Window-wall Ratio Research Articles

Analyzing Passive Design Retrofits using Pareto Front Optimization to Reduce Operational Carbon in Commercial Laboratory Spaces

Buildings are one of the leading sources of carbon emissions in the world. Most of the carbon emissions are released during the operation phase of the building. It is essential for buildings to provide thermal and visual comfort for the users. In the case of existing buildings, it is necessary to offer retrofit solutions so that the operational carbon emissions can be reduced without compromising on the other essential factors. In this study a Multi-Objective Optimization (MOO) of passive design strategies was conducted for a commercial laboratory in India situated in a moderate climate zone. The design variables considered for the study are wall and roof insulation, glazing material, window-wall ratio (WWR), depth of shading device and the number of shading devices used. The objective functions are: 1. reduced energy use intensity and operational carbon emissions, 2. increased thermal comfort hours and 3. increased daylight autonomy. Rhinoceros and grasshopper software along with Ladybug and Honeybee plug-ins were used for the study which resulted in 1296 iterations. MOO technique namely Pareto front optimization was used to optimize the objective functions. Out of 1296 solutions (excluding base case), 72 solutions were non-dominated. Two methods are described in the study to identify the recommendations for retrofit. The first method describes a Heuristic method of selection using Design Explorer recommending 5 good solutions. In the second method a factor is evolved to identify the 5 best solutions in sequential order. The overall study recommends the use of EPS insulation for the RCC roof, WWR of 20% on all sides, 3 horizontal shading devices of depth 0.75 m for all window openings. When compared with the base case scenario, this solution minimizes the EUI by 3.7%, maximizes average TCH by 106.6% and maximizes average DA by 66.9%. The overall operational carbon emissions are reduced by 7095.6 kgCO2.

Integrated optimization of the building envelope and the HVAC system in office building retrofitting

Increasing the energy efficiency of existing buildings is the major strategy to reach carbon neutral targets, given that the building sector is a major emitter. In particular, one major part of building energy usage is the building heating, ventilation and air-cooling system, which are highly depending on the thermal performance of building envelope and increase the challenge of selecting optimal packages of energy efficiency measures. This paper thereby presents a method for optimizing the building envelope and heating, ventilation and air-cooling system. The simulation-based NSGA-III approach developed in this paper is based on coupling the dynamic simulation models created in EnergyPlus software with the non-dominated sorting genetic algorithm, as the engine that performs an optimization process. A large domain of energy efficiency packages combined with heating, ventilation and air-cooling systems and building envelope are investigated to minimize energy consumption, retrofit cost and thermal discomfort in indoor environments, which including ideal loads air system, four pipe fan coil system and variable refrigerant flow system, insulation materials and insulation thickness for external walls and roof, different types of external windows, and window-wall ratio. An office building in Chongqing was chosen as a case study to demonstrate the practical implementation of the proposed method. The results show that the four pipe fan coil system was superior in the diversity and performance of the Pareto front. Then, the optimal packages were generated by a synthetic method, which have 58.57 kWh/m2 of energy consumption, 30.76 CNY/m2 of retrofit cost and 40.67 % of the percentage of thermal discomfort hours. The results also indicate that the yearly energy savings rates are 17.30 %, 23.05 % and 21.10 % separately for ideal loads air system, four pipe fan coil system and variable refrigerant flow system after performing optimization. These results highlight the importance and necessity of performing an optimization procedure for existing buildings to select the optimal retrofit measures.

Windows: socio-environmental dimensions in Palestinian residential buildings

People spend a significant portion of their lives indoors. Nowadays, windows are the essential architectural element that allows users to have contact with the outside world. This contact has an important impact on our physiology, psychology, well-being, and indoor environment. Understanding the physical and behavioral (social) characteristics of this element in the Palestinian residential building is still insufficiently explored. A cross-sectional survey of 272 respondents was conducted to investigate the openings’ characteristics and user’s behavior to assess their influence on residents’ satisfaction and indoor performance. This assessment was based on the concept that residents’ satisfaction with their homes is a measure of buildings’ performance in meeting users’ needs, expectations, and aspirations. The findings show that the physical properties (i.e. Window wall ratio, Window floor ratio, position, orientation, etc.) of windows do not meet the minimum threshold of sustainable and energy-efficient values (i.e. Daylight, thermal comfort). In addition, the survey analysis determines the driving parameters and their corresponding variations influencing window operations in different periods of the day and season. The culture plays a central role in the Palestinians’ window operation behavior.

