Energy Performance Evaluation Research Articles

Finding Patterns of Construction Systems in Low-Income Housing for Thermal and Energy Performance Evaluation through Cluster Analysis

Energy consumption in buildings depends on many factors, including envelope materials. This paper aims to propose a method based on cluster analysis for finding reference models based on actual construction systems of low-income housing. Such reference models can be used in future thermal and energy performance studies. Data on the envelope composition of a sample of 106 dwellings were obtained through a field survey in Florianópolis, southern Brazil. Cluster analyses were performed to group similar materials and construction systems together, and therefore, a reference model was obtained for each cluster. Computer simulations and hypothesis tests were performed to verify whether the reference models represented the sample. Three reference models were obtained from the cluster analysis. Cluster 1 comprised houses with ceramic-brick walls, concrete floor, and concrete slabs. Cluster 2 comprised houses with ceramic-brick walls, concrete floor, ceramic tiles, and wooden ceilings. Cluster 3 comprised houses with wooden walls, wooden floor, cement tiles, and wooden ceilings. Cluster 1 performed better than the other clusters in the cold season (mean degree-hour was 1299 for cooling and 1361 for heating in the reference model). Cluster 2 performed better the other clusters over the hot season (mean degree-hour was 1014 for cooling and 1451 for heating). Cluster 3 showed the worst performance (mean degree-hour was 3793 for cooling and 2988 for heating). Thus, the hypothesis tests have shown that the three reference models differ from each other and can represent their clusters properly. Cluster analysis was a practical and objective method for obtaining reference models.

Design and multiple performance evaluation of green energy saving process for ethyl acetate/ethanol/water azeotrope separation by extractive distillation based on mixed solvent

The clean and efficient separation of ethyl acetate/ethanol/water azeotrope is of great significance for the production of high-purity ethyl acetate. In this study, a highly efficient separation of ethyl acetate/ethanol/water azeotrope by extractive distillation based on mixed solvent was developed. The relative volatility and quantum chemistry calculation were used to determine the alternative entrainer of mixed solvent. The multi-objective optimization based on genetic algorithm was carried out to obtain the optimal process scheme which considered both economy and environment. Three energy-saving process schemes were developed based on the conventional extractive distillation process, and the economic, environmental, energy and exergy properties of each process were investigated. The results show that the heat pump-assisted extractive distillation process may yield a significant reduction in gas emission and process energy consumption, showing an obvious advantage over the conventional extractive distillation process and the process proposed by previous researchers. The results of this study have important significance for the separation of high purity ethyl acetate and the recovery of wastewater containing ethyl acetate and ethanol. The research approach can be applied to further systems and serve as a reference for the creation of extractive distillation with mixed solvent.

Natural gas hydrate exploitation and recovered natural gas liquefaction driven by wind power: Process modelling and energy performance evaluation

Current oceanic hydrate research mainly focuses on its exploitation, but the subsequent storage and transportation of recovered gas is also necessary. To accelerate its commercial application and clarify the potential of liquefaction after hydrate exploitation, a rigorous simulation modelling was firstly conducted on the depressurization exploitation of hydrate coupled with recovered gas liquefaction in this paper. The energy performance was evaluated by energy consumption and efficiency analysis. The energy efficiency of the gas and liquid production process, liquefaction process, and the key influence factors of the whole process were studied separately. Results show that the energy efficiency ratio for depressurization exploitation reaches between 4.9 and 19.4, while that for the whole system of hydrate exploitation and liquefaction is only between 1.3 and 2.7 considering recovered gas combustion for power generation. The energy efficiency ratio of the whole system increases to between 2.6 and 4.3 powered by offshore wind farm. The largest energy efficiency reduction is up to 77.8% after recovered gas liquefaction compared with exploitation process. Therefore the storage process with lower energy consumption should be prioritized or the energy consumption should be optimized for the storage and transportation process after hydrate exploitation.

