scholarly journals A comparative benchmarking study of multi-storey residential buildings in two periods of energy saving efforts: the 1980s and the 2010s

2021 ◽  
Vol 2069 (1) ◽  
pp. 012075
Author(s):  
O M Jensen ◽  
J Rose ◽  
J Kragh ◽  
C H Christiansen ◽  
M Grimmig ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Residential Buildings ◽  
Measurement Data ◽  
Building Energy ◽  
Energy Performance ◽  
Building Energy Performance ◽  
Heated Area ◽  
Energy Signature ◽  
Change Point Models

Abstract In 1990, Technological Institute (TI) in Denmark made a benchmarking study of 92 typical multi-storey buildings covering 23 000 dwellings. The study included measurement data from the 1970s and the years after the energy crises. This study showed that over a period of less than 20 years a significant reduction in energy consumption took place. In a new similar study, TI and Aalborg University have analysed 62 buildings covering 18 000 dwellings including measurement data from the last 20 years. This time, the data covers a period with an increasing focus on the carbon-emission impacts of energy consumption. As opposed to the first benchmarking study, the new 20-years study shows that the heat consumption has been almost constant over the last 20 years. This paper presents a comparative study of the two sets of measurements and evaluates energy saving efforts and individual building energy performance. Furthermore, the paper compares two different ways of deriving benchmarks from the data and demonstrates how utilizing change-point models/energy signature as opposed to the more traditional mean annual values per heated area, significantly increases the usability.

scholarly journals Identification of Environmental and Contextual Driving Factors of Air Conditioning Usage Behaviour in the Sydney Residential Buildings

Buildings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 122
Author(s):  
Bongchan Jeong ◽  
Jungsoo Kim ◽  
Zhenjun Ma ◽  
Paul Cooper ◽  
Richard de Dear
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Energy Use ◽  
Residential Buildings ◽  
Significant Proportion ◽  
Building Energy ◽  
Energy Performance ◽  
Time Of Day ◽  
Performance Simulation ◽  
Building Energy Performance

Air conditioning (A/C) is generally responsible for a significant proportion of total building energy consumption. However, occupants’ air conditioning usage patterns are often unrealistically characterised in building energy performance simulation tools, which leads to a gap between simulated and actual energy use. The objective of this study was to develop a stochastic model for predicting occupant behaviour relating to A/C cooling and heating in residential buildings located in the Subtropical Sydney region of Australia. Multivariate logistic regression was used to estimate the probability of using A/C in living rooms and bedrooms, based on a range of physical environmental (outdoor and indoor) and contextual (season, day of week, and time of day) factors observed in 42 Sydney region houses across a two-year monitoring period. The resulting models can be implemented in building energy performance simulation (BEPS) tools to more accurately predict indoor environmental conditions and energy consumption attributable to A/C operation.

scholarly journals Re-discussion and Correction of Shape Coefficient for Residential Buildings

2019 ◽  
Vol 136 ◽  
pp. 04096
Author(s):  
Lingkun Jia ◽  
Yiru Huang ◽  
Zhietie Yue ◽  
Perry Pei-Ju Yang
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Residential Building ◽  
Building Energy ◽  
Energy Performance ◽  
Research Field ◽  
Residential Energy ◽  
Building Energy Performance ◽  
Shape Coefficient ◽  
Performance Research

As one of the critical concepts in residential energy performance research field, shape coefficient has long been disputed for its validity of evaluating energy consumption. Although suggestions have been brought forward to try to optimize this concept, these proposals still have shortcomings and have not been tested. Based on analysing these existing optimizing proposals, this paper starts from prototype study and summarizes the problems of concept of shape coefficient in terms of definition and relationship with building energy. According to these current issues, the reason for negatively influencing the accuracy of shape coefficient with regard to assessing the building energy consumption is confirmed. By correcting the expression of shape coefficient through inserting a correction factor related to story height, corrected shape coefficient is proposed. Combined with built residential building samples, the corrected and original shape coefficient is contrasted at the macro statistical and micro experimental levels respectively. It is found that the new coefficient has closer correlation with residential building energy performance and is more accurate in evaluating the energy consumption.

scholarly journals Modifying Building Energy-Saving Design Based on Field Research into Climate Features and Local Residents’ Habits

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 442
Author(s):  
Xiaoyue Zhu ◽  
Bo Gao ◽  
Xudong Yang ◽  
Zhong Yu ◽  
Ji Ni
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Residential Buildings ◽  
Average Energy ◽  
Field Tests ◽  
Building Energy ◽  
Building Energy Efficiency ◽  
Local Conditions ◽  
Building Energy Saving ◽  
Average Energy Consumption