Demand response strategies for air-conditioning systems based on direct load control: Considering envelope structures

In recent years, the surge in rural air-conditioning (AC) electricity consumption has led to an overall increase in peak loads in both winter and summer, presenting a major challenge to the reliability and stability of low-voltage distribution networks. Demand response (DR) strategy not only relieves the peak load, but also reduces the energy consumption and achieves the purpose of energy saving and emission reduction. Among the many DR strategies, direct load control (DLC) stands out as an effective way to quickly reduce building AC loads. Meanwhile, the building envelope is also one of the important factors affecting the AC load. A typical rural house in the Xi’an area of Shaanxi Province was used as a case study. A ground source heat pump system was developed, installed and used as an experimental platform in order to aid the study. Therefore, in this study, the combination of external envelope and DLC strategies was investigated to establish a simulation model of energy consumption in rural building complexes. Two DLC load control strategies were implemented under different external envelope conditions for annual AC energy simulation. The results show that the thickness of the external insulation layer has the greatest impact on the AC load of the building compared to the window-wall ratio and orientation. With a thickness of 0 mm–75 mm insulation, the DCCM strategy can effectively reduce AC energy consumption by 16%–18%; With a thickness of 0 mm–75 mm insulation, the TSCM strategy can effectively reduce AC energy consumption by 5%–8%.

The synergistic effect of multiple design factors on building energy consumption of office blocks: A case study of Wuhan, China

Design factors such as block morphology, building form and building envelope performance are key parameters affecting building energy consumption of urban blocks. However, the synergistic effect of multi-design factors on building energy consumption has not been studied in detail. This paper aims to investigate the synergistic effect of multi-design factors on building energy consumption of office blocks in Wuhan, China. This study employs field survey, satellite map and open street map to extract the typical building forms and construct parametric models of office blocks. Then, 81 representative scenarios considering the synergy of multiple design factors in office blocks are built. Then, based on the Rhino & Grasshopper parametric platform, a building energy assessment tool that considers the synergistic effect of multiple design factors is developed to simulate and record the building energy consumption of each scenarios. Finally, the synergistic effect of multi-design parameters on building energy consumption of office blocks is quantified using correlation and multiple linear regression methods. The findings reveal that the synergistic effect of multi-design factors on building energy consumption is 18.53 %. Building energy consumption for high-rise pavilion typology is saved by 9.64 % than multi-storey courtyard. The key design parameter combinations affecting building energy consumption in office block are building shape factor, solar heat gain coefficient, wall K-value, building width and window-wall ratio of west and east. This study contributes to a deeper understanding of the synergistic effects of multiple design factors on building energy consumption in office blocks and presents a scalable model that can be applied globally to promote sustainable urban development.

Passive energy-saving design strategy and realization on high window-wall ratio buildings in subtropical regions

Indoor overheating in high window-wall ratio (WWR) buildings has drawn widespread attention, but there is limited research on it during winter. Similarly, the application of radiative cooling (RC) technology on high-WWR facades and the effectiveness of combining RC with phase change materials (PCMs) need exploration. In Guangzhou, typical rooms in commercial buildings were studied, revealing that high-WWR buildings experience greater indoor overheating in winter compared to summer. For a 100 % WWR, the total equivalent energy consumption (EEC) is 71.389 kWh·m−2 in winters, 7.8 % higher than summer. Using RC glass with high solar (diffuse) reflectivity (0.65) on south-facing windows reduced EEC by over 70 %. RC glass also provided significant cooling capacity during unoccupied periods, which is sufficient to meet daytime cooling needs. In the case of a 100 % WWR, the proportion of available cooling capacity (37.5 %) during unoccupied period exceeded daytime cooling EEC (24.9 %). Therefore, PCMs were adopted to store this cooling capacity and transfer it for release during the occupied period, which bring an additional improvement in energy-saving performance by 4.7 %. The combination of PCMs and RC technology further achieves building energy efficiency. This study offers insights for addressing winter indoor overheating in high-WWR buildings.