Investigation into energy performance of a multi-building complex in a hot and humid climate: efficacy of energy saving measures

PurposeCommercial buildings, which include office buildings, are one of the three major energy-consuming sectors, alongside industrial and transportation sectors. The vast increase in the number of buildings is a positive sign of the rapid development of Malaysia. However, most Malaysian government office buildings tend to consume energy inefficiently due to lack of energy optimization. Most of the previous studies focused on the performance of green buildings in fulfilling the green development guidelines. As such, it is essential to study the energy performance of existing government office buildings that were constructed before most energy-efficient standards were implemented to mitigate energy wastage due to the lack of energy optimization. This study aims to analyse the energy performance of existing non-green Malaysian government office buildings and the factors that influence building energy consumption, as well as to evaluate the efficacy of the existing energy conservation measures.Design/methodology/approachThis study was conducted by a literature review and case study. The chosen buildings are six government office building blocks located in Kuala Lumpur, the capital city of Malaysia. In this study, a literature review has been conducted on the common factors affecting energy consumption in office buildings. The energy consumption data of the buildings were collected to calculate the building energy intensity (BEI). The BEI was compared to the MS1525:2019 and GBI benchmarks to evaluate energy performance. SketchUp software was utilized to illustrate the solar radiation and sun path diagram of the case study buildings. Finally, recommendations were derived for retrofit strategies based on non-design factors and passive design factors.FindingsIn typical government office buildings, the air-conditioning system consumed the most energy at 65.5%, followed by lighting system at 22.6%, and the remaining 11.9% was contributed by office appliances. The energy performance of the case study buildings is considered as satisfactory as the BEI did not exceed the MS1525:2019 benchmark of 200 kWh/m2/year. The E Block recorded the highest BEI of 183.12 kWh/m2/year in 2020 due to its north-east orientation which is exposed to the most solar radiation. Besides, E Block consists of rooms that can accommodate large number of occupants. As such, non-design factors which include higher occupancy rate and higher cooling demand due to high outdoor temperature leads to higher energy consumption. By considering passive design features such as building orientation and building envelope thermal properties, energy consumption can be reduced significantly.Originality/valueThis study provided a comprehensive insight into the energy performance of Malaysian government office buildings, which were constructed before the energy-efficient standards being introduced. By calculating the BEI of six government office buildings, it is found that the energy performance of the case study buildings fulfils the MS1525 benchmark, and that all their BEIs are below 200 kWh/m2/year. Malaysia's hot and humid climate significantly affects a building's cooling load, and it is found the air-conditioning system is the major energy consumer of Malaysian government office buildings. This study discusses the efficacy of the energy-saving measures implemented in the case study buildings to optimize energy consumption. Recommendations were derived based on the non-design factors and passive design factors that affected the energy consumption of the case study building. It is envisioned that this study can provide practical strategies for retrofit interventions to reduce energy consumption in Malaysian office buildings as well as for office buildings that are in a similar climate.

Degradation and energy performance evaluation of mono-crystalline photovoltaic modules in Egypt

Degradation reduces the capability of solar photovoltaic (PV) production over time. Studies on PV module degradation are typically based on time-consuming and labor-intensive accelerated or field experiments. Understanding the modes and methodologies of degradation is critical to certifying PV module lifetimes of 25 years. Both technological and environmental conditions affect the PV module degradation rate. This paper investigates the degradation of 24 mono-crystalline silicon PV modules mounted on the rooftop of Egypt's electronics research institute (ERI) after 25 years of outdoor operation. Degradation rates were determined using the module's performance ratio, temperature losses, and energy yield. Visual inspection, I–V characteristic measurement, and degradation rate have all been calculated as part of the PV evaluation process. The results demonstrate that the modules' maximum power ({P}_{max}) has decreased in an average manner by 23.3% over time. The degradation rates of short-circuit current ({I}_{sc}) and maximum current ({I}_{m}) are 12.16% and 7.2%, respectively. The open-circuit voltage ({V}_{oc}), maximum voltage ({V}_{m}), and fill factor (FF) degradation rates are 2.28%, 12.16%, and 15.3%, respectively. The overall performance ratio obtained for the PV system is 85.9%. After a long time of operation in outdoor conditions, the single diode model's five parameters are used for parameter identification of each module to study the effect of aging on PV module performance.

