Variability of Thermal Comfort and Energy Consumption by Introducing Working from Home

Owing to the COVID-19 pandemic, many companies have introduced working from home to avoid the risk of infection. In this study, we conducted questionnaire surveys and analysed the building energy management system (BEMS) in an office building where the number of employees working from home increased after the onset of the pandemic. The influence of working from home on the indoor environment satisfaction and the variability in energy consumption at home and office was determined. The indoor environment satisfaction was significantly higher when working from home than when working at the office. In 2020, the total energy consumption at home and office decreased by 30% in April and increased by 22% in August compared to the previous year. To work from home while saving energy regardless of the season, it is necessary to reduce office energy consumption by decreasing the number of workers present at the office. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Efficiency and Sustainability: The Role of Digitization in Re-Inhabiting the Existing Building Stock

Cities are complex and constantly evolving systems where changing social needs have always reshaped the built environment. Considering recent evolutionary trends in housing emergencies, amplified by the COVID-19 pandemic, and environmental sustainability goals, a rethinking of the building heritage is fundamental. This article aims to promote the conversion of buildings designed initially for nonresidential uses as a process and project strategy based on energy efficiency and a holistic and integrated vision of the circular economy. The methodological approach is based on two main phases: definition of evaluative parameters for the potential reuse of a building, and integration of the evaluation system in a BIM and GIS environment. The result is a tool for rapid automatic pre-evaluation of the potential conversion of a building into a residential space. Applying the developed methodology allows for a practical approach to the significant issue of sustainable construction, with particular attention to energy improvement and the reduction of environmental impact related to the construction of new buildings. The originality of the contribution lies in the systematization of various digital technologies to provide fundamental support for managing and transforming the varied and widespread unused real estate assets in a state of abandonment and degradation. [ FROM AUTHOR] Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

OPTIMIZED HVAC AIR DISTRIBUTION FOR IMPROVED AIR QUALITY USING CFD ANALYSIS

The energy consumption of Heating Ventilation and Air Conditioning (HVAC) systems accounts for a large proportion of global energy usage so even a small percentage of energy savings in these systems will account for important absolute value savings. One such saving can be realized by better designs as well as optimizing existing air distribution system. The indoor air quality (IAQ) is also greatly impacted by the air distribution system. In this work, the task of optimizing both the placement and the design of diffusers is investigated so acceptable Air Changes per Hour (ACH) numbers are attained with less energy consumption and good thermal comfort. The ANSYS Fluent software was used to optimize the design and placement of a newly developed diffuser. The proposed air distribution system is design to produce conditions like what one would experience while standing outside in a small breeze while experiencing perfect weather (room temperature, uniform air temperature distribution, air speed less than 2 m/s) [1]). This work is an extension of a previous study where a new diffuser design was proposed, which takes advantage of the Coanda effect [2]. The numerical analysis includes realistic models of a 9 × 9 × 3 m (width × length × height) classroom, which is occupied by students and a teacher. To be more realistic, it includes furniture, a door and windows. The simulated Heating Ventilation and Air Conditioning (HVAC) system complies with ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) standards for acceptable air quality. This investigation proposes a template on how anyone can optimize the location and placement of the air diffusers while achieving both thermal comfort and good IAQ. While this work was inspired by the COVID-19 pandemic this is foreseen to be an important ongoing issue and could lead to future advances in HAVC system that improve IAQ and produce better thermal comfort with improved energy savings. Copyright © 2022 by ASME.

