Building Energy Use Research Articles

PM2.5 can help adjust building's energy consumption

Long- or short-term exposure to air pollution would distort human's cognitive function which has aroused widespread concern in interdisciplinary fields. It furtherly seems rational to assume that air pollution may affect energy use in public buildings. However, the overlooks of the potential impacts of air pollution on energy use would result in substantially higher energy saving cost. By matching the real-time energy consumption of public buildings to indoor and outdoor PM2.5, we construct a panel containing 193,226 data items. Based on this, we conduct the first preliminary exploration to try to reveal the impact of PM2.5 on energy use at the building-hourly level. Results show that the increase of energy intensity caused by PM2.5 is subtle, it indeed exists significantly. When indoor PM2.5 is 1 μg/m3, the marginal effect is minimum. After indoor PM2.5 exceeding 1 μg/m3, the marginal effect began to increase and the maximum is 0.3224 when PM2.5 is 1114 μg/m3. However, given the sorting and contrast effect, the practical relationship between indoor PM2.5 and energy use is possible inverted-U shaped. Furtherly, we find long term exposure to outdoor PM2.5 would not make people adapt to air pollution and instead cumulative the impact on energy use. Besides, centralized office could be an economical and feasible measure to achieve energy saving goal. Finally, we propose that it is promising for achieving the synergy between air pollution control and energy consumption reduction.

AutoBPS: A tool for urban building energy modeling to support energy efficiency improvement at city-scale

China has promised to peak carbon emissions by 2030 and become carbon neutral before 2060. Achieving this target requires actions from all sectors, especially the building sector, which accounts for 33 % of the total energy consumption in China. Within this scenario, this paper introduces a new urban building energy modeling tool, Automated Building Performance Simulation (AutoBPS), to calculate urban building energy demands and to analyze energy retrofit and rooftop photovoltaic (PV) potential. AutoBPS uses a building-by-building approach to automatically generate multi-zone (one zone per floor) models based on the city building dataset, considering the shading effect by surrounding buildings. The tool simulates building energy use and PV generation via EnergyPlus. A downtown district of 3633 buildings in Changsha, China, was selected as a case study to demonstrate the features of the tool. Firstly, annual baseline energy uses of 1793 GWh were simulated by inputting Geographic Information System (GIS) data. Then, different energy conservation measures (covering envelope, lighting, cooling system upgrade, etc.) and roof PV generation systems were adopted to explore energy saving potential. The results showed that the window upgrade was the most energy-efficient individual measure for residential buildings, while the lighting upgrade was that one for commercial buildings. Altogether three measures could save 2.7 ∼ 30.7 % of annual site energy use intensity per building. The total energy demand could be reduced by 18.5 % by combining all measures and saved by 38.6 % when PV installation was added. AutoBPS can be easily applied to other cities, supporting urban energy efficiency plans for carbon reduction goal implementation.

Advanced solutions to improve heat recovery from wastewater in a double heat exchanger

Reducing energy consumption and CO2 footprint in existing buildings without requiring extensive construction work is one of the biggest challenges facing the globe today. Although heating contributes for the majority of energy use in buildings, residential hot water demand is also relatively high, particularly when daily usage is high and especially for certain applications. The use of technologies that recover energy from sources other than fossil fuels to heat water has grown crucial, and one such technology involves recovering thermal energy from wastewater. Typically, heat recovery from wastewater is made to collect any remaining energy from the hot drainage water, and this energy is then applied to heat pumps or to warm up incoming cold water. The paper presents numerical simulations using a SST k-ω turbulence model in order to compare a regular geometry of heat exchanger with a helicoidal one. The second one provides a more turbulent flow that allows an intensification of the outer flow, thus allowing the enhancement of the heat transfer from the inner heated flow to the outer flow.

Assessment of a Decision-Making Model for Monitoring the Success of a Project for Smart Buildings

Objective: To express the usage of intelligent concepts in the architectural building construction field that are primarily concerned with reducing building energy use. Improved energy-saving methods and the use of environmentally friendly design principles are essential in this field. This type of managerial decision-making is necessary for the success of these types of projects. Methods: monitoring the performance of intelligent buildings use the cost variance (CV) and schedule variation as standard metrics to track the progress of a project based on the save energy concept. Also, this research conducted a comparative study on Building Information Modelling (BIM) and (MCDM) decision-making limitations as presented in the article. Analysis: the conventional technique, on the other hand, is unable to offer data on variance from typical performance levels. The main point based on Delphi results of construction cost variables has been observed 19 effective factors. Finding and Novelty: The RII observed that the most effective aspects of an intelligent building are the number of floors in the building, the kind of structural design, and the size of the shadow cast on the surface of the building. The Multi-Criteria Decision Maker (MCDM) observed significant differences in planned value (PV) and actual value (AC) results. In addition, as a result of the current approach, it is possible to track project costs and timelines more precisely. Doi: 10.28991/CEJ-2023-09-01-010 Full Text: PDF