Energy Efficiency and Performance Evaluation of an Exterior-Rotor Brushless DC Motor and Drive System across the Full Operating Range

In recent years, exterior-rotor brushless DC motors have become increasingly popular in robotics applications due to their compact shape and high torque density. However, these motors were originally used for continuous operation in drones. For applications such as exoskeletons, prostheses, or legged robots, short bursts of high power are often required. Unfortunately, vendors do not typically provide data on the motors’ performance under these conditions. This paper presents experimental data on the torque–speed relationship, efficiency, and thermal responses of one of the most widely used outrunner-type brushless motors across its full operating range, including high-power short-duration operation. The results of this study can inform the selection and design of actuators for a range of robotics applications, particularly those that require high power output for brief periods of time.

Evaluation of thermal and energy performance of cool envelopes on low-rise residential buildings in hot climates

Evaluation of thermal and energy performance of cool envelopes on low-rise residential buildings in hot climates

Digital radiography by counting photons: innovative solution for testing very thick parts

In 2019 we presented the first prototype of a photon counting detector (PCD) specially designed for the inspection of very thick parts requiring the use of high energy (HE) sources (E > 200keV). HE PCD differs from the standard model by the following characteristics: 1) Photoconductor CdTe active layer thickness optimized for HE, with about 30% increased detection efficiency; 2) Completely renewed ASIC allowing selection of energy threshold up to 1300keV. Modification 2) allows to reduce scattered radiation when using gamma sources such as Iridium 192 and Cobalt 60; or pulsed sources like linear accelerators and betatrons. The object-contrast results from this considerably improved. Image quality is comparable to, if not better than, film. We present energy threshold optimization study and performance evaluation results in terms of ISO 19232 IQI (wire and hole), signal-to-noise ratio, and spatial resolution (via duplex IQI) according to ISO 17636_2 (class B). Focus is given to HE PCD/film comparison, which was carried out by means of mock-ups containing artificial and/or real flaws; and, in 2020, for the first time in a nuclear power plant site, for the examination of primary circuit dissimilar welds. Photons energy thresholding successfully addressed also the presence of background radiation. The latter represented 2% of counted photons, while with film, background was responsible of 13% of optical density.

Time series prediction method based on sub-metering in building energy performance evaluation

Time series prediction method based on sub-metering in building energy performance evaluation

Accelerating the design and optimization of catalysts for the hydrogen evolution reaction in transition metal phosphides using machine learning

Transition metal phosphides (TMPs) are potential substitutes for platinum group metal catalysts in hydrogen evolution reactions (HER) for sustainable energy. In this work, a novel machine learning (ML)-based technique for HER performance prediction of TMPs is presented. ΔGH, which assesses catalytic activity, was utilized as the expected target value and data from sources like collected papers and self-calculated data were also employed. The random forest (RFR) technique produced an R2 of 0.89 on the test set, while non-tree ML algorithms were utilized for learning and feedback. Additionally, TMPs of ΔGH were predicted using an original Ensemble learning technique. The ensemble learning method significantly increased the model's predictive effect and strengthened the model's stability and resilience, resulting in an R2 >0.85 on the test set for the tree algorithm model. The SHAP (SHapley Additive exPlanations) algorithm and RFR showed that the geometric means of atomic volume, first ionization energy, and p-orbital electron number significantly impact free energy performance evaluation by tree ML algorithms. These findings can effectively guide the design and development of new products. In conclusion, this approach offers a useful tool to assess TMPs’ performance in HER studies.

