Achieving carbon neutrality by 2050 requires evaluating and retrofitting existing buildings. However, despite the numerous studies on energy analytics, they usually focus on energy consumption ...patterns and motifs rather than encompassing various energy usage characteristics. This study proposes a novel symbolic hierarchical clustering for building energy analytics at the city level. It utilizes change-point model (CPM) parameters to represent building energy usage, performance, occupant behavioral characteristics. The clustering method based on the CPM parameters defines energy performance signatures (EPS) for determining their energy characteristics and as symbolic data transformation. In a case study conducted in Gangwon, South Korea, five different energy performance signatures (EPSs 1–5) showing their unique energy characteristics were determined for commercial buildings. EPS1 to 3 were classified as signatures with good performance (65.5% of all buildings) while EPS4 and 5 were classified as signatures with bad performance (34.5%). Using this EPS symbolic data, an EPS map was visualized and analyzed from various perspectives. For example, buildings that showed a continuous or overall decline in envelope performance over five years were among the oldest buildings (construction completion date closer to 1978; 7.9%). Despite poor envelope performance, buildings with lower energy usage showed a tendency for occupants to delay heating (28.4%). The proposed method can contribute to the data-driven building energy analytics in providing detailed insights into energy usage patterns, building energy performance, and occupant behavioral characteristics at the city level. The effectiveness of open-source energy data for urban building energy analysis would be improved through the proposed method.
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•Energy performance signature (EPS)-based clustering is proposed for urban building energy analysis.•A combined data-driven five-parameter change-point model and clustering using symbolically transformed data are proposed.•A case study is conducted to analyze energy usage characteristics of commercial buildings in Gangwon, South Korea.•The EPS map from the proposed method provides information on the change in envelope performance, energy consumption pattern, and occupant behavior.
Fuel Poverty is a big challenge for everybody: politicians, decision-makers, technicians, researchers, etc. In Italy, a strategy to solve fuel poverty involves action in order to reduce energy ...prices, the AEEG (Italian regulatory authority for electricity gas and water) has defined an Assist Tariff for poor people. Fuel poverty depends on family income and energy prices. Building energy performance also influences required energy consumption, and is a contributing cause of fuel poverty. Subsequently, it is possible to introduce a new Fuel Poverty risk Index, correlated to Building Energy Performance: the Building Fuel Poverty index. The Building Fuel Poverty Index (BFP) allows us to quantify how many buildings need direct action and/or just economic incentives.
The index should be adopted in order to identify subjects that can afford to pay building energy refurbishment. The paper proposes an index in order to evaluate fuel poverty condition correlated to building energy performance.
•How to measure a building energy index to find fuel poverty.•How to use energy performance certificates in order to define.•The building fuel poverty index as a tool to drive policy choice.
Increasing the performance of an energetic material can be achieved by changing its composition or using additives, such as metal powders. Aluminum hydride (AlH3) exhibits attractive properties, such ...as high hydrogen/energy storage, relatively good stability, and low dehydrogenation temperature. AlH3 has excellent prospects for use as a component in solid propellants for increasing the specific impulse of rocket engines and effectively reducing the erosion of engine nozzles. In this work, the effect of AlH3 on the energy performance, ignition characteristics, and combustion characteristics of solid propellants, as well as the agglomeration characteristics of metal particles was investigated. It was found that with increasing AlH3 content, the theoretical mass heat of combustion and the theoretical volumetric heat of combustion of the propellants increased, and the combustion efficiency also gradually improved. When the content of AlH3 in the propellant increased from 0.00% to 17.00%, the temperature of the propellant combustion chamber was reduced from 3314.59 to 2957.49 K and the theoretical specific impulse increased from 2584.2 to 2641.7 N‧s/kg. The average molecular mass of the gas was reduced from 25.54 to 21.54 due to the large amount of hydrogen gas released by the combustion of AlH3. The maximum combustion temperature decreased and the burning rate increased with the gradual replacement of aluminum (Al) in the propellant with AlH3. The maximum combustion temperatures of the pure Al propellant and the pure AlH3 propellant were 2510.5 and 2232.5 K, respectively. The linear burning rates were 0.29 and 0.46 cm/s at 1.0 MPa, respectively. The agglomeration process of AlH3 included three main stages, namely accumulation, aggregation, and agglomeration. With the increase in the AlH3 content, the number of agglomerated particles in the propellant gas-phase flame region decreased continuously.
