Measurement and verification (M&V) is fundamental in determining the impact of energy efficiency (EE) interventions. However, accurately quantifying the EE savings on complex industrial systems can present several technical challenges. It is of critical importance that these challenges be practically addressed within regulatory requirements when applying for tax-based EE incentives. In this study, the key uncertainties affecting the M&V of Section 12L EE tax incentive applications are identified. A novel approach provides practical guidelines to manage and mitigate uncertainty. This approach ensures that reported savings are a fair and compliant reflection of the actual savings achieved. The presented case studies show that uncertainty can affect up to 30 per cent of reported savings. This emphasises the significant impact of uncertainty, and quantifies the benefit of compliant uncertainty management. Ultimately, this study provides valuable insight into the practical implementation of tax-based directives intended to stimulate sustainable development. OPSOMMINGMeet en verifieer (M&V) is fundamenteel om impak van energiedoeltreffendheid intervensies te bepaal. Die akkurate kwantifisering van die energie besparings op komplekse industriële stelsels kan egter verskeie tegniese uitdagings bied. Dit is van kritieke belang dat hierdie uitdagings prakties aangespreek word binne regulatoriese vereistes van belasting gebaseerde aansporingsprogramme. In hierdie studie word die kern onsekerhede geïdentifiseer wat die Seksie 12L belasting aansporingprogram beïnvloed. 'n Nuwe benadering wat gebaseer is op praktiese riglyne word voorgestel om hierdie onsekerhede te bestuur. Die benadering verseker dat gerapporteerde besparings 'n regverdige weerspieëling weergee van die werklike besparings wat behaal word. Die implementering van die benadering op vier gevallestudies toon dat onsekerheid tot 30 persent van gerapporteerde besparings kan beïnvloed. Dit beklemtoon die beduidende impak van onsekerheid en motiveer dus die belangrike rol van onsekerheidsbestuur. Hierdie studie bied waardevolle insig tot die praktiese implementering van belasting gebaseerde programme wat daarop gemik is om volhoubare ontwikkeling te stimuleer. 1BACKGROUND AND RELEVANCE The 12L tax incentiveThe South African government has committed itself to a 32 per cent reduction in greenhouse gas (GHG) emissions by 2020 and to a 42 per cent reduction by 2025 [1]. This is part of a global effort to address the threat of anthropic climate change in the context of sustainable development [2]. 129The focus of climate change mitigation is on implementing laws, policies, and regulations that promote sustainable development. Good M&V practice will therefore play a key role in the practical application of the 12L tax incentive. Role of M&V in 12L tax incentive applicationsEnergy saving measures (ESMs) include a wide range of activities dedicated to improving EE and decreasing GHG emissions. However, several challenges arise when administrating the actual benefits...
Internationally, innovation and technology are driving change through concepts such as 'Industry 4.0'. However, due to various constraints, South Africa is lagging behind in this transformation. Furthermore, local industry generates large amounts of data that could contribute to a positive transformation. Data analytics, in the form of reporting, may therefore present a workable alternative to understand better the intricate nature of real-world operations. This paper identifies four qualities for the practical application of data analytics, with the aim of intelligent reporting. The four qualities are focus area, data availability, analytics, and visualisation. Research on each quality shows that they have various levels. A comprehensive literature review supports these findings. Forty studies are included that were selected through a process of relevant research criteria. A case study is presented to show how the four qualities contribute to the development of intelligent reports as an objective representation of industry performance.
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