Techno-economic and environmental evaluation on radiative sky cooling-based novel passive envelope strategies to achieve building sustainability and carbon neutrality

As the pursuit of carbon neutrality gains momentum, retrofitting high-performance buildings with novel, energy-efficient passive envelope systems has emerged as a promising pathway towards building sustainability. To this end, this study aims to propose, evaluate, and optimize such envelope systems considering varying climate patterns in China by incorporating state-of-the-art passive cooling strategies into buildings. Comprehensive techno-economic and environmental evaluations were conducted on a standard-compliant three-story typical commercial building, considering newly proposed passive approaches. The energy performance evaluation reveals that the super-cool white roof corresponds to annual cooling electricity savings of 2.5–6.1% for the entire building and 7.0–17.1% for the top floor in response to varying climate patterns. By contrast, the radiative cooling red and yellow walls exhibit cooling energy saving rates of 1.4–1.9% and 1.9–2.6%, respectively. The insulated grey clear double-glazing window can garner even greater cooling energy savings of 2.6–13.5%. It is highlighted that for the cities located in cold regions, the thermal improvement in windows offers a significantly greater opportunity for cost savings and carbon reduction compared to retrofitting roof and wall surfaces. To maximize net savings, the optimization scheme can achieve cost savings in hot-summer cities ranging from 859.1 to 1835.1 $/year, with an average of 1151.2 $/year, and from 784.4 to 1076.5 $/year, with an average of 658.8 $/year for cold cities. To minimize carbon emissions, the optimal design approach can reduce carbon emissions by 18,093.6–37,526.6 kg/year, with an average of 22,745.0 kg/year, in response to varying climate patterns. Overall, this study sheds light on the state-of-the-art passive envelope strategies that can achieve energy-efficient carbon-neutral buildings for a variety of climates in China. The optimization scheme proposed in this study provides a useful framework for designing passive envelope systems that are tailored to specific climate patterns.

Energy Performance Evaluation of Domestic Airport Departure Hall TIA, Kathmandu

This research focuses on the energy performance of the building envelope of an Airport Terminal Building in Kathmandu, Nepal. This study explores how to improve thermal comfort Energy analysis through a quantitative analysis of the effect of thermal characteristics of the building envelope. Development of base model Revit and duplicated in Autodesk Insight. This study is about the operational electricity consumption, Peak Heating/cooling load and Energy use intensity of the building at domestic departure hall at Tribhuvan International Airport, Building envelops systems pose a great scope to reduce the energy consumption and consequently improve building efficiency. This research is concern with reduction of operational electricity consumption on Heating and cooling system Most part of the energy consumption is occupied by HVAC system and this consumption needs to be optimized to reduce whole energy consumption of the buildings.

Energy, economic and environmental performance evaluation of co-gasification of coal and biomass negative-carbon emission system

This study evaluated the energy, economic, and environmental performance of co-gasification coal and biomass negative-carbon emission systems. All coal and all biomass systems were analyzed in detail for performance differences. The effects of the blending ratio and carbon capture rate (CCR) on the system were explored at the technical level. In addition, the impacts of carbon trading and fuel prices were considered at the market level. The results showed that the co-gasification system effectively improved the heat value of syngas and reduced the power generation cost. The efficiency and levelized cost of energy (LCOE) increase with the blending ratio. Compared with the 100 % biomass system, the power generation cost was reduced by 19 % at most. For the certain blending ratio, the energy and economic performance deteriorated as the CCR increased. A higher CCR corresponds to a higher cost of capturing unit CO2. The economic advantage decreased significantly with increasing CCR for the system with lower blending ratio. The LCOE was most sensitive to the carbon trading price at the market level. The LCOE was reduced by $ 1.93 as the carbon trading price increased by $ 1. This study demonstrates the potential and promotion value of negative-carbon emission power generation systems.

