilets, are also widely used in densely populated areas. According to statistics, since the outbreak of COVID-19 in 2019, multiple incidents of people being infected by the COVID-19 virus due to aerosol proliferation in public toilets have been confirmed. It is an urgent issue to resolve the internal environmental pollution of mobile public health and reduce the risk of virus transmission in public spaces under the global epidemic prevention. This paper utilized a typical combined mobile public toilet as the research object and measured and evaluated the indoor thermal environment in real time over a short period of time. The diffusion mode and concentration change law of pollutants in mobile public toilets were predicted and analyzed based on CFD. Regression analysis was also used to clarify the relationship between indoor thermal environment variables and aerosol diffusion paths, and a ventilation optimization scheme was proposed to reduce the risk of virus transmission. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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17 pages, 6315 KiB  
Article
Thermal Performance and Energy Conservation Effect of Grain Bin Walls Incorporating PCM in Different Ecological Areas of China
by Yan Wang, Changnv Zeng and Chaoxin Hu
Processes 2022, 10(11), 2360; https://doi.org/10.3390/pr10112360 - 11 Nov 2022
Cited by 3 | Viewed by 1272
Abstract
China, as one of the largest grain production countries, is faced with a storage loss of at least 20 billion kilograms each year. The energy consumption from grain bin buildings has been rising due to the preferred environmental demand for the long-term storage [...] Read more.
China, as one of the largest grain production countries, is faced with a storage loss of at least 20 billion kilograms each year. The energy consumption from grain bin buildings has been rising due to the preferred environmental demand for the long-term storage of grain in China. A prefabricated phase change material (PCM) plate was incorporated into the bin walls to reduce energy consumption. The physical model of PCM bin walls was numerically simulated to optimize the latent heat and phase change temperature of PCMs for ecological grain storage area. The thermal regulating performance of the prefabricated PCM plate on the grain bin wall was optimized. It was indicated that a higher value of latent heat of the PCM is more suitable for the hotter region for storing grain in bins in this paper. The energy saving did not increase in the same proportion as the increase in latent heat, suggesting a diminishing return. In this study, the optimal latent heat ranged from 180 to 250 kJ/kg. The values of phase change temperature were selected as 31 °C, 28 °C, and 28 °C for Guangzhou, Zhengzhou, and Harbin cities, respectively, corresponding to hot, warm, and cold climates. The percentages of energy saving were 12.5%, 14.8%, and 17.5% with the corresponding phase change temperatures, which showed an advantage of the PCM used in grain bin walls. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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15 pages, 7842 KiB  
Article
Real-Time Temperature and Humidity Measurements during the Short-Range Distribution of Perishable Food Products as a Tool for Supply-Chain Energy Improvements
by Martim L. Aguiar, Pedro D. Gaspar, Pedro D. Silva, Luísa C. Domingues and David M. Silva
Processes 2022, 10(11), 2286; https://doi.org/10.3390/pr10112286 - 4 Nov 2022
Cited by 6 | Viewed by 2740
Abstract
Food waste results in an increased need for production to compensate for losses. Increased production is directly related to an increase in the environmental impact of agriculture and in the energy needs associated with it. To reduce food waste, the supply chain should [...] Read more.
Food waste results in an increased need for production to compensate for losses. Increased production is directly related to an increase in the environmental impact of agriculture and in the energy needs associated with it. To reduce food waste, the supply chain should maintain ideal preservation conditions. In horticultural products, temperature, and relative humidity are two of the main parameters to be controlled. Monitoring these parameters can help decision-making in logistics and routes management, as well as to diagnose and timely prevent food losses. In the present work, eighteen wireless traceability devices with temperature and relative humidity sensors monitored crates with horticultural products along a short-range distribution route with five stops (4 h 30 m). Sensor data and a location tag were sent via GSM for real-time monitoring. The results showed fluctuations in temperature and relative humidity that reached up to 7.4 °C and 35.3%, respectively. These fluctuations happened mostly due to frequent door opening, operational procedures, and irregular refrigeration conditions. Furthermore, the results brought attention to a procedure that creates unnecessary temperature fluctuations and energy losses. This study highlights the importance of individual monitorization of goods, for quality control and optimization of energy efficiency along the supply chain. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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16 pages, 2673 KiB  
Article
Evaluating Indoor Carbon Dioxide Concentration and Ventilation Rate of Research Student Offices in Chinese Universities: A Case Study
by Guangtao Fan, Haoran Chang, Chenkai Sang, Yibo Chen, Baisong Ning and Changhai Liu
Processes 2022, 10(8), 1434; https://doi.org/10.3390/pr10081434 - 22 Jul 2022
Cited by 4 | Viewed by 2708
Abstract
This work provides a case study on the indoor environment and ventilation rate of naturally ventilated research student rooms in Chinese universities. In the measured room, air temperature, relative humidity and carbon dioxide (CO2) concentration were monitored during the heating period [...] Read more.
This work provides a case study on the indoor environment and ventilation rate of naturally ventilated research student rooms in Chinese universities. In the measured room, air temperature, relative humidity and carbon dioxide (CO2) concentration were monitored during the heating period for 4 weeks. The number of indoor occupants, occupied time of the room and window/door-opening cases were simultaneously recorded. Results showed the research student room was occupied for an average of 12.0 h each day. Due to a large indoor and outdoor temperature difference during the heating season, and occupants’ adaption to indoor environment, indoor occupants seldom open windows/doors for ventilation. Air exchange of the room only by air infiltration cannot meet the ventilation requirement. As a result, an average of 77.6% of measured CO2 data each day exceeded 1000 ppm during occupied time. In fact, according to CO2 data, it was observed that window/door opening could effectively decrease indoor CO2 concentration. Therefore, intermittent window/door opening or CO2-based demand-controlled ventilation facilities were suggested for improving indoor air quality of such rooms. Additionally, special attention should be paid to other possible outdoor pollution. Full article
(This article belongs to the Special Issue Application of Data-Driven Method for HVAC System)
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