In China, a surging urbanization highlights the significance of building energy conservation. However, most building energy-saving schemes are designed solely in compliance with prescriptive codes and lack consideration of the local situations, resulting in an unsatisfactory effect and a waste of funds. Moreover, the actual effect of the design has yet to be thoroughly verified through field tests. In this study, a method of modifying conventional building energy-saving design based on research into the local climate and residents’ living habits was proposed, and residential buildings in Panzhihua, China were selected for trial. Further, the modification scheme was implemented in an actual project with its effect verified by field tests. Research grasps the precise climate features of Panzhihua, which was previously not provided, and concludes that Panzhihua is a hot summer and warm winter zone. Accordingly, the original internal insulation was canceled, and the shading performance of the windows was strengthened instead. Test results suggest that the consequent change of SET* does not exceed 0.5 °C, whereas variations in the energy consumption depend on the room orientation. For rooms receiving less solar radiation, the average energy consumption increased by approximately 20%, whereas for rooms with a severe western exposure, the average energy consumption decreased by approximately 11%. On the other hand, the cost savings of removing the insulation layer are estimated at 177 million RMB (1 USD ≈ 6.5 RMB) per year. In conclusion, the research-based modification method proposed in this study can be an effective tool for improving building energy efficiency adapted to local conditions.

Optimization of Energy Consumption Using BIM-Based Building Energy Performance Analysis

2013 ◽  
Vol 281 ◽  
pp. 649-652 ◽  
Author(s):  
Dae Kyo Jung ◽  
Dong Hwan Lee ◽  
Joo Ho Shin ◽  
Byung Hun Song ◽  
Seung Hee Park
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Performance Analysis ◽  
Cooling System ◽  
Optimization Technique ◽  
Building Energy ◽  
Energy Performance ◽  
Information Modeling ◽  
Building Energy Performance ◽  
Heating And Cooling

Recently, the interest in increasing energy efficiency of building energy management system (BEMS) has become a high-priority and thus the related studies also increased. In particular, since the energy consumption in terms of heating and cooling system takes a large portion of the energy consumed in buildings, it is strongly required to enhance the energy efficiency through intelligent operation and/or management of HVAC (Heating, Ventilation and Air Conditioning) system. To tackle this issue, this study deals with the BIM (Building Information Modeling)-based energy performance analysis implemented in Energyplus. The BIM model constructed at Revit is updated at Design Builder, adding HVAC models and converted compatibly with the Energyplus environment. And then, the HVAC models are modified throughout the comparison between the energy consumption patterns and the real-time monitoring in-field data. In order to maximize the building energy performance, a genetic algorithm (GA)-based optimization technique is applied to the modified HVAC models. Throughout the proposed building energy simulation, finally, the best optimized HVAC control schedule for the target building can be obtained in the form of “supply air temperature schedule”.

Investigating the probability of designing net-zero energy buildings with consideration of electric vehicles and renewable energy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Seyed Sajad Rezaei Nasab ◽  
Abbasali Tayefi Nasrabadi ◽  
Somayeh Asadi ◽  
Seiyed Ali Haj Seiyed Taghia
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Building Energy ◽  
Energy Performance ◽  
Zero Energy ◽  
Content Type ◽  
Building Energy Performance ◽  
Net Zero Energy ◽  
Net Zero ◽  
Net Zero Energy Buildings

PurposeDue to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.Design/methodology/approachFirst, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.FindingsThe results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.Originality/valueConsidering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

Energy Consumption Simulation for Residential Buildings With Shading Devices in Different Regions

2007 ◽  
Author(s):  
Junjie Liu ◽  
Xiaojie Zhou ◽  
Zhihong Gao
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Residential Building ◽  
Building Energy ◽  
Energy Performance ◽  
Indoor Environments ◽  
Total Energy Consumption ◽  
South West ◽  
Shading Devices ◽  
Energy Consumption Simulation

With the development of energy saving, it is needed to calculate the energy consumption of the residential building, particularly accurate dynamic energy consumption. Fixed shading devices are wildly used to save building energy because they prevent undesirable heat coming through the windows during the “overheated period”, just as in summer, which can ameliorate the indoor environments and reduce the energy consumption of air-conditioning in summer. But they will also prevent solar energy which can be used in winter to enter windows. So it is very important to be able to determine the optimal shading devices of windows. The overhangs and vertical-shading devices are representative to study the different energy performance in summer and winter, in an actual dwell house. On the other hand, fixed shading devices can weaken the effect of daylighting, so we would take both the total energy consumption and rooms’ daylighting into account. In this study, we choose several typical dwelling houses in different cities located in north, south, west, east and central region of China respectively. We calculated energy consumption of those models by using Energyplus program, and compared the shading performance of horizontal and vertical shading devices, then optimal configuration dimensions of horizontal shading devices are recommended on the basis of different requirements for solar heat gains in winter and in summer for those typical dwelling houses.