Hybrid Renewable Energy System Design: A Machine Learning Approach for Optimal Sizing with Net-Metering Costs

Hybrid renewable energy systems with photovoltaic and energy storage systems have gained popularity due to their cost-effectiveness, reduced dependence on fossil fuels and lower CO2 emissions. However, their techno-economic advantages are crucially dependent on the optimal sizing of the system. Most of the commercially available optimization programs adopt an algorithm that assumes repeated weather conditions, which is becoming more unrealistic considering the recent erratic behavior of weather patterns. To address this issue, a data-driven framework is proposed that combines machine learning and hybrid metaheuristics to predict weather patterns over the lifespan of a hybrid renewable energy system in optimizing its size. The framework uses machine learning tree ensemble methods such as the cat boost regressor, light gradient boosting machine and extreme gradient boosting to predict the hourly solar radiation and load demand. Nine different hybrid metaheuristics are used to optimize the hybrid renewable energy system using forecasted data over 15 years, and the optimal sizing results are compared with those obtained from 1-year data simulation. The proposed approach leads to a more realistic hybrid renewable energy system capacity that satisfies all system constraints while being more reliable and environmentally friendly. The proposed framework provides a robust approach to optimizing hybrid renewable energy system sizing and performance evaluation that accounts for changing weather conditions over the lifespan of the system.

Geographic Information Systems for Facilitating Audits of the Urban Built Environment

Data collection and large-scale urban audits are challenging and can be time consuming processes. Geographic information systems can extract and combine relevant data that can be used as input to calculation tools that provide results and quantify indicators with sufficient spatial analysis to facilitate the local decision-making process for building renovations and sustainability assessment. This work presents an open-access tool that offers an automated process that can be used to audit an urban area in order to extract relevant information about the characteristics of the built environment, analyze the building characteristics to evaluate energy performance, assess the potential for the installation of photovoltaics on available building rooftops, and quantify ground permeability. A case study is also presented to demonstrate data collection and processing for an urban city block, and the relevant results are elaborated upon. The method is easily replicable and is based on open data and non-commercial tools.

Toward a Fast but Reliable Energy Performance Evaluation Method for Existing Residential Building Stock

Building a reliable energy model for old residential buildings with insufficient documentation and user assistance is a challenging and time-consuming task. Nevertheless, the ambitious European decarbonization targets require this building stock to be renovated, making energy assessment a key priority. In line with this goal, the following study explores a more simplified and automatic framework to generate a residential building energy model (BEM). The paper’s approach is based on the concept of urban building energy modelling (UBEM) archetypes or building prototypes and is customized according to the principles of dynamic simulations performed in the existing BEM software, Integrated Environmental Solutions Virtual Environment IES VE, and Solemma Open Studio. Therefore, based on three real starting inputs, a prototype database (DB) of assigned inputs is generated, i.e., an input matrix, using Google Maps as a geometry source. Other data are drawn from tabular DB. The proposed approach is evaluated by benchmarking the simulation results with precise models and monitoring the data that come from the Horizon2020 project REZBUILD. Nevertheless, a level of simplification is introduced that creates less accurate results for total or system-level energy consumption; this is compensated for using a set of simple calibration steps. The approach gives promising results for daily indoor temperature, making it a suitable indicator for evaluating further retrofitting alternatives.

Thermal and energy performance evaluation of a full-scale test cabin equipped with PCM embedded radiant chilled ceiling

The escalating global demand for space cooling has led to the emergence of new cooling technologies, including the phase change material embedded radiant chilled ceiling (PCM-RCC) system. This technology improves energy efficiency and indoor environmental quality, while also offering demand-side flexibility. The present study experimentally evaluates the thermal efficiency and energy performance of a PCM-RCC system in a full-scale test cabin equipped with PCM panels. Here, the transient thermal behaviour of PCM ceiling panels besides the cooling energy delivered during charging-discharging cycles are examined. The indoor thermal comfort and peak electricity demand reduction enabled by the present PCM-RCC are also discussed. The results reveal that chilled water circulation for 4–5 h overnight was sufficient to fully recharge the PCM panels. Over 80% of the occupancy time was classified as “Class B″ thermal comfort according to ISO 7730. The system's daily electricity usage was mostly concentrated during off-peak hours, accounting for ∼70% of the total usage. While the controlling schedule used in this study responded to the transient thermal behaviour of the indoor space and PCM ceiling panels, a more dynamic, predictive schedule is necessary to improve the system's overall efficiency and further enhance indoor thermal comfort in response to the changing environmental conditions.

