Final and primary energy use for heating new residential area with varied exploitation levels, building energy performance and district heat temperatures

This Technical Note describes a framework for handling the inherent complexities of carbon emission and primary energy factors for networked electricity supply systems within building energy codes and similar policy instruments. The proposed framework reflects the main characteristics of carbon emissions from such networked supplies, while retaining a level of complexity (and simplification) comparable to that of procedures used in existing building energy codes. The main issues that are addressed are the time-varying nature of factors for networked supply, the impact of variability and curtailment for variable and intermittent renewable sources of electricity and relationship between “marginal” factors and “average” factors. These are important issues as the currently common use of annual system-average factors can result in misleading guidance as to the most effective ways of reducing carbon emissions or primary energy demand. The note first explains the relationship between building energy performance ratings and networked electric supplies. It then discusses the characteristics of electricity demand and the networked supply systems before proposing and discussing the framework. Practical application: A framework that can improve the reliability of building energy performance rating based on carbon emissions or primary energy factors.

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Big-data for building energy performance: Lessons from assembling a very large national database of building energy use

Applied Energy ◽

10.1016/j.apenergy.2014.11.042 ◽

2015 ◽

Vol 140 ◽

pp. 85-93 ◽

Cited By ~ 87

Author(s):

Paul A. Mathew ◽

Laurel N. Dunn ◽

Michael D. Sohn ◽

Andrea Mercado ◽

Claudine Custudio ◽

...

Keyword(s):

Big Data ◽

Energy Use ◽

Building Energy ◽

Energy Performance ◽

National Database ◽

Building Energy Performance ◽

Building Energy Use ◽

Large National Database

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The Effect of Dynamic Primary Energy Factors On Building Energy Performance

Proceedings of Building Simulation 2019: 16th Conference of IBPSA ◽

10.26868/25222708.2019.211314 ◽

2020 ◽

Author(s):

Kjartan Van den Brande ◽

Sam Hamels ◽

Jelle Laverge ◽

Michel De Paepe ◽

Arnold Janssens ◽

...

Keyword(s):

Building Energy ◽

Energy Performance ◽

Primary Energy ◽

Building Energy Performance ◽

Energy Factors

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Impact of space layout on energy performance of office buildings coupling daylight with thermal simulation

E3S Web of Conferences ◽

10.1051/e3sconf/201911103077 ◽

2019 ◽

Vol 111 ◽

pp. 03077 ◽

Cited By ~ 1

Author(s):

Tiantian Du ◽

Sabine Jansen ◽

Michela Turrin ◽

Andy van den Dobbelsteen

Keyword(s):

Architectural Design ◽

Energy Use ◽

Building Energy ◽

Energy Performance ◽

Thermal Simulation ◽

Floor Plan ◽

Building Energy Performance ◽

Artificial Lighting ◽

Space Layout ◽

The Impact

Space layout design is one of the most important phases in architectural design, and current studies have shown that it can affect building energy performance. However, its influence has not been quantified. This paper aims at investigating the impact of space layouts on building energy performance. We use the floor plan of an office building in the Netherlands as reference, and propose eleven space layouts based on the reference. Calculations are performed with the tools Honeybee and Ladybug in Grasshopper, which are developed based on Daysim and EnergyPlus, to simulate lighting, cooling and heating demand of these layouts. In addition, we couple daylight with thermal simulation, by importing the artificial lighting schedule calculated in Daysim to EnergyPlus. The result shows that the heating demand of the worst layout is 12% higher than the best layout, the cooling demand of the worst layout is 10% higher than the best layout, and the lighting demand of the worst layout is 65% higher than the best layout. The total final energy use of the worst layout is 19% higher than the best layout.

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

Buildings ◽

10.3390/buildings11030122 ◽

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.

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A Comparative Study on Building Energy Performance between Movable and Fixed Shading Materials

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.164.85 ◽

2012 ◽

Vol 164 ◽

pp. 85-88

Author(s):

Xiao Chang Yang ◽

Jian Yao

Keyword(s):

Energy Use ◽

Residential Building ◽

Building Energy ◽

Energy Performance ◽

Simulation Software ◽

Public Building ◽

Building Energy Performance ◽

Energy Demands ◽

Building Energy Use ◽

Better Than

The purpose of this paper is to investigate the effect of movable shading on building energy demands. A public building and a residential building with movable shading and fixed shading were modeled by the building energy use simulation software DOE-2. Cooling and heating energy demands were calculated. The results showed that movable shading is better than fixed shading.

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A Non-Invasive Sensing System for Decoding Occupancy Behaviors Affecting Building Energy Performance

Computing in Civil Engineering 2015 ◽

10.1061/9780784479247.033 ◽

2015 ◽

Cited By ~ 2

Author(s):

Triana S. Carmenate ◽

Diana Leante ◽

Sebastian A. Zanlongo ◽

Leonardo Bobadilla ◽

Ali Mostafavi

Keyword(s):

Building Energy ◽

Energy Performance ◽

Building Energy Performance ◽

Non Invasive ◽

Sensing System

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Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽

10.3390/en14030749 ◽

2021 ◽

Vol 14 (3) ◽

pp. 749

Author(s):

John H. Scofield ◽

Susannah Brodnitz ◽

Jakob Cornell ◽

Tian Liang ◽

Thomas Scofield

Keyword(s):

Greenhouse Gas ◽

Energy Use ◽

Energy Savings ◽

Electric Energy ◽

Building Energy ◽

Energy Performance ◽

Office Buildings ◽

Ghg Emission ◽

Site Energy ◽

New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

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