Real energy performances of buildings depend not only on deterministic aspects, such as building physics and HVAC systems, but also on stochastic aspects such as weather and occupants' behavior. ...Typically, occupant behavior is not adequately considered when calculating the expected performance. As a result, field test studies all over Europe have shown discrepancies between real and expected energy performance of buildings. In order to bridge this gap, stochastic occupants' behavior models could be embedded into building energy performance simulation software. In order to make such models, there is a need for a better understanding of occupants' behavior and in particular the reasons of their adjustments of building controls such as window opening, heating set points, etc. The purpose of this paper was to analyze window opening behavior in residential buildings, investigate which drivers lead occupants to interact with windows and how these actions can be modeled. A method to analyze the probability of a state change of the windows, based on logistic regression, was applied to monitored data (measured each minute) from two refurbished demonstration buildings. The weather and the five rooms of the 60 apartments located in the buildings were monitored in terms of air quality and thermal environment (presence of occupants was not monitored) during four years.
The most common driver to open a window was the time of the day, followed by the carbon dioxide concentration. The most common driver to close a window was the daily average outdoor temperature, followed by the time of the day.
•Occupants open and close windows depending on drivers leading them to take action.•Drivers can be identified through logistic regression analysis.•The most common drivers for opening action are: time of the day and CO2 concentration.•The most common drivers for closing action are: outdoor temperature and time of the day.•Thermal comfort and AIQ play a role for occupant behavior in regard to natural ventilation.
As a market-based mechanism which can actively promote energy efficiency, Energy Performance Contracting (EPC) is now universally accepted throughout China and has been incorporated into various ...business models. Four of these business models are frequently adopted in China: the Share Savings Model, the Guaranteed Savings Model, the Energy-cost Trust Model and the Finance Lease Model. The choice of a suitable business model has been recognized as one of the most important factors in the effective implementation of EPC projects. In this paper, the selection of EPC business models is formulated as a multi-criteria decision making (MCDM) problem. When selecting an EPC business model, it is natural for decision-makers (DMs) to express their preferences/opinions in linguistic terms. Given the characteristics of EPC projects, taking DMs' psychological behavior into account is of considerable and realistic significance. TODIM (an acronym in Portuguese of interactive and multicriteria decision making) has been verified as an effective behavioral decision-making method. To address the problem of EPC business model selection, an extended TODIM method based on multi-granularity linguistic terms and entropy measure is proposed. The sensitivity and comparison analyses show that DMs' psychological behavior can affect the selection order with respect to the given EPC business models. One case of a real-life campus EPC project demonstrates that the validity and applicability of the proposed extended TODIM method for solving the EPC business model selection problem.
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•First attempt to quantify the Energy Performance Gap of the Italian building stock.•Theoretical Energy Performance Gap assessment with parametric energy simulations.•Energy ...Performance Gap as a function of the climatic zone and building type.•Rebound and Prebound effects range of values under different user profiles.•Energy Performance Gap assessment for standard calculation method correction.
Energy Performance Gap (EPG) is a crucial issue in the building sector that can lead to an overestimation of the national energy policies. It is the difference between the calculated energy consumption and actual energy use, and it is relevant mainly for space heating. As EPG quantification or correction methods could lead to more realistic energy policies, EPG has become a focus of many studies and research. In this framework, this study aims to quantify the theoretical deviation of EPG, i.e., concerning to the standard conditions, for the Italian residential building stock by performing parametric energy simulations of thousands of representative reference buildings. After a comprehensive thermophysical characterization of the national building stock, parametric simulations were carried out by varying the main standard conditions set in the Energy Performance Certificate (EPC) calculation. This approach allowed the quantification of EPG according to the climatic zone, building type, usage profile, and thermal insulation level of buildings, while also analysing the influence of these parameters on the EPG and checking for prebound or rebound effects (i.e. when standard consumption is greater or smaller than actual one). The study identified a range of EPG variability for both prebound (0% to +80%) and rebound (−30% to 0%) effects and quantified an average EPG between −3 and +16 kWh per heating degree day of the selected location as a function of the usage profile. This work represents the first attempt to calculate the EPG of the Italian residential building stock and it could lead to the correction of the national energy policies implemented in the building sector.
In photovoltaic–thermal (PV/T) technology, the use of glass cover on the flat-plate hybrid solar collector is favorable to the photothermic process but not to the photovoltaic process. Because of the ...difference in the usefulness of electricity and thermal energy, there is often no straight forward answer on whether a glazed or unglazed collector system is more suitable for a specific application. This glazing issue was tackled in this paper from the viewpoint of thermodynamics. Based on experimental data and validated numerical models, a study of the appropriateness of glass cover on a thermosyphon-based water-heating PV/T system was carried out. The influences of six selected operating parameters were evaluated. From the first law point of view, a glazed PV/T system is found always suitable if we are to maximize the quantity of either the thermal or the overall energy output. From the exergy analysis point of view however, the increase of PV cell efficiency, packing factor, water mass to collector area ratio, and wind velocity are found favorable to go for an unglazed system, whereas the increase of on-site solar radiation and ambient temperature are favorable for a glazed system.