Performance gap analysis for Korean building energy efficiency certification

Performance gap between predicted and measured building energy use can be caused by simplifications and assumptions introduced in the building energy modeling process, uncertainties in building operation such as heating and cooling setpoint temperature, operational hours, occupant behavior, heat generated from lights and equipment, etc. In South Korea, the building energy efficiency certification system (BEEC) evaluates annual energy use intensity (EUI, kWh/m2/yr) and assigns ten certificate levels using ECO2, a EUI calculation tool developed by the Korean government that is based on ISO 52016 and DIN V 18599. Firstly, we collected information on 158 non-residential BEEC-certified buildings and their actual energy usage data. Subsequently, we analyzed the performance gap between predicted and measured EUI for 158 non-residential buildings in terms of building types, heating and cooling degree days, chiller types, gross floor area, window-wall ratio, and envelope U-value. The study reveals that the performance gap is significant, showing mean absolute error ranging from 21.3 to 417.4 kWh/m2/yr, mean biased error from −3.2 to 73.4 %, and the coefficient of variance of the root mean squared error from 57.0 to 304.9 %, respectively. It is also noteworthy that even individual building’s annual consumption during eight years (2014–2021) is annually fluctuating, indicating that even the performance gap is a moving target. This study reassures that building energy certification in the design stage should be understood as a rating, not for a prediction because of many unpredictable and stochastic behavior of building energy systems and occupants.

Pengaruh Pencahayaan terhadap Kinerja Karyawan di Kantor Swarna Hutama Loka Asia, Bali

Title: The Lighting Effect on Employee Performance in the Swarna Hutama Loka Asia, Bali Office Lighting is one of the essential aspects to support daily human activities. The result of the reflection of light onto an object allows us to see clearly and comfortably so that the work can be done correctly. A good workspace should fulfill the comfortability aspects of its users. One of them is visual comfort, which affects worker performance and productivity. Optimal employee performance and productivity can be achieved if the comfort points in the workspace comply with standards, i.e., the lighting design provisions for the workspace layout and the required light intensity. The research method used in this study is a comparative method with a combined methods approach, namely by comparing the results of qualitative (respondents' questionnaire) and quantitative (measurement of light intensity and Window Wall Ratio) methods according to SNI 03-6575-2001 standards: Procedures for designing artificial lighting systems in buildings. This method is used to analyze the lighting and visual comfort of the room and its relation to the productivity of Swarna Hutama Loka (SHL) Asia’s office users. Generally, if employees feel comfortable with the workplace's lighting intensity, their performance and productivity will also increase. However, it does not always work in some conditions due to factors other than lighting, such as furniture arrangement and environmental adaptation, which are not included in this research.

Analysis of the influence of outer envelope structure on indoor thermal environment of zero energy building

Zero-energy building is the main development trend in the current construction field. Reducing the carbon emission of the building, enhancing the indoor comfort of the building, and improving the comprehensive performance of the building are the current research hotspots in the field of construction, and it is necessary to explore the impact of the envelope on the performance of the building as the main medium for the transfer of indoor and outdoor heat in the building. In this paper, zero energy consumption buildings in Northwest China are taken as the study application. Numerical simulation and experimental research are combined to compare and analyze the changes of indoor thermal environment under the conditions of external wall insulation layer thickness of 150mm, 140mm, 130mm and window-wall ratio of 0.36 and 0.5 in the heating season. The results show that the indoor comfort level of 130mm is lower than that of 140mm and 150mm external wall insulation layer thickness, and in winter, the increase of window wall ratio improves indoor thermal comfort. In general, increasing the thickness of external wall insulation layer and window wall ratio can be effective means to improve indoor comfort. However, blindly increasing the thickness of insulation layer and window wall ratio will only cause resource waste and cost increase, affecting the long-term development of zero-energy buildings.