Effects of General and Task Lighting on Subjective Perception and Work Performance: Empirical Study in an Office

Lighting accounts for a large proportion of building energy use. Task lighting is effective in saving lighting energy consumption and found to improve productivity in factories, but its effects in offices remain unknown. This study aims to investigate the effects of general and task lighting on office occupants’ satisfaction, alertness, mood, and performance in simple and complex tests. A within-subject design involving 2 lighting condition (100% general lighting vs. 70% general + 30% task lighting) × 2 task type (paper-based vs. computer tasks) was adopted. The work-plane illuminance and the equivalent melanopic illuminance were controlled at the same level in two lighting conditions. The lighting power was reduced by 16.7% when introducing task lighting. 28 subjects participated in this empirical study. The results showed that different lighting conditions had no significant impact on alertness. Introducing task lighting would suppress positive mood, but improve work performance. The respond speed in simple tasks was significantly improved by 4.3%-8.5% and the correct rates in complex assessments increased by 6.2%. These findings highlight that the combination of general and task lighting reduces power consumption and benefits work performance. However, its suppression on the positive mood also needs to be considered in the lighting design.

A Case Study on Potential Saving of Energy Consumption at Hospital Putrajaya

Efficient electrical energy usage has been recognised as one of the significant factors to reduce the cost of electrical energy consumption. In this world, hospitals are public buildings that use the enormous energy of other buildings. Due to its 24 hours service, the use of hospital building energy is estimated to be among the highest compared to commercial and residential buildings. In this research, the main building of Putrajaya Hospital has been selected. The main building covered by the first floor until the fifth floor will be focused to conduct this research. This research aims to identify energy consumption, cost savings and the provision of solutions to achieve the cost savings target of Putrajaya Hospital. The characteristics and location of the building were recognised at the beginning of the research. Besides, this study was continued by identifying the lighting system presented at Putrajaya Hospital and the electricity tariff published by Tenaga Nasional Bhd. The calculation of energy consumption and cost for each floor of the main building, starting from the first floor to the fifth floor proposed the energy saving method. Four potential savings methods are proposed later in this research which include the switch to LED lighting saving potential, occupancy sensor, regular maintenance, and reduce light operation hour by using the alternate system. The result was found that energy consumption can be reduced up to 73.38% by switching the current lamp to LED lamp.

Scenario-based analysis of future life cycle energy trajectories in residential buildings-A case study of inner Melbourne

The residential building sector contributes significantly to energy use in Australia. However, future energy use in residential buildings is seldom evaluated from a life cycle perspective, and such analysis rarely provides details about potential energy savings by specific strategies. This study develops a scenario-based bottom-up approach to predict the future life cycle energy (LCE) trajectories in residential buildings to 2050 with different energy-saving strategies. The proposed approach is used to investigate the impacts of strategies on the future LCE of residential buildings in detail in four scenarios: high carbon (HC), business-as-usual (BAU), accelerated policy (AP), and net-zero emissions (NZE), for a case study of Inner Melbourne Cities. The results demonstrate the potential upward trajectory of operational energy (OE) in the HC scenario and a downward trend in the NZE scenario. The analysis also reveals how stringent energy-efficient strategies and increasing renewable energy supply could lead to future net-zero operational emissions in the NZE scenario by 2050. The most effective strategies for decarbonising the residential building sector include improving the building envelope efficiency, upgrading heating and hot water systems, and using renewable energy. Furthermore, embodied energy (EE) will contribute more to LCE after 2045 in AP and NZE scenarios with the decrease of OE. EE in the NZE scenario is higher than that in the other three scenarios, as energy-efficient dwellings usually use more insulation materials. Therefore, EE reduction is critical for achieving net-zero life cycle emissions in the residential building sector. Building stakeholders should synergistically promote demand-side, supply-side, and EE reduction strategies for achieving net-zero life cycle emissions. A detailed analysis of the future LCE development with different strategies shows the benefits of the proposed approach, which supports informed decision-making towards the 2050 net-zero emissions target.