Energy Performance Certificates (EPCs) are the adopted method by which the UK government tracks the progress of its domestic energy efficiency policies. Over 15 million EPCs have been lodged, ...representing a valuable resource for research into the UK building stock. However, the EPC record has a reputation of containing multiple errors. In this work, we identify many such errors and quantify how common they are. We find that 27% of EPCs in the open EPC record display at least one flag to suggests it is incorrect and estimate the true error rate of the EPC record to be between 36 and 62%. Many of these errors are caused by EPC assessors disagreeing on building parameters such as floor type, wall type and built form. Additionally, flats and maisonettes appear to cause more issues than other property types. This may be due to difficulties in assessing their location in the building and the nature of the surrounding space. We also suggest potential new methods of quality assurance which rely on machine learning and which could allow such errors to be avoided in the future.
•Between 36 and 62% of Energy Performance certificates possess errors.•Many of these errors are caused by simple-to-assess building parameters.•Flats and Maisonettes show more errors that other dwelling types.•The energy efficiency rating of EPCs will typically change by 4 points due to errors.•Machine learning has the potential to avoid many of these errors in future EPCs.
The energy efficiency of different biogas systems, including single and co-digestion of multiple feedstock, different biogas utilization pathways, and waste-stream management strategies was ...evaluated. The input data were derived from assessment of existing biogas systems, present knowledge on anaerobic digestion process management and technologies for biogas system operating conditions in Germany. The energy balance was evaluated as Primary Energy Input to Output (PEIO) ratio, to assess the process energy efficiency, hence, the potential sustainability. Results indicate that the PEIO correspond to 10.5–64.0% and 34.1–55.0% for single feedstock digestion and feedstock co-digestion, respectively. Energy balance was assessed to be negative for feedstock transportation distances in excess of 22
km and 425
km for cattle manure and for Municipal Solid Waste, respectively, which defines the operational limits for respective feedstock transportation. Energy input was highly influenced by the characteristics of feedstock used. For example, agricultural waste, in most part, did not require pre-treatment. Energy crop feedstock required the respect cultivation energy inputs, and processing of industrial waste streams included energy-demanding pre-treatment processes to meet stipulated hygiene standards. Energy balance depended on biogas yield, the utilization efficiency, and energy value of intended fossil fuel substitution. For example, obtained results suggests that, whereas the upgrading of biogas to biomethane for injection into natural gas network potentially increased the primary energy input for biogas utilization by up to 100%; the energy efficiency of the biogas system improved by up to 65% when natural gas was substituted instead of electricity. It was also found that, system energy efficiency could be further enhanced by 5.1–6.1% through recovery of residual biogas from enclosed digestate storage units. Overall, this study provides bases for more detailed assessment of environmental compatibility of energy efficiency pathways in biogas production and utilization, including management of spent digestate.
To cope with rapid urbanization and achieve urban sustainable development, both energy efficiency and GHG emissions in the building sector are considered as the main challenges in recent years. ...Multi-objective optimization will be a useful tool in energy saving and low carbon for town planning policy making. This study incorporates geographical weighting (GW) with the Light Gradient Boosting Machine (LGBM), namely the GW-LGBM method, to analyze the impact of the surrounding environment on building energy performance. Besides, a genetic algorithm-based approach is applied in this research to achieve a multi-objective optimization solution for buildings' energy performance and GHG emissions. A Pareto front of the optimal trade-off solution with different influential variables and multi-objectives can be determined. Several scenarios incorporating various percentages of constraints are performed, aiming to provide more strategies for decision-makers under different situations. The main findings are summarized as: (1) The proposed GW-LGBM shows superior predictability for assessing the buildings' energy performance than the traditional LGBM. The value of the indices R2 is 0.91 in site EUWN (weather normalized energy use) and 0.90 in GHG emissions, which have respectively 6.14% and 9.22% improvement compared with the LGBM; (2) Four common factors, including the Natural gas, total Gross floor area, Energy star score, and shape form, are identified as the most important factors for both site EUWN and GHG emissions; (3) The change of the three influence factors, such as the natural gas, vertical to horizontal ratio, and greenery density, is expected to achieve a 37.77% improvement for mitigating energy consumption and GHG emissions given a 10% change in the adjustable factors. The novelty lies in the development of GW-LGBM by adding geographical weight to learning energy patterns for achieving more accurate results in building performance estimation and optimization.
•A GW-LightGBM method is developed for analyzing building energy and GHG emissions.•An explainable AI method is applied to identify and explore the most critical factors.•Multi-objective optimization (MOO) is applied to find the optimal solution for energy savings.•Different constraints are given to investigate the effect on the improvement magnitude.
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