ABSTRACT
Internet of things is progressing very rapidly and involving multiple domains of everyday life including environment, governance, healthcare system, transportation system, energy management system, etc. smart city is a platform for collecting and storing the information that is accessed through various sensor-based IoT devices and make their information available in required and authorized domains. This interoperability can be achieved by semantic web technology. In this paper, I have reviewed multiple papers related to IoT in Smart Cities and presented a comparison among the semantic parameters. Moreover, I've presented my future domain of research which is about delivering the COVID-19 patients report to the concerned domains by the healthcare system domain. © 2023 IEEE.
ABSTRACT
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.
ABSTRACT
Advanced metering infrastructure (AMI) is becoming increasingly popular as an efficient means of energy demand management. By collecting energy data through AMI, it is possible to provide users with information that can induce them to change their behavior. To ensure that AMI continues to expand and to encourage the use of energy data, it is important to increase consumer participation and analyze their preferred service attributes. This study utilized a choice experiment to analyze consumer preferences for and acceptance of smart energy services based on AMI data. The results of a mixed logit model estimation show that consumers prefer the electricity information service for individual households and the social safety-net service among convergence services. A scenario analysis confirms that monetary compensation to offset any additional charges is important to maintain the level of consumer acceptance. These empirical findings offer insights for policymakers and companies seeking to develop policies and similar services.
ABSTRACT
Before 2020, the way occupants utilized the built environment had been changing slowly towards scenarios in which occupants have more choice and flexibility in where and how they work. The global COVID-19 pandemic accelerated this phenomenon rapidly through lockdowns and hybrid work arrangements. Many occupants and employers are considering keeping some of these flexibility-based strategies due to their benefits and cost impacts. This paper explores how demand-driven control strategies in the built environment might support the transition to increased workplace flexibility by simulating various scenarios related to the operational technologies and policies of a real-world campus using a district-scale City Energy Analyst (CEA) model that is calibrated with measured energy demand data and occupancy profiles extracted from WiFi data. These scenarios demonstrate the energy impact of ramping building operations up and down more rapidly and effectively to the flex-based work strategies that may solidify. The scenarios show a 5–15% decrease in space cooling demand due to occupant absenteeism of 25–75% if centralized building system operation is in place, but as high as 17–63% if occupancy-driven building controls are implemented. The paper discusses technologies and strategies that are important in this paradigm shift of operations. © 2023 The Author(s)
ABSTRACT
Human activities have been limited by coronavirus disease 2019 (COVID-19), and the normal conditions of our lifestyles have changed, particularly in terms of electricity usage. The aim of this study was to investigate the impact of COVID-19 on the power sector in the Lao PDR in 2020, as well as the challenge of using solar energy to supply power to the network using an optimal approach. The returns on investment of network extension and the purchase of solar energy were also evaluated. Furthermore, load conditions caused by the country's lockdown policy were analyzed. We analyzed the optimal sizing and location of solar energy using a particle swarm optimization method based on the main objective functions, with the system's power loss decreasing and its reliability improved. The results demonstrated that the suddenly reduced load from industry and commercial business did not have a large impact on its operations;however, revenue was reduced. The optimal method for connecting solar energy to a network can reduce power loss and improve system reliability. In addition, we discovered that the location and capacity of solar generation can reduce the investment costs of extensions for new lines, with the surplus power being exported.
ABSTRACT
Smart cities need energy-efficient and low-emission transportation for people and goods. Most studies focus on sustainable urban-transportation systems for passengers. Freight transportation in cities has increased significantly during the COVID-19 pandemic, leading to greenhouse gases emissions and negative externalities, such as traffic congestion. The purpose of this paper is to identify through a systematic literature review which innovations (hardware and software) applied by logistics service providers (LSPs) in sustainable urban freight (SUF) are suitable to support the transition to energy-efficient smart cities. We propose to classify the existing innovations in last-mile delivery for SUF into categories: (1) urban freight consolidation and/or trans-shipment;(2) the Consumer as a Service Provider (CaaSP);(3) choice of transportation modes. We introduce the concept of CaaSP as an innovative solution in last-mile delivery (LMD), where customers take over some transport operations with the use of smart technologies, and thus reduce the energy demand. We consider the modes of transportation, such as: drones, autonomous delivery robots, autonomous vehicles, cargo bikes (including e-cargo bikes, e-tricycles), electric vehicles (mainly vans), and combined passenger-and-cargo transportation rapid-transit systems. From the analyzed dataset, we find that energy-efficiency in smart cities can be improved by the consolidation of parcels in micro-depots, parcel lockers, and mobile depots. We analyze smart technologies (the Internet of things, big data, artificial intelligence, and digital twins), which enable energy efficiency by reducing the energy demand (fuel) of SUF, due to better operational planning and infrastructure sharing by logistics service providers. We propose a new IEE matrix as an actionable tool for the classification of innovations applied by LSPs in SUF, according to the level of their interconnectivity and energy efficiency. Additionally, this paper contributes to the theory by exploring possible future research directions for SUF in energy-efficient smart cities. © 2023 by the authors.