Overheating and energy use in urban office buildings in a warming climate

AbstractBuildings are responsible for one‐third of the UK's greenhouse gas (GHG) emissions. The move to reduce emissions has resulted in recent stringent building regulations primarily aimed at reducing heating and associated energy use, often by improving the building fabric's airtightness. However, internal gains dominated, highly–insulated and airtight non‐domestic buildings will likely overheat in the projected warming climate, requiring energy‐intensive cooling, thus diminishing the effectiveness of heating efficiency focused regulations. This research investigated the effects of the warming climate on overheating and energy use and resulting emissions in representative urban office spaces in London in the present‐day and projected future climates using hourly dynamic thermal simulations. Findings suggest that airtight and highly–insulated office buildings in the temperate UK will overheat in the 2050s. Heating demand reduces by at least 36% in the 2050s but electricity consumption and summertime space conditioning will increase by at least 13% and 55% respectively when hybrid cooling is adopted to ameliorate overheating. Despite the increase, a mixed‐mode ventilation strategy is one of the ways of achieving overall energy efficiency while meeting benchmark overheating and emissions targets. Current heating‐focused legislation needs to be re‐evaluated to account for the effects of the warming climate and overheating risks.

Impact of urban form on building energy consumption and solar energy potential: A case study of residential blocks in Jianhu, China

Urban form can significantly affect building energy consumption and solar energy potential, which is essential to sustainable urban development. However, few studies have proposed a comprehensive framework to discuss this. In addition, how to bridge the gap between theory and practice, and how to combine quantitative research results with urban form design is also a matter of concern. Based on this background, this study proposes a multi-objective urban form design optimization framework based on the Grasshopper platform. Three optimization objectives were identified: minimum building energy consumption, maximum solar potential and maximum sunlight hours. Then, taking Jianhu in China as an example, the building types are extracted from the actual urban context to create blocks. The Ladybug Tools plugin is used for performance simulation, and multi-objective optimization is run in Wallacei X. Furthermore, based on the optimization process data, a correlation analysis of urban form factors with building energy consumption and solar energy potential is conducted. Finally, the research findings are integrated, and energy-efficient urban form design strategies are proposed. The research results show that a block form with excellent energy performance in Jianhu has the following characteristics: (i) The open space is often located in the center of the block. High-rise buildings are located on the west side. (ii) The block presents a layout consisting of a low south side and high north side. (iii) The orientation of the block is 15° south by westor due south. (iv) Avoid building types with large shape coefficient such as P-4, C-1, S-3 and C-2. In addition, building density (BD), open space ratio (OSR), shape coefficient (SC) and average perimeter-area ratio (PAR) have significant correlations with the total building energy use intensity of the block. For solar potential, floor area ratio (FAR), BD, the average number of floors (AF), OSR, SC, and PAR are highly correlated with rooftop PV energy generation, and sky view factor (SVF) is significantly correlated with rooftop PV energy generation.

Study on Thermal Storage Wall Heating System of Traditional Houses in Cold Climate Zone of China: A Case Study in Southern Shaanxi

Solar energy has the advantages of being green, renewable, and energy-efficient. The use of solar energy in buildings can result in significant energy savings, and a great deal of practical and theoretical research has been conducted on solar buildings around the world. Southern Shaanxi belongs to a climate zone with hot summers and cold winters (HSCW). The mean room temperature is 4 °C, and it is lower than 2 °C at night, which greatly exceeds the thermal comfort range that the human body can bear. Aiming at a range of challenges including backward heating methods and low heating efficiency in southern Shaanxi, a fully passive thermal storage wall heating system (TSWHS) is proposed for traditional houses in the area. The specific method is to set up a thermal storage wall (TSW) outside the outer walls on the east, west, and south sides of the residential buildings. The wall is provided with an air exchange port, and there is no glass in the outer area of the doors and windows, which does not affect the normal application. The principle is that after the TSW receives solar radiation, the temperature of the internal HDPE (high-density polyethylene) and the air inside the cavity rises, which raises the interior temperature via the heat transfer and the air exchange port inside the TSW. The hot air inside the thermal wall achieves the purpose of heating. Lastly, through a comparison with the original heating system (OHS), it is confirmed that the TSWHS has certain practicability. According to an experimental simulation, the system can increase the indoor temperature by an average of 5.1 °C in winter and save about 1726.43 kWh of energy, accounting for 27.24% of the energy saving.

