2010
DOI: 10.1002/er.1676
|View full text |Cite
|
Sign up to set email alerts
|

Greenhouse gas emission intensity factors for marginal electricity generation in Canada

Abstract: SUMMARYIn Canada, each province has its own electric utility system, and each system is responsible for meeting the demand of its customer base. Electricity demand in all provinces is highly variable throughout the day, as well as during the year. In order to achieve a good match between electricity demand and generation, a mix of base, intermediate and peaking load power plants is used, which uses different fuel sources. When a renewable energy technology or an energy efficiency measure that results in electr… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
61
0

Year Published

2012
2012
2017
2017

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 51 publications
(64 citation statements)
references
References 2 publications
3
61
0
Order By: Relevance
“…In line with numerous studies regarding energy-system-level implications [29][30][31][32][33][34][35][36][37][38], our results highlight the relevance of marginal system implications. These studies have mainly focused on single measures, short-term implications, or general implications, while our study has focused on municipal planning and municipal energy planning.…”
Section: Discussionsupporting
confidence: 76%
See 2 more Smart Citations
“…In line with numerous studies regarding energy-system-level implications [29][30][31][32][33][34][35][36][37][38], our results highlight the relevance of marginal system implications. These studies have mainly focused on single measures, short-term implications, or general implications, while our study has focused on municipal planning and municipal energy planning.…”
Section: Discussionsupporting
confidence: 76%
“…Studies [29,30] have suggested that by altering the electricity consumption at the system level decreases or increases the regulative/marginal capacity in a similar fashion. Studies [31,32,34] have offered similar findings to the perspective that uses a single measure.…”
Section: Electricity Grid-level System Implicationsmentioning
confidence: 99%
See 1 more Smart Citation
“…CHREM consists of six components that work together to provide predictions of the end-use energy consumption and GHG emission of the CHS. These components are (Swan et al 2008(Swan et al , 2013Swan 2010;Farhat and Ugursal 2010):  The Canadian Single-Detached & Double/Row Housing Database (CSDDRD),  A neural network model of the appliances and lighting (AL) and domestic hot water (DHW) energy consumption of Canadian households,  A set of AL and DHW load profiles representing the usage profiles in Canadian households,  A high-resolution building energy simulation software (ESP-r) that is capable of accurately predicting the energy consumption of each house file in CSDDRD,  A model to estimate GHG emissions from marginal electricity generation in each province of Canada and for each month of the year,  A model to estimate GHG emissions from fossil fuels consumed in households. As shown in Fig.…”
Section: Methodsmentioning
confidence: 97%
“…Though subjective norm might be expected to be significant in determining technology acceptance, based on theory of reasoned action and the theory of planned behavior, there is empirical evidence to support the role of building somewhat mixed (Ajzen, 1985(Ajzen, , 1991. However, most companies can minimise GHG emissions by managing efficiency barriers more appropriately (Farhat & Ugursal, 2010).…”
Section: Attitudesmentioning
confidence: 99%