Evaluation of potential capabilities of energy savings and utilization of solar energy in mosques in Hail city, Kingdom of Saudi Arabia

Energy consumption is one of the most important variables that have an impact on the environment. One of the nations in the world with the highest per capita electrical energy usage is the Kingdom of Saudi Arabia. Many attempts are being made in Kingdom of Saudi Arabia to lower energy consumption and electricity consumption to achieve sustainability. In this work, the data on the energy consumption of two mosques in Hail City were analyzed, and the opportunities for energy conservation and the use of solar energy were studied to make mosques sustainable. Annual energy use intensity was determined to be 100 and 121 kWh/m2 for the Al-Khashil and Al-Jamil mosques, respectively. While Al-Khashil's mosque envelope is insulated, energy efficiency measures implemented to the walls of Al-Jamil's mosque resulted in reductions in energy consumption of 27%, 13%, and 6%, respectively. The most effective energy efficiency option is a heating, ventilation, and air conditioning system with a high energy efficiency ratio, which can reduce cooling demand by more than 30%. If the condition of Saudi Building Code 601 is met, then it has the potential to cut energy usage by 35.4% and 63.3% for Al-Khashil and Al-Jamil, respectively. Due to coronavirus disease 2019, Al-Khashil's electricity usage was reduced by 58,737 kWh, or 39.9%, in 2020 compared to 2019. When using data from RETScreen and ATLAS, there were inconsistencies of up to 28%, but for DesignBuilder, the findings were the closest to the billing data. The mosques Al-Khashil and Al-Jamil have a combined yearly photovoltaic energy output from the suggested systems of around 135.93 MWh and 33.98 MWh, respectively. For the mosques, Al-Khashil and Al-Jamil, the yearly yield factor and capacity factor were both 1887.9 kWh/kWp/year and 21.9%, respectively. The annual greenhouse gas emission reductions from photovoltaic systems for Al-Khashil and Al-Jamil were 102.9 tCO2 and 25.72 tCO2, respectively. Concerning economics, the following results were obtained: The levelized cost of energy of photovoltaic systems is 0.0901 SR/kWh (0.024 $/kWh);the net present value and internal rate of return for photovoltaic systems are not suitable as a result of the current prices and the system applied in the Kingdom of Saudi Arabia. If the electricity produced from photovoltaic systems is injected into the grid at a rate of 0.32 SR/kWh, which is comparable to the SEC tariff for the mosque or government sector, then the simple payback time is 5.14 years. © The Author(s) 2023.

Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season

Since the coronavirus disease 2019, the extended time indoors makes people more concerned about indoor air quality, while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating, ventilation, and air-conditioning systems. In this study, to represent the dynamics of indoor temperature and air quality, a coupled grey-box model is developed. The model is identified and validated using a data-driven approach and real-time measured data of a campus office. To manage building energy usage and indoor air quality, a model predictive control strategy is proposed and developed. The simulation study demonstrated 18.92% energy saving while maintaining good indoor air quality at the testing site. Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones. The results showed 20%–40% energy saving in general while maintaining a predetermined indoor air quality setpoint. Although the infection risk is increased due to the reduced ventilation rate, it is still less than the suggested threshold (2%) in general. © 2022, Tsinghua University Press.

Data-informed building energy management (DiBEM) towards ultra-low energy buildings

To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy-efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations. © 2022 Elsevier B.V.

Monitoring the Trend of Energy Consumption during the Pandemic

The COVID-19 pandemic had a tremendous impact on socioeconomics and directly impacted the electrical system. In Malaysia, Grid System Operators (GSOs) were found to lack detailed information to differentiate the total energy demand before and during a pandemic. Working from home during the pandemic has changed the way of life and daily energy management methods for the domestic sector. This paper aims to study the national energy demand during the pandemic and then look into domestic energy management. The study included 3 phases. Phase 1 involved the analysis of data from the GSO to identify differences in energy demand before and during the pandemic. Next, in phase 2, a survey will be conducted on the energy management of the domestic sector. Finally, phase 3 involves household energy-saving proposals through examples of structural improvements. During the 2020 Movement Control Order (MCO) in Malaysia, the average total decrease in energy demand compared to 2019 was 15.82%. This high percentage is due to the closure of several economic sectors, such as trade and industry. From the survey, 88 110 respondents reported that domestic electricity bills increased during the MCO. Statistical analysis using ANOVA indicated no significant link between age range and behavior, knowledge, and total bills paid by respondents. Furthermore, this study also suggested structural upgrades incorporating 5-star air conditioning that can save RM389.47 per year, which will take 4.78 years to repay. This study concluded with suggestions on changes that can be implemented to aid homeowners with energy savings. © 2022 IEEE.