Energy Balance Data-Based Optimization of Louver Installation Angles for Different Regions in Korea

A louver is a traditional environmental control device and passive architectural element based on an ecofriendly concept. Louvers are architectural elements that can be used to regulate natural lighting, thermal environment, and building energy use. To realize these integrated functionalities of louvers, they must be designed considering the climate and geographical characteristics of the target region. However, these aspects are typically not considered during building design in Korea, resulting in lovers being used as design elements with simple natural lighting control functions. Therefore, the objective of this study was to promote the integrated use of louvers by optimizing the louver angle according to the microclimate in Korea from the viewpoint of thermal energy use. We performed load and energy simulation planning and calculation and conducted optimization studies for the louver angle and range of motion for each region. The energy consumption in central and southern Korean regions was minimized when the angles of the fixed louvers were 45°–75° and 60°–90°, respectively. Kinetic louvers could enhance thermal energy management when installed at 30°–75° in spring, 135°–165° in summer, 75°–165° in autumn, and 45°–75° in winter. These findings can promote the realization of integrated functionalities of louvers from the perspective of indoor environment comfort based on the microclimates of the Korean regions.

A critical review for formulation and conceptualization of an ideal building envelope and novel sustainability framework for building applications

Energy use in the building is responsible for one-third of total carbon dioxide (CO 2 ) emissions globally. Nearly half of the energy loss occurs through the building envelope due to heat transfer to/for the surroundings. Therefore, there is a need to design an optimum building envelope to reduce energy use in buildings that depend on several parameters. This study aims to review different building parameters and provide a conceptual framework to optimize the building envelope. In total, 260 papers were reviewed, and the building envelope design consideration was categorized into: 1) Design Parameters (design and geometry), 2) environmental conditions (indoor and outdoor) and 3) performance criteria (energy, environment, economic, comfort). Energy use and CO 2 -emission in buildings increase with high thermal conductivity, low thermal mass, and low solar absorption of its envelope. Geometrically, building orientation impacts energy use more than the building shape factor. Changing set point temperature according to surrounding conditions has reduced energy use and CO 2 -emission by 30% and 56%, respectively. However, indoor air quality, velocity, and occupancy have meagerly affected building energy use. Energy and emission optimization criteria are directly related, but the emission-based optimized envelope is thicker than the energy one. Other criteria such as economy and comfort (thermal and visual) are inversely proportional to the energy-efficient building envelope. Based on the comprehensive review, this study proposed a conceptual framework to design a sustainable building envelope that includes life cycle assessment, occupant's satisfaction, and social benefits. Several future research recommendations were made, including 1) the use of switchable reflective materials to minimize heat transfer, 2) dynamic insulation material to control insulation value as needed, and 3) smart windows with tunable optical properties.

Energy performance enhancement in institutional and commercial buildings

The built environment has been identified as a major contributor to the energy consumption as well as the GHG emissions across the world. Enhancing the energy performance of the building sector is crucial in meeting the current climate action targets, as well as in improving the economic outcomes and welfare of building owners and occupants. With the current energy and foreign exchange reserve crises faced by Sri Lanka, it is clearly evident that reducing the energy use in buildings as well as the reliance on imported fossil fuels are important. When it comes to greenhouse gas emissions curbing and climate action initiatives, demand side management initiatives appear to be more promising for Sri Lanka compared to supply side interventions, as the latter have higher costs of mitigation [3]. The effectiveness of the energy efficiency enhancement strategies employed in buildings depends on the archetype of the building as well as locational parameters such as climate conditions [1].

Building Energy Models at Different Time Scales Based on Multi-Output Machine Learning

Machine learning techniques are widely applied in the field of building energy analysis to provide accurate energy models. The majority of previous studies, however, apply single-output machine learning algorithms to predict building energy use. Single-output models are unable to concurrently predict different time scales or various types of energy use. Therefore, this paper investigates the performance of multi-output energy models at three time scales (daily, monthly, and annual) using the Bayesian adaptive spline surface (BASS) and deep neural network (DNN) algorithms. The results indicate that the multi-output models based on the BASS approach combined with the principal component analysis can simultaneously predict accurate energy use at three time scales. The energy predictions also have the same or similar correlation structure as the energy data from the engineering-based EnergyPlus models. Moreover, the results from the multi-time scale BASS models have consistent accumulative features, which means energy use at a larger time scale equals the summation of energy use at a smaller time scale. The multi-output models at various time scales for building energy prediction developed in this research can be used in uncertainty analysis, sensitivity analysis, and calibration of building energy models.