BIM-Based Building Performance Simulation Analysis: A Multi-Parameter-Driven Approach to Building Energy Efficiency and Carbon Reduction

Global warming and other environmental problems are increasing the demand for high-performance buildings. The development of high-performance computers and building information models has a significant impact on buildings’ energy simulation. High-performance building design needs to comprehensively consider geography, climate, material, cost and other factors which is a highly complex multidisciplinary research problem. Therefore, it is urgent to use advanced modeling and simulation technology to realize it, involving Building Information Modelling (BIM), parametric design and cloud platform. Comprehensive simulation of building performance refers to a multidisciplinary collaborative design, and the correlation between research objects and parameters should be achieved by complex programming design. This study integrates BIM, computer, cloud computing and other technologies to simulate BIM-based building energy consumption performance. Based on project information, geometry information and physical properties exhibited by materials stored in BIM model, the energy analysis model is created. Revit–Dynamo API functions are employed to generate a novel BIM model in Revit after automatically changing and transferring user-defined parameters. BIM energy consumption model is converted into Green Building eXtended Markup Language (GBXML) file and uploaded to Green Building Studio (GBS) cloud server. The optimal project solution is yielded by retrieving the energy consumption simulation results of BIM models with a range of parameters. The case study shows that building volume, glass material, window-wall ratio and window height have significant influence on energy consumption targets of buildings. In hot-summer and cold-winter areas, the total energy consumption of glass materials with high insulation and reflection coefficient is small. The window size slightly impacts the annual lighting energy consumption, but it has significant influence on the annual air conditioning energy consumption, with a maximum increase of about 22%. Finally, the application advantages and limitations of the framework in high-performance building design and its application prospects in energy-saving building design are discussed.

The impact of a kinetic façade on the lighting performance and energy efficiency of a public building: the case of Dubai frame

ABSTRACT This paper proposes a novel framework for selecting a kinetic system strategy to enhance the performance of the building while preserving its architectural concepts. Dubai Frame, which is one of the most iconic buildings in Dubai, was chosen to act as a case study. A parametric model was developed for adjusting the opening ratios of the panel’s solid parts in the façade geometrics using the Grasshopper plugin in Rhino. Integrated Environmental Solutions (IES) simulation software was used and validated by calibration of the actual monthly electricity bills and real measurement of lux value against the predicted readings. The simulation assessed the total energy savings in terms of electricity and cooling loads and cost savings in terms of the KW per hour of electricity generated. In addition, it examined daylight illuminance levels for nine scenarios of the proposed kinetic system. The research has revealed several important results that include the finding that the optimal kinetic system results in 20% energy savings and 31% reduction in daylight illuminance levels while taking into account the current situation of the building and its aesthetic values. Abbreviations: UAE, United Arab Emirates; IEQ, Indoor Environmental Quality; PCM, Phase change materials; ASHRAE, The American Society of Heating, Refrigerating and Air-Conditioning Engineers; LEED, Leadership in Energy and Environmental Design system; HVAC, Heating, ventilation and air conditioning; RH, Relative Humidity; WWR, Window Wall Ratio; LR, Literature Review; RSMF, Room Surface maintenance factor; LMF, Luminaire maintenance factor; VAT, Value added tax; IHG, Internal Heat Gains

EVALUATION OF ENERGY-COST-EFFICIENT DESIGN ALTERNATIVES FOR RESIDENTIAL BUILDINGS IN KARNATAKA’S TROPICAL WET AND DRY CLIMATIC ZONES

Introduction: The existing building construction techniques in India account for increased operating energy consumption. Due to this, there is a need to apply sustainable construction methods by including passive design techniques. In accordance with the local climatic condition, a good passive design not only maintains a comfortable environment in the house, but also consumes less energy all the while performing the same basic functions as the traditional structures. Purpose of the study: The present research focuses on residential villas by analyzing parameters such as illuminance, energy, and cost consumption using Revit (Insight 360) software with two different cases. Methods: Considering Case1 as an existing villa of conventional design and Case2 presenting a proposed villa, a remodeling of the existing villa with an increased window wall ratio (WWR), different fenestration designs, and a new building plan. The authors followed the Indian Green Building Council (IGBC) guidelines relating to illuminance and generated an analytical energy model using Insight 360 to compare the energy consumption and cost efficiency of the cases. Results: The effectiveness of various fenestration types related to direct heat gain, window orientation that would provide more natural light, total operating energy consumption and costs of two different cases of villas are investigated in this paper.