Data-Informed Building Energy Management (DiBEM) towards Ultra-Low Energy Buildings

To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations.

A Novel Heuristic Algorithm for Energy Saving in SDN networks

In the last years, the world has faced a lot of significant challenges, like the COVID pandemic, or the Russo-Ukrainian War. Among others, both of them indicated that one has to focus on energy efficiency, because the energy prices have skyrocketed. Computer networks are part of our everyday life. Software-Defined Networks (SDNs) provide the ability to communicate with and control directly the network nodes and to ensure a more adaptable as well as better performing packet forwarding. These capabilities make possible to respond quickly and efficiently to network events. This article presents some possible solutions for optimizing SDN networks in terms of energy management. Beside doing a survey on four known methods the authors also present a novel heuristic solution called Modified Heuristic Algorithm for Energy Saving (MHAES). The new method is compared to another heuristic method and to the case of not applying any energy saving measures using simulations with three different topologies. The results show that both heuristic approaches provided significant energy savings and above a request number threshold MHAES clearly outperformed the previous heuristic method. © 2022 IEEE.

Energy Audit in an Urban Indian Residential Community-A Case Study

This paper presents an energy audit study conducted for an urban residential community in Mumbai. The consumers are categorized using a k-means clustering algorithm based on their electricity consumption. The energy-efficient appliance selection is undertaken by a benchmarking study based on the appliance energy labeling and star rating initiated by the Bureau of Energy Efficiency(BEE) in India. The study establishes the techno-economic feasibility of energy savings in Indian urban households with an average payback period of 3.3 years. The energy-saving opportunities are selected based on each cluster's capital cost and payback period. Sensitivity analysis of electricity tariff of a region on payback period is undertaken. The covid impact analysis on the residential energy consumption is conducted by comparing energy consumption before and after the covid. The benefits are replicable in most Indian households, especially the urban residential consumers with high consumption in regions with high electricity tariffs. © 2022 IEEE.

Exploration of the Emergency Renovation of Sports Venues Resilience Space Based on Green Building Technology Under the Normal Epidemic Situation

The sudden outbreak of COVID-19 has caused a surge in medical demand. It has inspired people to continuously explore how to transform public buildings such as gymnasiums in a fast, low-cost and green way during emergencies. The article studies the feasibility of applying gymnasium to sudden public events, discusses the design methods for the renovation of gymnasium space, water supply and drainage system, ventilation system and intelligent system in emergency situations. The focus is on preventing cross-contamination, preventing backflow contamination, pressure shaving, airflow organization, and system control. Through these design methods, the gymnasium has the characteristics of efficient, adaptable and inclusive epidemic prevention. The application prospect of green building technology in emergency reconstruction was explored, and a reference is put forward for the design and reconstruction of gymnasiums in the post-epidemic era with “combination of epidemic control” and improving the resilience space of gymnasiums. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Parametric analysis of energy savings achievable by windows configurations in different climates

The advent of the COVID-19 pandemic led to an economic crisis of the construction industry and to an increasing of energy consumption in the residential sector for all the world. These effects are added to those of climate change, requiring ever greater efficiency and sustain ability in buildings. The windows design and the windows replacement are critical aspects in the new and existing buildings, respectively. The proposed parametric analysis evaluates the effects of different window -system (thus glasses type and technology, frames and shields), conventional and innovative, on the total primary energy demand of an office, in different climatic locations. It is shown how the best configuration can be influenced by the window frame, the window orientation and the installation of internal or external shields. Considering also a smart-glass technology, the findings of this paper show that the approach adopted in a typical Mediterranean climate - where it is not enough to minimize only the energy need for heating or for cooling - is also valid in dominant heating or cooling climates. This study shows that an accurate design of windows can lead to significant savings in total primary energy. In particular, with reference to an office case study, the effect of solutions based on the solar gain control (low-e, selective glazing) was better than solutions based on the heat loss control (triple glazing), even in heating dominated climates. In Vienna and Split these configurations show the maximum total primary energy reduction, that is equal to $\approx - 38\%$ and $\approx -41\%$. compared to the base case $(\Delta \mathrm{E}_{\mathrm{P}})$, respectively. © 2022 University of Split, FESB.

