scholarly journals Minimising the Deviation between Predicted and Actual Building Performance via Use of Neural Networks and BIM

Buildings ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 131 ◽  
Author(s):  
Ahmed WA Hammad
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Building Energy ◽  
Energy Performance ◽  
Limiting Factor ◽  
Occupant Behaviour ◽  
Actual Performance ◽  
Building Energy Performance ◽  
The Difference ◽  
Actual Energy Consumption

Building energy performance tools are widely used to simulate the expected energy consumption of a given building during the operation phase of its life cycle. Deviations between predicted and actual energy consumptions have however been reported as a major limiting factor to the tools adopted in the literature. A significant reason highlighted as greatly influencing the difference in energy performance is related to the occupant behaviour of the building. To enhance the effectiveness of building energy performance tools, this study proposes a method which integrates Building Information Modelling (BIM) with artificial neural network model for limiting the deviation between predicted and actual energy consumption rates. Through training a deep neural network for predicting occupant behaviour that reflects the actual performance of the building under examination, accurate BIM representations are produced which are validated via energy simulations. The proposed method is applied to a realistic case study, which highlights significant improvements when contrasted with a static simulation that does not account for changes in occupant behaviour.

scholarly journals Building Energy Performance Certificate—A Relevant Indicator of Actual Energy Consumption and Savings?

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3455
Author(s):  
Aleksandar S. Anđelković ◽  
Miroslav Kljajić ◽  
Dušan Macura ◽  
Vladimir Munćan ◽  
Igor Mujan ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Gap ◽  
Building Energy ◽  
Energy Performance ◽  
Building Stock ◽  
District Heating System ◽  
Performance Gap ◽  
Building Energy Performance ◽  
Actual Energy Consumption

A building energy performance gap can be illustrated as the difference between the theoretical (methodologically defined) and the actual energy consumption. In EU countries, Energy Performance Certificates are issued when buildings are constructed, sold, or leased. This information is the first step in order to evaluate the energy performance of the building stock. In Serbia, when issuing an energy certificate, the adopted national methodology recognizes only energy consumption for heating. The main purpose of this paper is to evaluate the energy gap and estimate the relevance of an Energy Performance Certificate to meet the national energy efficiency or carbon target. An Energy Performance Certificate determines the theoretical residential and commercial building energy efficiency or its “design intent”. This research stresses the necessity of measuring and achieving reductions in actual energy consumption through system regulation and consumers’ self-awareness in buildings. The research compares the performance of the building stock (135) that is connected to the District Heating System (DHS), with its own integrated heat meter, to Individual Gas Boiler (IGB) systems (18), in the city of Novi Sad, Serbia, built after 2014. For the purpose of comparing energy consumption, 16 buildings were selected that are very similar in terms of design, operation, and location. The data used are derived from metered consumption data, official evidence of city service companies, and Energy Performance Certificates of the considered buildings. We have determined that IGB systems have a much wider specific annual performance gap (11.19–101 kWh/m2a) than the buildings in the DHS (3.16–18.58 kWh/m2a).

Building performance in the context of industry pressures

2014 ◽  
Vol 8 (4) ◽  
pp. 527-543
Author(s):  
Craig Robertson ◽  
Dejan Mumovic
Keyword(s):  
Energy Consumption ◽  
Performance Assessment ◽  
Energy Gap ◽  
Building Energy ◽  
Energy Performance ◽  
Building Performance ◽  
Structured Interviews ◽  
Web Based ◽  
Actual Performance ◽  
Content Type

