STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS

South Africa has committed itself to reducing its greenhouse gas emissions. A key strategy to minimise the greenhouse gas intensity involves using incentivised energy efficiency initiatives. In South Africa, one of these energy efficiency incentives is Section 12L of the Income Tax Act, which reward...

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Main Authors: Johnson, Kristin, Hamer, Waldt, Vosloo, Jan
Format: Article
Language:English
Published: Stellenbosch University 2019-11-01
Series:South African Journal of Industrial Engineering
Subjects:
Online Access:http://sajie.journals.ac.za/pub/article/view/2234
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spelling doaj-c49099e9d2104785bc2aeb57895c56ad2020-11-25T01:27:06ZengStellenbosch UniversitySouth African Journal of Industrial Engineering1012-277X2224-78902019-11-0130314916210.7166/30-3-2234STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONSJohnson, Kristin 0Hamer, Waldt 1Vosloo, Jan 2North-West UniversityNorth-West UniversityNorth-West UniversitySouth Africa has committed itself to reducing its greenhouse gas emissions. A key strategy to minimise the greenhouse gas intensity involves using incentivised energy efficiency initiatives. In South Africa, one of these energy efficiency incentives is Section 12L of the Income Tax Act, which rewards claimants with 95c/kWh for verified energy efficiency savings linked to the reduction of greenhouse gas emissions. This verification is done using the SANS 50010 standard, which requires the management and quantification of the uncertainty associated with reported savings. The accurate quantification of energy efficiency savings is therefore critical, and highlights the need for uncertainty management to ensure accurate and fair results. Although uncertainty quantification and management methods are already available, the correct and consistent application of relevant methods for specific uncertainty contributors is important. In this study, a solution in the form of an uncertainty quantification and management flowchart was developed to quantify and manage energy efficiency savings uncertainties. This tool incorporates a five-step approach towards energy efficiency savings quantification, and was applied to three industrial energy efficiency case studies. It was found that uncertainty levels can range between two and 18 per cent, due to varying uncertainty contributors. This highlighted the need for a structured approach pro-actively to identify, quantify, and manage uncertainty contributors.http://sajie.journals.ac.za/pub/article/view/2234greenhouse gasreduction of greenhouse gas emissions
collection DOAJ
language English
format Article
sources DOAJ
author Johnson, Kristin
Hamer, Waldt
Vosloo, Jan
spellingShingle Johnson, Kristin
Hamer, Waldt
Vosloo, Jan
STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
South African Journal of Industrial Engineering
greenhouse gas
reduction of greenhouse gas emissions
author_facet Johnson, Kristin
Hamer, Waldt
Vosloo, Jan
author_sort Johnson, Kristin
title STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
title_short STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
title_full STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
title_fullStr STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
title_full_unstemmed STRUCTURING UNCERTAINTY MANAGEMENT FOR ENERGY SAVINGS CALCULATIONS
title_sort structuring uncertainty management for energy savings calculations
publisher Stellenbosch University
series South African Journal of Industrial Engineering
issn 1012-277X
2224-7890
publishDate 2019-11-01
description South Africa has committed itself to reducing its greenhouse gas emissions. A key strategy to minimise the greenhouse gas intensity involves using incentivised energy efficiency initiatives. In South Africa, one of these energy efficiency incentives is Section 12L of the Income Tax Act, which rewards claimants with 95c/kWh for verified energy efficiency savings linked to the reduction of greenhouse gas emissions. This verification is done using the SANS 50010 standard, which requires the management and quantification of the uncertainty associated with reported savings. The accurate quantification of energy efficiency savings is therefore critical, and highlights the need for uncertainty management to ensure accurate and fair results. Although uncertainty quantification and management methods are already available, the correct and consistent application of relevant methods for specific uncertainty contributors is important. In this study, a solution in the form of an uncertainty quantification and management flowchart was developed to quantify and manage energy efficiency savings uncertainties. This tool incorporates a five-step approach towards energy efficiency savings quantification, and was applied to three industrial energy efficiency case studies. It was found that uncertainty levels can range between two and 18 per cent, due to varying uncertainty contributors. This highlighted the need for a structured approach pro-actively to identify, quantify, and manage uncertainty contributors.
topic greenhouse gas
reduction of greenhouse gas emissions
url http://sajie.journals.ac.za/pub/article/view/2234
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