Research and Development on Power Supply Systems for a Sustainable Society

Carbon neutrality is a necessary goal as a countermeasure against climate change. Therefore, it has become more important to promote further energy saving and the use of energy storage systems in railway systems. Notwithstanding, falls in passenger traffic due to COVID-19 have had a significant impact on railway management, and reducing infrastructure maintenance costs has become an urgent issue. This paper presents recent research and development on power supply systems, especially for decarbonizing the railways and reducing resources required for maintenance of overhead contact line systems. © 2022 Ken-yusha Inc.. All rights reserved.

Didactic Model for the optimization of ventilation in rooms with the presence of CO2

This project arises from the need to contribute to the improvement of ventilation in buildings with multiple rooms. The COVID-19 pandemic forces us to look for alternatives to natural ventilation for energy savings as well as creating more comfortable work spaces without sacrificing the health of users. The mock-up presents a model of extraction ventilation. Optimizes the flow depending on the quality of the air. This work carried out at the IES Escolas Proval is part of an Innovation Project awarded in the current 2020-21 academic year with the participation of the IES Val Miñor and the company Hermes Smart Control. © 2022 IEEE.

Operation energy saving of central air conditioning based on auto-counting of people number

In the background of low carbon emission reduction, today's society has put forward higher requirements for improving the energy use efficiency of buildings and reducing building energy consumption, and reducing the energy consumption of central air conditioning systems in public buildings is also very important. Due to the persistence of the COVID-19 in recent years, the equipment with functions of temperature detection and reporting has become an essential way to prevent COVID-19 transmitting in public places. In this paper, a body temperature detection and data collection system is designed and further optimized, the number of people collected by this system is used as a basis to regulate the cooling load of central air conditioning to achieve energy saving. © 2021 IEEE.

Smart Home: Household Appliance usage Recommender and Monitoring System (HARMS)

The demand for energy sources such as electricity is increasing as the population is increasing, which results in high billing costs and more energy consumption. More factors are resulting from these issues. For example, the decreased awareness from residents about how to save energy, especially kids and elderly people who forget about turning off home appliances and lights when they are not needed to be on. HARMS provide a smart solution through the concept of machine learning (ML) and recommendations, it will monitor power consumption, show recommendations and control home appliances based on the resident's behaviors, when they are willing to turn on the room light or any other home appliance and when to turn them off in order to enhance energy saving. HARMS will also track the inhabitant's usual and unusual behavior to take an action. We must note that due to this exceptional situation (Covid-19 Pandemic), HARMS may be done either using actual hardware, simulation, or both. The hardware parts will consist of microcomputer, motion, light, and current transformer sensors. The software parts will consist of a control system that collects data from sensors and monitors the power consumption, a database to store the collected data, appropriate algorithms for the recommender system, and an android application to interact with the residents. Regarding the simulation will consist of a web-based application to represent the home environment and the appliances, including the control and the recommender systems. This project will experiment at the College of Computer Sciences and Information Technology (CCSIT) at King Faisal University (KFU). © 2022 IEEE.

Can PCS help us save energy? Initial assessment using dynamic energy and CFD analyses

This study is the first step towards a broader research intent: developing and optimising a Personal Comfort System for tertiary sector working environments. The entire industrial sector, and in particular offices, have seen changes in working habits, with a large increase in smart working to prevent COVID infection. The chance to partialise the HVAC system and maintains the rooms in an under-conditioned state is the obligatory way towards reducing energy waste, providing each workstation with an independent system that guarantees the operator's comfort conditions. The first step of the analysis was conducted simulating a general scenario and adopting conservative assumptions in order to predict the potential energy savings and the required PCS power. BES and CFD were coupled, using the outputs of the dynamic energy simulations in its most energy demanding timestep as input for the fluid dynamics analysis. The results showed energy savings between 15 and 20%, which is likely an underestimation of the potential savings due to very conservative assumptions and looking at the data from the few field analyses available in literature. Moreover, the operators' localised thermal comfort conditions improved, moving from a slightly cold to a neutral situation. Despite the conservative hypothesis, the results are promising, showing several opportunities for further analysis and improvement, as well as possible ways for its optimisation. © 2021 IEEE

