SUNConferences, SAIIE NeXXXt

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Structuring uncertainty management for energy savings calculations
Kristin Johnson, Waldt Hamer, Jan Vosloo

Last modified: 2019-08-29

Abstract


South Africa has committed to reducing its greenhouse gas (GHG) emissions. A key strategy to minimise this GHG intensity involves utilising incentivised energy efficiency initiatives. In South Africa one of these energy efficiency incentives is Section 12L of the Income Tax Act. The section 12L tax incentive rewards claimants 95c/kWh for verified energy efficiency savings (EES) linked to reduction of GHG emissions. This verification is done using the SANS 50010 standard. The SANS 50010 standard requires management and quantification of the uncertainty associated with reported savings. Accurate quantification of EES is therefore critical and highlights the need for uncertainty management to ensure accurate and fair results.

Though uncertainty quantification and management (Q&M) 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 Q&M flowchart was developed for quantifying and managing EES uncertainties. This tool incorporates a five-step approach towards EES quantification and was applied to three industrial energy efficiency case studies. It was found that uncertainty levels can range between 2% and 18% due to varying uncertainty contributors. This highlighted the need for a structured approach to pro-actively identify, quantify and manage uncertainty contributors.