A Survey of Environmental Sustainability Practices in Dialysis Facilities in Australia and New Zealand.

Climate change is the biggest global health threat of the twenty-first century. Health care itself is a significant contributor to greenhouse gas emissions, and dialysis programs contribute disproportionately. Nephrology societies have called for increased recognition and action to minimize the environmental effect of dialysis care, but little data exist regarding environmental sustainability practices within dialysis facilities worldwide. This survey reports a baseline of environmental sustainability practices of dialysis facilities in Australia and New Zealand. An online survey was used to collect data regarding key areas of environmental sustainability practices within dialysis facilities between November 2019 and December 2020. An invitation to complete the survey was sent to the heads of all dialysis facilities in Australia and New Zealand. Responses were received from 132 dialysis facilities, representing 33% (122 of 365) of dialysis services within Australia and New Zealand. Most responses were from public satellite facilities (53 of 132; 40%), in-center dialysis facilities (33 of 132; 25%), and co-located dialysis and home therapies facilities (28 of 132; 21%). Opportunities for improvement in environmental sustainability practices were identified in three domains. (1) Culture. A minority of facilities reported having an environmental sustainability strategy in place (44 of 132; 33%) or undertaking sustainability audits (27 of 132; 20%). Only 7% (nine of 132) reported the inclusion of environmental training in staff induction programs. (2) Building design, infrastructure, and energy use. Few facilities reported the use of renewable energy (18 of 132; 14%), reclaiming reverse osmosis reject water (16 of 126; 13%), or the use of motion-sensor light switches (58 of 131; 44%). (3) Operations. A minority of facilities reported waste management education (47 of 131; 36%), auditing waste generation (23 of 132; 17%), or that environmental sustainability was considered in procurement decisions (33 of 132; 25%). Environmental sustainability is not currently prioritized in clinical practice, building design and infrastructure, or management systems in Australian and New Zealand dialysis facilities responding to this survey.

Hourly air temperature projection in future urban area by coupling climate change and urban heat island effect

Global climate change and urban heat island (UHI) effect are changing the urban microclimate and ecosystem of building and outdoor environment. In this study, CMIP5 family, which was found to have the most consistent projection with the current worldwide observation till now, was chosen to evaluate climate change’s impact on urban climate. This research uses Principal Component Analysis and Gaussian Mixture Model based building type clustering method to obtain urban morphological data and input parameters of the UHI model, and the validated UHI model is then coupled to the projections from various global climate models (GCMs).It is found that future urban microclimate prediction after considering the UHI effect can significantly improve the prediction accuracy of air temperature when downscaling future weather data from various selected GCMs, indicating the UHI shall be considered in predicting future weather data in urban tissue. After using the best-fit climate change prediction model MRI-CGCM3 to couple with the UHI model, the projections of the heating degree days (HDD) and cooling degree days (CDD) of Shenzhen from 2020 to 2099 has shown that comparing with the typical meteorological year, the average HDD in Shenzhen will be reduced by 57.5% in 2020–2099 under the RCP8.5 scenario, and the CDD will increase by 25.1%, which will exert considerable impacts on building energy use in urban tissue.

Investigating the energy use in an Australian building: A case study of a west-facing apartment in Sydney

This study presents the simulation of retrofitting measures in a residential apartment located in Sydney based on energy consumption, building characteristics, and climatic conditions through energy audits. From the results, an upgrade to a casement aluminum framed double glazing window with a thermal conductance (U-Value) of 2.3 W/m2/oC, having an initial cost of $6,570, will save 41.2 % and 21 % of the energy used for heating and cooling equipment with a simple payback of 6.3 years and fuel cost savings of $1,046. In addition, 787kWh of electricity saved from white goods by investing $1,050 has a payback of 2.2 years and fuel cost savings of $472. Finally, the building will save 2.7 tons of GHG emissions, equivalent to three people reducing energy use by 20 % in Australia. The research is vital because retrofitting multi-residential buildings in Australia has not been fully explored, leaving 7.8 million existing buildings that are not energy efficient.