Simplified Model of Heat Load Prediction and Its Application in Estimation of Building Envelope Thermal Performance

This study provides a reference for estimating the building envelope thermal performance at the initial stage of design for nearly zero-energy buildings in different climate zones. A simplified model of heat load prediction, which combines the quasi-steady-state thermal balance calculation procedure in ISO 52016 and the variable-base degree-days method, was proposed. Therefore, a building energy performance evaluation tool BPT V1.0 was developed. Subsequently, the simplified model was validated through comparative analysis with the Building Energy Simulation Test (BESTEST) standard procedure. To conduct a feasibility analysis of the development tool, case studies were performed on the performance evaluation of building envelopes of residential and office buildings in different climate zones in China. Compared to the simulation results from EnergyPlus, the deviation of heat load calculated by BPT V1.0 was within 10%, which further verifies the applicability of the tool under different climatic conditions. Annual heat load under different thermal performance building envelopes was calculated through BPT V1.0. The building energy efficiency improvement rates were found to range from 30 to 60% in nearly zero-energy buildings in different climate zones in China. The study results can provide a reference for energy managers and a basis for estimating the building energy efficiency performance with different envelope thermal properties in the region.

Energy Consumption Analysis Using Weighted Energy Index and Energy Modeling for a Hotel Building

Energy consumption is an essential and vital issue for commercial hotel buildings. Regulations and codes are commonly used to regulate the energy usage of the building. However, the energy index used to evaluate energy performance does not include the usage of hotel buildings for different service purposes. This study utilizes a comprehensive approach involving data collection, field measurement, regression analysis, and building energy modeling to investigate the energy performance in hotel buildings. The study finds that ambient temperature and occupancy rate are key factors in energy consumption, resulting in a weighted energy index for public areas and guest rooms with an R-square of 0.8314 and 0.9184, respectively. The measurement data are also used to perform the energy modeling, and the data are validated. Studies on different regions, occupancy, orientation, window-to-wall ratios, and U-values are evaluated and simulated to determine the energy consumption, which might be useful for the hotel building design phase. In addition, it also evaluates the energy-saving potential, including chilled and condenser water temperature, COP, and indoor temperature settings. The study finds that implementing various studies could result in significant energy consumption and savings, with higher chilled water and lower condenser water temperature having a particularly prominent impact. The study concludes that energy modeling approaches can be useful tools for identifying and implementing energy-saving strategies.

New indicator for a comprehensive evaluation of building energy performance through spatial and temporal dimensions

Building functioning requires energy consumption. Traditional building energy performance (BEP) certification typically takes energy consumption as a single indicator, neglecting to evaluate the effect of energy application. Based on the definition of BEP and integrated consideration of energy consumption and service management, this study proposes a methodological path to construct a comprehensive performance indicator for buildings by evaluating energy consumption efficiency and amplitude of fluctuation using the XGBoost algorithm and objective assignment method. The indicator compares the deviation between actual and benchmark energy consumption in the spatial dimension and the amplitude of energy efficiency ratio fluctuations in the temporal dimension. Consequently, a comprehensive BEP evaluation model is thus coupled to form the comprehensive energy performance indicator (CEPI). The proposed approach is verified based on a city-scale dataset of over 2000 buildings, with CEPIi = 0.5288ECIi + 0.4712*MPIi for Chongqing. Compared with other evaluation systems, it is more intuitive, simple and robust, and can objectively reflect the rationality of energy use and provide a basis for scientific judgment.