Energy Efficiency in the Post-COVID-19 Era: Exploring the Determinants of Energy-Saving Intentions and Behaviors

The COVID-19 pandemic has a long-lasting influence on global economies. Households are expected to consume more electricity for their usual routine activities due to mandatory stay-at-home restrictions, resulting in greater energy utilization. The proposed study seeks to investigate the most relevant energy consumption factors amid the COVID-19 pandemic. The study employs a structural equation modeling approach to evaluate the responses from 511 Pakistani residents. Empirical results report a positive and significant association among perceived behavioral control (PBC), perceived environmental concern (PEC), perceived monitory benefits (PMB), and intention to save energy (ISE). Positive anticipated emotions (PAE) is found to be a significant predictor of ISE and energy-saving behavior (ESB). As a step further, we extend the analysis to find the moderating effect of perceived COVID-19 disruptiveness (PCD) between the relationship of ISE and ESB. Results reveal that PCD positively moderates this relationship. Based on research findings, policy implications and future research directions are provided for practitioners, researchers, and academicians to fulfill the country’s energy needs on its way to a future of sustainable development. Copyright © 2022 Ahmad, Irfan, Salem and Asif.

Evaluating Energy Saving Potential and IAQ Improvement of an Environmental-Controlled Fan System for Residence during the COVID-19 Era

This paper presents an evaluation of the potential energy-saving and indoor air quality (IAQ) improvement when using an environmental-controlled fan without causing any thermal discomfort to residents in a tropical country (Malaysia). In the past year, countries enforced complete/partial lockdown to control the spreading of Covid-19, consequently increasing the time spent at home from approximately 63 % to 90 %. The mobility restrictions have contributed tremendously to limiting the spread of the pandemic but resulted in the increase of energy consumption in residential buildings and the decrease in indoor air quality. These unacceptable indoor air quality conditions and high energy consumption resulting from over-dependence on air conditioners, the absence of natural ventilation, and the minimal usage of ceiling fans have inspired the idea of using an environmental-controlled fan. The research was conducted in a master bedroom over a period of two weeks, where a volunteer was assumed to be sitting in a quiet position practicing an exercise with limited movements such as reading or writing with only a ceiling fan turned on. The investigation demonstrated how the reliance on a ceiling fan could reach as high as 75% with an energy-saving of 31.4 % under acceptable indoor air conditions without causing any uncomfortable thermal sensation. © 2021 IEEE.

Optimal control of high-rise building mechanical ventilation system for achieving low risk of COVID-19 transmission and ventilative cooling.

As suggested by many guidelines, a high ventilation rate is required to dilute the indoor virus particles and reduce the airborne transmission risk, i.e., dilution ventilation (DV). However, high ventilation rates may result in high energy costs. Ventilative cooling (VC), which requires high ventilation rates like DV, is an option to reduce the cooling energy consumption. By combining DV and VC, this paper investigated the operation of the mechanical ventilation system in high-rise buildings during the COVID-19 pandemic, aiming to minimizing the cooling related energy consumption and reducing COVID-19 transmission. First, a modified Wells-Riley model was proposed to calculate DV rates. The ventilation rate required to achieve VC was also introduced. Then, a new ventilation control strategy was proposed for achieving DV and VC. Finally, a case study was conducted on a real high-rise building, where the required DV rate and the impact of the settings of the mechanical ventilation on the energy savings were evaluated. The results indicate that the required ventilation rates vary from 36 m3/s to 3306 m3/s depending on the protective measures. When the occupants follow the protective measures, the proper settings of the mechanical ventilation system can reduce energy consumption by around 40%.