ABSTRACT
Senegal has been investing in the development of its energy sector for decades. By using a novel multi-criteria decision analysis (MCDA) based on the principal component analysis (PCA) method, this paper develops an approach to determine the effectiveness of Senegal's policies in supporting low-carbon development. This was determined using six criteria (C1 to C6) and 17 policies selected from the review of Senegal's energy system. In order to determine the optimal weighting of the six criteria, a PCA is performed. In our approach, the best weighted factor is the normalized version of the best linear combination of the initial criteria with the maximum summarized information. Proper weighted factors are determined through the percentage of the information provided by the six criteria kept by the principal components. The percentage of information is statistically a fit of goodness of a principal component. The higher it is, the more statistically important the corresponding principal component is. Among the six principal components obtained, the first principal component (comp1) best summarizes the values of criteria C1 to C6 for each policy. It contains 81.15% of the information on energy policies presented by the six criteria and was used to rank the policies. Future research should take into account that when the number of criteria is high, the share of information explained by the first principal component could be lower (less than 50% of the total variance). In this case, the use of a single principal component would be detrimental to the analysis. For such cases, we recommend a higher dimensional visualization (using two or three components), or a new PCA should be performed on the principal components. This approach presented in our study can serve as an important benchmark for energy projects and policy evaluation.
ABSTRACT
Climate change, disturbance of the energy security resulting from increasing fuel prices due to conflicts, and disruptions to production and supply chains caused by COVID-19 have highlighted the need for the world to be prepared for future challenges. The environmental and climate change impacts of heavy use of fossil fuels for energy production have yielded numerous crucial challenges and will even cause increasingly more severe effects in the years to come. This is particularly important, as the utilization of fossil fuels is the largest contributor to the increasing emissions of greenhouse gases in the atmosphere, which is leading to climate change and other problems. As a result, there is an emerging need to transition towards low or zero-emission energy systems where renewables and nuclear energy can play a critical role in the new energy equation and help establish the source ecosystem for hydrogen. Hydrogen, being the most abundant, clean, and energy-intensive element in nature, is an attractive alternative to fossil fuels. Furthermore, when produced using renewable energy sources, it is easier to reduce and control upstream emissions to produce or store hydrogen than fossil fuels. This study presents a framework for developing hydrogen technologies, building the necessary infrastructure, and selecting appropriate energy sources to help transition to a more sustainable and resilient energy system. There are also life cycle assessment studies conducted for various energy production technologies, including hydrogen, and their results are comparatively evaluated to confirm renewables and nuclear energy options would be the most suitable sources for hydrogen production. The global warming potential values of electricity production using nuclear and renewable energy are found to be 0.027 and 0.043 kg CO 2 eq./kWh. Comparatively, the global warming potential for natural gas, oil and coal are found to be 0.2, 0.3 and 0.36 kg CO 2 eq./kWh, respectively. [ FROM AUTHOR] Copyright of Energy Conversion & Management is the property of Pergamon Press - An Imprint of Elsevier Science 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.)
ABSTRACT
Financing strategies and energy performance have been extensively studied previously, and researchers frequently overlook the co-movements of integration of financial inclusion and energy performance index in the E7 Context. To address this gap, current research estimates the co-movement between the financial inclusion index and sustainable energy performance index to reflect the consequences of the COVID-19 crisis. Our findings show that in E7 economies, China exceeds the other nations in terms of energy performance. With a steady score, Russia is second in the group. Indonesia and Turkey are respectively fourth and fifth, and their total results show excellent prospective performances for sustainability. Mexico and Brazil follow this ranking with bad results and the lowest scores reported in the study results. The study findings are helpful for policy formulation and assessment. The study presented recommendations about financial inclusion and energy management practices in COVID-19 and delivered insights about the energy performance index in E7 economies. © 2023 Elsevier Ltd
ABSTRACT
Building energy management, in terms of both adopted technologies and occupant consumption behaviour, is becoming an essential element of sustainability and climate change mitigation programs. The global COVID-19 pandemic and the consequential lockdowns and remote working had a notable impact on office building operations and provided a unique opportunity for building energy consumption studies. This paper investigates the COVID-19 effects on energy consumption in office buildings, particularly in the education sector. We studied different buildings at the University of Technology Sydney (UTS) campus before and during the pandemic period. The results demonstrate that the changes in energy consumption due to COVID-19 in different UTS faculties are not as strongly correlated with occupant activity. The comparison shows that buildings with administrative offices or classrooms are easier to switch to a remote-working mode than those housing laboratories and special equipment. During weekends, public holidays, or conditions requiring working from home, the per capita energy consumption increases significantly translating into lower energy efficiency. Our findings highlight the essential need for some changes in office building energy management systems. We provide recommendations for office and commercial buildings in general to deal with similar crises and to reduce energy overconsumption in normal situations. © 2023 by the authors.