An optimized energy efficient design of a light gauge steel building

This paper presents a case study of an energy efficient and cost optimized design of a light gauge steel building. The structural analyses conducted were linked to the concept of design for manufacture and assembly (DfMA) for the optimization of assembly time, quantity of labors and materials. A variety of analyses were performed on a prefabricated residential building constructed with cold formed and hot rolled steel materials for comparison which has a limited research previously. The energy optimization for the prefabricated building was carried out using Autodesk Insight 360. Several tools for structural, thermal, energy and cost analyses were adopted in this research. A Building Information Model (BIM) was developed in Revit and structural model in ETABS for structural analysis. Thermal performance was executed using Simulinks in MATLAB followed by energy simulations in DesignBuilder and EnergyPlus software packages. The material and energy costs of the designed building were estimated using CostX tool. From the analysis, the optimal window-wall ratio (WWR) was found to be 10%− 15% produced better energy and cost savings. Furthermore, the total energy consumption and greenhouse gas emissions of the building was found to be reduced by 28.7%− 31.5% with an application of insulation in its external walls in simulations. Improved bending capacity and shear force for CFS compared to RHS was observed. Finally, a framework was proposed for the automation and interoperability of building analysis tools.

Daylighting Assessment of a Heritage Place of Instruction and Office Building in Alice, South Africa

Mitigation of post-occupancy building energy consumption has resulted in the change of building design to utilise ambient weather factors for indoor thermal conditioning and lighting. This has increased the construction of new buildings with large glazing façades and reduced adaptive use of heritage buildings as they are considered not designed to meet modern energy use requirements. This paper evaluates the daylighting performance of a heritage place of instruction and office building. A quantitative research approach based on building information simulation tools was adopted. Autodesk Revit 2021 and Integrated Environmental Solutions Virtual Environment (IESVE) 2021 were used in modelling and simulating the building daylighting performances. The building’s annual daylight performance analysed with climate-based daylight modelling shows that points in the analysed spaces were within the UDI300-2000 for more than 50% of the occupied period (07h00 to 17h00) in a year. The sDA300,50% was found to be 100% in most spaces, which is considered a favourable daylit space according to the Illuminance Engineering Society of North America (IESNA). Further, discomfort glare analysis revealed that the building daylight glare is imperceptible, with an average daylight glare probability of 21.2%. The 1:14 window–wall ratio contributes to the building daylighting relative to orientation without constituting visual discomfort. Overall, climate-based daylight modelling revealed that the building’s annual daylight level meets the IESNA requirements with an imperceptible daylight glare.

Low-energy residential building optimisation for energy and comfort enhancement in semi-arid climate conditions

The application of energy-efficient strategies in buildings, such as the Green Building Concept, can significantly impact human comfort and resource consumption. However, due to the complexity of decision-making factors and the variety of available materials, computational models are necessary to identify the most effective solutions and optimise building energy performance. This study presents an integrated framework that uses machine learning algorithms and a Petri Net control system to optimise the thermal, comfort, and energy efficiency of both vertical and horizontal building envelopes in semi-arid climate zones. The framework incorporates several passive techniques for building energy parameters, including material thickness and melting point, window types, wall insulation thickness and thermal emissivity, wall solar absorbance, window wall ratio, fenestration position, air tightness, roof solar reflectance, roof insulation thickness and conductivity (W/(m·°C)), and floor insulation thickness. An experiment design was developed using Box-Behnken Design-Response Surface Methodology (BBD-RSM) for statistical optimisation, which was coupled with Design Builder simulation model. The methodology was demonstrated by applying it to a residential building in Mexico. Meta Additive Regression was used to analyse the output factors, which showed higher confidence compared to REP Tree and M5P Tree algorithms in green buildings. The results demonstrate that an annual energy reduction of 50 kW/m2 per household can be achieved by using an optimised building envelope.

Prediction of Cooling Load of Tropical Buildings with Machine Learning

Cooling load refers to the amount of energy to be removed from a space (or consumed) to bring that space to an acceptable temperature or to maintain the temperature of a space at an acceptable range. The study aimed to develop a series of models and determine the most accurate ones in the prediction of the cooling load of low-rise tropical buildings based on their basic architectural and structural characteristics. In this context, a series of machine learning (regression) algorithms were tested during the research to determine the most accurate/efficient prediction model. In this regard, a data set consisting of ten features indicating the basic characteristics of the building (floor area, aspect ratio, ceiling height, window material, external wall material, roof material, window wall ratio north faced, window wall ratio south faced, horizontal shading, orientation) were used to predict the cooling load of a low-rise tropical building. The dataset was generated utilizing a set of generative and algorithmic design tools. Following the dataset generation, a series of regression models were tested to find the most accurate model to predict the cooling load. The results of the tests with different algorithms revealed that the relationship between the predictor variables and cooling load could be efficiently modeled through Histogram Gradient Boosting and Stacking models.