Purpose – This paper aims to explore the relationship between designed and actual building performance as represented in an Royal Institute of British Architects- and Chartered Institution of Building Services Engineers-backed web-based comparison platform and the industry perception of the pressures surrounding building performance assessment. European directives and UK Parliamentary Acts have resulted in a range of mechanisms aimed at encouraging monitoring of energy consumption, responsive management and evidence-based design. Web-based feedback platforms aim to feed evaluation data back to industry anonymously; however, there exists a range of barriers and disincentives that prevent widespread and habitual engagement with building evaluation. Design/methodology/approach – Using energy data from the CarbonBuzzweb platform and a series of semi-structured interviews, a mixed-methods study has been carried out. Analysis of the characteristics of the existing energy discrepancy between designed and actual performance shows where variance typically occurs. Interviews with industry actors presents a synopsis of the perceived and actual legislative and procedural pressures that exist in relation to building performance assessment. Findings – The conclusions of this paper identify weaknesses in the current legislative and incentivisation mechanisms with regard to targeting building energy performance and industrial pressures that hinder broader industry engagement with post-occupancy evaluation. Originality/value – The recommendations arising from this study are for adjustments to the existing legislative framework to increase participation in meaningful building energy evaluation targeted at the specifics of the energy gap and the motivations of industrial actors. This will specifically help to reduce building energy consumption and associated carbon emissions.

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.

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 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.

Uncertainty of Daylighting Performance of Manual Solar Shades and its Influence on Lighting Energy

2020 ◽  
pp. 77-84
Author(s):  
Jian Yao ◽  
LiYi Chen ◽  
Wu Jin
Keyword(s):  
Energy Consumption ◽  
Economic Analysis ◽  
Stochastic Model ◽  
Building Energy ◽  
Energy Performance ◽  
Building Energy Consumption ◽  
Occupant Behaviour ◽  
The South ◽  
Weak Relationship ◽  
Lighting Energy

Occupant behaviour significantly influences building energy consumption. This paper is devoted to studies the uncertainty of daylighting performance and lighting energy of manual solar shades on the south facade. A developed stochastic model for manual solar shades was used for co-simulation by BCVTB. Results show that uncertainty of shade action was not suppressed by the shade behaviour model with very weak relationship between different simulation outputs. Uncertainty of daylighting performance is 15.08 % while lighting energy uncertainty is 10.38 %. Although this level of energy uncertainty is not very significant, it influences economic analysis of manual solar shades and therefore, occupant related uncertainty should be taken into consideration when predicting energy performance of manual shades.

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.

scholarly journals Occupant behaviour: a major issue for building energy performance

2019 ◽  
Vol 609 ◽  
pp. 072050
Author(s):  
Y Laaroussi ◽  
M Bahrar ◽  
M Elmankibi ◽  
A Draoui ◽  
A Si-Larbi
Keyword(s):  
Building Energy ◽  
Energy Performance ◽  
Occupant Behaviour ◽  
Building Energy Performance

scholarly journals Energy-Related Occupant Behaviour and Its Implications in Energy Use: A Chronological Review

2018 ◽  
Vol 10 (8) ◽  
pp. 2635 ◽  
Author(s):  
Vivian Tam ◽  
Laura Almeida ◽  
Khoa Le
Keyword(s):  
Energy Use ◽  
Building Energy ◽  
Energy Performance ◽  
Design Stage ◽  
Occupant Behaviour ◽  
Building Energy Use ◽  
Key Variables ◽  
The Difference ◽  
The One ◽  
Building Life Cycle

It is essential to understand how significantly occupants’ actions impact the performance of a building, as a whole, in terms of energy use. Consequently, this paper reviews the available resources on energy-related occupant behaviour and its implications in energy use in a building. A chronological review on energy-related occupant behaviour and its implications in energy use has been conducted. As a main existing gap, it was identified by researchers the difference between real energy performance and the one that is predicted during the design stage of a building. The energy predicted during the design stage of a building may be over twice the energy used in the operation stage. Buildings are one of the most energy intensive features in a country. They are affected by the interaction and correlation of several different variables, such as: its physical characteristics, technical systems, equipment, occupants, etc. Therefore, buildings are considered to be complex systems that require a careful and intensive analysis. Moreover, one of the key variables impacting real building energy use is occupant behaviour. The way occupants behave and their motivations are some of the main aspects that need to be considered in a building life-cycle.

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