ABSTRACT
The COVID-19 pandemic had a noticeable effect on household energy consumption. In addition, modern architecture has driven growth in Indonesia's property sector in recent years and is one of the biggest energy consumers. The COVID-19 pandemic along with modern lifestyles like using advanced residential appliances have contributed to increased energy consumption in Indonesia. Homeowners do notice an impact on their electricity usage from a large-scale social restriction policy (PSBB). Predicting appliance future utilization and optimizing space are key to the energy management of residential buildings. Data collected from 150 households in Sumatra and Java Island, Indonesia, were used to compare three different house designs. The purpose of this study is to determine whether household lifestyle influences residential energy consumption. According to the analysis, household electricity consumption increased by around 11% between 2020 and 2019. eQUEST simulation analysis reveals that roof design has a small impact on reducing energy consumption. In three urban centers in Indonesia: Batam, Semarang, and Jakarta, it did not show a significant reduction in electricity consumption. The largest contributor to energy consumption patterns is household habits. The use of miscellaneous equipment (laptop, handphone, water pump, washing machine) and the use of air conditioners have significant effects on energy choice behavior, emphasizing the importance of building planning. Changing electricity usage behavior and water-saving management can lead to achieving energy efficiency targets in residential buildings. © 2023 by authors, all rights reserved.
ABSTRACT
Energy insecurity-the inability to secure one's energy needs-impacts millions of Americans each year. A particularly severe instance of energy insecurity is when a utility disconnects a household from service, affecting its ability to refrigerate perishable food, purchase medicine, or maintain adequate temperatures. Governments can protect vulnerable populations from disconnections through policies, such as shutoff moratoria or seasonal protections that limit disconnections during extreme weather months. We take advantage of the temporary disconnection moratoria that states implemented during the COVID-19 pandemic to assess the efficacy of state protections on rates of disconnection, spending across other essential needs, and uptake of bill payment assistance. We find that protections reduce disconnections and the need for households to forgo other expenses. We further find that protections are most beneficial to people of color and households with young children. We conclude with a discussion of the policy implications for energy-insecure populations.
ABSTRACT
Building Applied Photovoltaics (BAPV) such as Roof-top Solar PV has gained significant attention in recent years for harnessing the untapped potential of renewable energy sources. However, rooftop PV poses hurdles of space restriction and shadowing in densely packed urban residential neighborhoods. This study aims to design and assess the feasibility of an integrated grid-connected Rooftop and Façade Building Integrated Photovoltaic (BIPV) for meeting the energy demand of residential buildings on an academic campus. Three distinctive groups of residential typologies have been investigated in this study, categorized based on built area and occupants' past energy usage. Additionally, the variation in the measured Energy Performance index of the three different residential groups is illustrated to pave the path for the development of a typology-based residential energy benchmarking and labelling system. The Solar PV system has been designed for the maximum household energy demand recorded in CoVID-affected years due to high residential electricity usage in this period. The study showcases that integration of façade BIPV for low-rise residential buildings increases the system energy production to up to 62.5 % based on the utilized surface area for active PV. Furthermore, the Net Zero Energy Building (ZEB) potential for each typology has been achieved by integration of the proposed Solar PV, evaluated as a function of the Energy Performance Index (EPI) and Energy Generation Index (EGI). The designed nominal PV power of the proposed grid-connected plant is 5.6 MW, producing 7182 MWh annually, meeting the maximum residential energy demand in the studied academic campus in CoVID affected year. © 2022 Elsevier B.V.
ABSTRACT
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.
ABSTRACT
This paper investigates the relationship between oil and airline stock returns under different time frequencies. First, we propose an Autoregressive moving average model with mixed frequency exogenous variable to analyse the different impacts of oil on airline stock returns on daily, weekly, and monthly basis. We consistently find a negative oil-airline stock return nexus on a daily basis, but a positive relationship on a weekly basis. While the former supports the economic-based channel, the latter is in line with the market inertia channel. Our findings help explain mixed results reported in the literature. Further, our time frequency connectedness analysis shows that the economic-based channel dominates the market inertia channel since the connectedness is more pronounced in the short-run compared to the medium- and long-run. Our block connectedness results highlight that business models of airline firms can play a significant role in affecting the connectedness, in which the low-cost airlines are more sensitive to the oil price changes. It is worth noting that there are distinguished drivers of the oil-airline stock return nexus in different time frequencies. The drivers also vary between the Global Financial Crisis and the COVID-19 pandemic. Our results are consistent under a battery of robustness checks and deliver important implications to investors, portfolio managers, and executives of airline firms. © 2022 Elsevier B.V.