Alternative window wall ratio of glasses with different solar heat gain coefficient and solar transmittance and their effect on total energy consumption in alternative directions

Energy simulation model of the building of Eskişehir Technical University Industrial Engineering Department Academic and Administrative Staff rooms were created in this study carried in the scope of energy efficiency and performance of buildings. In the aforementioned energy simulation mode, in line with the International Measurement, Verification and Energy Needs Standards and Protocol (IPMVP) “energy consumption verification”; heating energy, indoor-outdoor environment and climate data were defined, energy consumption verification was carried out and a realistic model was achieved. Using the realistic model achieved, alternative directions were applied to alternative window wall ratios thereby calculating “reference energy consumptions” in “reference building models”. Energy consumptions, calculated by applying alternative glass types to reference models, were then compared with reference energy consumptions

Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodology

This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. This paper aims to search for the optimum school building design under three simultaneous conflicting objective functions: (1) the minimization of overheating hours to less than 40 h as required by Building Bulletin BB101 building code by using passive mitigation measures, (2) the minimization of heating energy use to less than 15 kW/m2 according to passive house requirements and thus the reduction of greenhouse gas emissions, and (3) the minimization of artificial lighting energy use to less than the current lighting energy use by maximization of daylighting usage without exceeding acceptable glare index in classrooms. Ten building design variables are selected, which could generate approximately 300,000 solutions. The developed methodology reduced the numbers to 14,400 solutions and found seven Pareto solutions that comply with the three objectives and their constraints. High energy-efficient building envelope, appropriate window-wall ratio and window type, natural ventilation during the day, and night cooling can play a key role in achieving the objectives under current weather conditions. An additional cool roof and external overhang will be needed in the medium-term future climate, and an additional movable screen shading will be needed in the long-term future climate.

Study on Influencing Factors of Energy Consumption Building Characteristics of High-rise Hotel Standard Floor

In order to help architects Reduce energy consumption in buildings more pertinently in the early stage of design, this paper takes high-rise hotels in Guangdong as a research subject, obtains the building characteristic factor data of 28 groups of hotel samples through investigation, successively models and simulates the energy consumption value in Energy Plus software, and then studies the energy consumption characteristics and influencing factors of hotel buildings in Guangdong through the simulation results. Results show that the plane type has little effect on the energy consumption per unit area, and the standard floor area, the standard floor height and the four-way window wall ratio have a greater impact on the total energy consumption of the building. Except for the standard floor area, other building characteristics have a positive correlation with the total energy consumption per unit area.

Multivariate optimization towards energy balance with geometric constraints of building design and urban space intensity

Rapid urbanization has caused extensive energy shortage and excessive carbon emissions, thus creating a constant demand for advancing building energy performance. Such work often involves complex analysis of urban geometry and non-uniform irradiance conditions for dynamic shading. This paper presents a novel method for comprehensive evaluation and optimization of building design with integrated photovoltaics. Key parameters include building-height-to-street-width ratio (H/W), number-of-floors (Nf), aspect ratio (r), floor area (Af), window-wall ratio (WWR), and photovoltaics’ tilt angle on façades (β). The developed model has been validated experimentally. A baseline model was produced to further highlight the differences between EUI with and without surrounding buildings. Results showed that H/W and Nf were positively correlated with deviations with Af. Higher Af and Nfimproved energy efficiency especially for low-to-mid rises. Heating and cooling presented no correlation with Nf for r≥5, while both loads reached peaks at r=4. As H/W increased, heating proportionally increased by 2.1 kWh/m2 while cooling decreased by 1.8 kWh/m2. These rates dropped as H/W increased. Energy production from façades increased when r>2, with a slope of 10,000 kWh per unit, and a variance of 190,000 kWh. The effect of β showed higher significance in cooling, heating, and production, especially for low H/W.