Development of the Indian Future Weather File Generator Based on Representative Concentration Pathways

India’s fossil-fuel-based energy dependency is up to 68%, with the commercial and residential sectors contributing to the rise of building energy demand, energy use, and greenhouse gas emissions. Several studies have shown that the increasing building energy demand is associated with increased space-cooling ownership and building footprint. The energy demand is predicted to grow further with the conditions of global warming and the phenomenon of urban heat islands. Building designers have been using state-of-the-art transient simulation tools to evaluate energy-efficient envelopes with present-day weather files that are generated with historical weather datasets for any specific location. Designing buildings with historical climatic conditions makes the buildings vulnerable to the predicted climate change impacts. In this paper, a weather file generator was developed to generate Indian future weather files using a geo-filtering-based spatial technique, as well as the temporal downscaling and machine learning (ML)-based bias correction approach proposed by Belcher et al. The future weather files of the three representative concentration pathways of 2.6, 4.5, and 8.5 could be generated for the years 2030, 2050, 2070, 2090, and 2100. Currently, the outputs of the second-generation Canadian Earth System Model are being used to create future weather files that will aid architects, urban designers, and planners in developing a built environment that is resilient to climate change. The novelty lies in using observed historical data from present-day weather files on the typical meteorological year for testing and training ML models. The typical meteorological weather files are composed of the concatenation of the monthly weather datasets from different years, which are referred to for testing and training ML models for bias correction.

Optimization of the utilization of phase change materials in planar structures to control and optimize energy flux

The optimal use of phase change materials (PCMs) in multilayer constructions in hot climates is taken into account in this study. PCMs could reduce energy use and improve indoor thermal comfort by being added to the building envelope. To achieve this, an optimization-based numerical model is created to predict the thermal behavior of a multilayer wall of the building in a hot environment. The finite element model is coupled with design exploration tools based on design of experiments methodology and the response surface technique to analyze the relationships between the influencing PCM parameters and the response variable, which is represented by the heat flow into the internal space. Optimization analysis is carried out to identify a set of PCM thermophysical and geometrical parameters which minimize the output variable. The set of input parameters that includes the PCM thickness and location as well as melting temperature and melting zone is implemented in the computational model for a simulation period of 10 days. The achieved results show a decrease in the maximum temperature at the internal wall compared to the original wall without PCM, with <20% of the heat entering the occupant area. The analysis demonstrates the potential utilization of PCMs as an approach to enhance the thermal characteristics of the building and decrease energy use in regions with high temperatures.

Assessment of Outdoor Design Conditions on the Energy Performance of Cooling Systems in Future Climate Scenarios—A Case Study over Three Cities of Texas, Unites States

The excessive use of energy in buildings due to increased populations and economic development leads to more greenhouse gas emissions, which affect climate change and global warming. Changes in prevailing outdoor weather conditions significantly affect the energy systems of buildings through increased cooling and decreased heating. In this paper, 30 years of data of dry and wet bulb temperatures (1990–2020) with a time interval of 3 h were considered in order to estimate the climatic outdoor design conditions in the cities of Dallas–Fort Worth, Houston, and San Antonio in the state of Texas. The results suggest that the dry bulb temperature (DBT) had significantly higher increases in Dallas–Fort Worth (2.37 °C) than the wet bulb temperature (WBT) in Houston (4.1 °C) during the study period. Furthermore, this study analyzed the effects of climate change on cooling degree hours (CDH) and heating degree hours (HDH) and the results suggest the most significant drop in HDH in Dallas–Fort Worth with a maximum CDH fluctuation as compared to other two cities. The effect of climate change on the performance of cooling systems is also investigated in this study via direct evaporative coolers (DECs) and direct-indirect evaporative coolers (IDEC), which do not perform well in the selected cities. In contrast, absorption system (Abs) and vapor compression (VC) systems show an increase in the number of additional loads. The second part of this study is related to the future projection using the ARIMA model, which suggests that DBT would rise significantly in Houston (from 37.18 °C to 37.56 °C) and Dallas–Fort Worth (39.1 °C to 39.57 °C) while diminishing in San Antonio (from 34.81 °C to 33.95 °C) from 2020 to 2030. In contrast, WBT will experience an upward trend in Houston (from 36.06 °C to 37.71 °C) and Dallas–Fort Worth (from 31.32 °C to 31.38 °C) and a downward trend in San Antonio (from 32.43 °C to 31.97 °C) during 2020–2030. Additionally, the future performance prediction of Abs and VC systems is also performed, which reveals that the amount of additional load required is significantly higher in 2030 compared to 2020 and is more prominent in Houston. Conversely, amount of additional load required for cooling systems in San Antonio shows a decreasing trend in 2030.