ABSTRACT
The application of newly available technologies in the green maritime sector is difficult due to conflicting requirements and the inter-relation of different ecological, technological and economical parameters. The governments incentivize radical reductions in harmful emissions as an overall priority. If the politics do not change, the continuous implementation of stricter government regulations for reducing emissions will eventually result in the mandatory use of, what we currently consider, alternative fuels. Immediate application of radically different strategies would significantly increase the economic costs of maritime transport, thus jeopardizing its greatest benefit: the transport of massive quantities of freight at the lowest cost. Increased maritime transport costs would immediately disrupt the global economy, as seen recently during the COVID-19 pandemic. For this reason, the industry has shifted towards a gradual decrease in emissions through the implementation of "better" transitional solutions until alternative fuels eventually become low-cost fuels. Since this topic is very broad and interdisciplinary, our systematic overview gives insight into the state-of-the-art available technologies in green maritime transport with a focus on the following subjects: (i) alternative fuels;(ii) hybrid propulsion systems and hydrogen technologies;(iii) the benefits of digitalization in the maritime sector aimed at increasing vessel efficiency;(iv) hull drag reduction technologies;and (v) carbon capture technologies. This paper outlines the challenges, advantages and disadvantages of their implementation. The results of this analysis elucidate the current technologies' readiness levels and their expected development over the coming years.
ABSTRACT
Rapid urbanization in developing countries has come at great costs in terms of the increasing energy demand. As India is a developing nation, the rising per capita income, and increasing purchasing power of domestic alliances by households, are pushing the household energy demand to rise sharply. Thus, there is a need to move towards the implementation of Net-Zero buildings in the residential sector in India to curb the escalating trend of energy demand. Although Rooftop Solar Photovoltaic has gained attention as a sustainable energy alternative to conventional sources, the potential of façade solar PV for harnessing alternative energy sources remains unexplored. This study aims to design and assess the feasibility of a grid-connected façade solar PV to meet the energy demand of residential complexes in a residential academic campus in India. Three groups of residential complexes based on energy-related user behaviour and built area have been identified in the study. Further, the maximum energy demand recorded in CoVID-affected years has been considered for designing the PV system. The study demonstrates that Façade Solar PV can solely meet 77-82% of the maximum energy demand of each group, and meets the Net-Zero potential for the studied residential typologies. Furthermore, it has been found, that the current residential benchmarking and labeling by the Bureau of Energy Efficiency (BEE), are largely climate-based and do not correspond with housing typology and built area. Thus, this study proposes a novel energy benchmarking and labelling system, based on the studied housing typology and corresponding energy usage, expressed in terms of the Energy Performance Index (EPI). It is found that the proposed energy efficiency labels for different typologies vary from the existing BEE residential benchmarking labels in terms of the calculated EPI and corresponding star rating when considered for Warm and Humid climatic zone. © 2022 ACM.
ABSTRACT
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.
ABSTRACT
Nowadays, it is essential for modern grids to operate at optimal scheduling, this helps in reducing the energy costs, mitigating the pollutant emissions, and making better use of renewable energy resources (RESs) such as photovoltaic (PV) and wind turbine (WT). Therefore, this paper proposes an energy management scheme for microgrid (MG) using recent metaheuristic honey badger algorithm (HBA) to enhance its operation via identifying the optimal scheduling of the installed generation units. HBA has the ability to solve complex optimization problem and avoid stuck in local optima due to balance between the exploration and exploitation phases. The constructed MG composes PV, WT, microturbine (MT), fuel cell (FC), and battery storage system. Operation of PV and WT at their normal generations, operation of WT at its rated power, and operation of PV and WT at their maximum limits are three cases analyzed in this work. Two objective functions are considered which are mitigating the operating cost and minimizing the pollutant emission. The proposed HBA is evaluated via conducting comparison to some reported approaches like Fuzzy self-adaptive particle swarm optimizer (FSAPSO), sparrow search algorithm (SSA), and gravitational search and pattern search algorithm (GSA-PS). Moreover, other programmed approaches of aquila optimizer (AO), Tasmanian devil optimizer (TDO), artificial rabbits optimizer (ARO), coronavirus herd immunity optimizer (CHIO), manta-ray foraging optimizer (MRFO), and dynamic arithmetic optimization approach (DAOA) are implemented and compared to the proposed algorithm. The fetched results proved the robustness and preference of HBA in achieving the best operation of MG in all studied operating conditions.
ABSTRACT
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.