scholarly journals Modeling the Impacts of Local Factors for Healthcare Building Energy Performance Improvement in Thailand

2018 ◽  
Vol 3 (8) ◽  
pp. 157-166
Author(s):  
Nuttasit Somboonwit ◽  
Nopadon Sahachaisaeree
Keyword(s):  
Energy Consumption ◽  
Performance Improvement ◽  
Building Design ◽  
Building Energy ◽  
Energy Performance ◽  
Health Care Facilities ◽  
Information Modeling ◽  
Slight Variation ◽  
Building Energy Performance ◽  
Local Factors

This research aims to perform, compare, and evaluate Integrated Building Design (IBD) processes, collaborating the Building Information Modeling (BIM) with Building Performance Simulation (BPS) applications to perform energy analysis and to improve the building energy performance of a Generalizable Building Design (GBD), an universal application on health care facilities design in Thailand. The IBD processes produce the simulation results in a harmonious direction. Slight variation of building orientation could alter the extent of energy consumption. The integration of the three measures could minimize the energy consumption greatly. The study addresses limitations of the IBDs in the software integration processes. Keywords: Local Factors in Construction ; Energy Performance Improvement ; Generalizable Healthcare Building Design ; Integrated Building Design. eISSN 2514-751X © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. https://doi.org/10.21834/aje-bs.v3i8.288   

scholarly journals Top Energy Saver of the Year: Results of an Energy Saving Competition in Public Buildings

2020 ◽  
Vol 24 (3) ◽  
pp. 278-293
Author(s):  
Jan Kaselofsky ◽  
Ralf Schüle ◽  
Marika Rošā ◽  
Toms Prodaņuks ◽  
Anda Jekabsone ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Energy Use ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
Energy Performance ◽  
Heat Consumption ◽  
The European Union ◽  
Public Building ◽  
Team Members

AbstractNon-residential buildings in the European Union consume more than one third of the building sector’s total. Many non-residential buildings are owned by municipalities. This paper reports about an energy saving competition that was carried out in 91 municipal buildings in eight EU member states in 2019. For each public building an energy team was formed. The energy teams’ activities encompassed motivating changes in the energy use behaviour of employees and small investments. Two challenges added an element of gamification to the energy saving competition. To assess the success of the energy saving competition, an energy performance baseline was calculated using energy consumption data of each public building from previous years. Energy consumption in the competition year was monitored on a monthly base. After the competition the top energy savers from each country were determined by the percentage-based reduction of energy consumption compared to the baseline. On average, the buildings had an electricity and heat consumption in 2019 that was about 8 % and 7 %, respectively, lower than the baseline. As an additional data source for the evaluation, a survey among energy team members was conducted at the beginning and after the energy competition. Support from superiors, employee interest and motivation and behaviour change as assessed by energy team members show a positive, if weak or moderate, correlation with changes in electricity consumption, but not with changes in heat consumption.

An Uncertainty and Sensitivity Analysis Tool for Building Thermal Energy Consumption: A Performance Comprehension of Static and Dynamic Response Analyses

2019 ◽  
Author(s):  
Rasool Koosha ◽  
Fatemeh Shahsavari
Keyword(s):  
Sensitivity Analysis ◽  
Energy Consumption ◽  
Dynamic Response ◽  
Building Energy ◽  
Energy Performance ◽  
Response Analysis ◽  
Design Decision ◽  
Building Energy Consumption ◽  
Predictive Tool ◽  
Building Energy Performance

Abstract Recent literature on building energy performance simulation leans toward implementing uncertainty analysis (UA), instead of deterministic solutions, to handle ever-existing and pivotal uncertainties in building design decision-making process. Variations in weather temperature, degradation of building envelope material properties over time, and random behavior of occupants, among all, are the key sources of uncertainty in building energy consumption predictions. The UA couples to the sensitivity analysis (SA) to identify the most influential inputs on the uncertainties of the building energy consumption. This paper describes a newly-developed UA and SA predictive tool for building energy performance simulations. Energy performance simulations are based on a resistance-capacitance thermal model for the building. For a hypothetical residential building in College Station, Texas, USA, the present work describes and compares predicted probability distribution and sensitivity indexes produced by the UA-SA tool using a transient (dynamic) response analysis (TRA) and static response analysis (SRA). For brevity, the analysis considers uncertainty only for the exterior walls’ parameters including thickness, thermal conductivity, heat transfer coefficient, density, and heat capacity; i.e., a five-dimensional problem is solved. Compared to the TRA, predictions from the SRA underestimate the annual energy consumption up to 30%; however, SRA is significantly faster. Nonetheless, sensitivity indexes from the SRA and TRA closely match.

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