Energy cost-reduction projects implemented on complex industrial systems present several challenges. The involvement of multiple project stakeholders associated with programmes such as demand side management (DSM) further increases potential risks. The process of determining project impacts is especially important due to the direct financial impact on stakeholders. A good understanding of the independent measurement and verification (M&V) process is therefore vital to ensure an unbiased process. A review of existing M&V frameworks and guidelines found that M&V protocols and templates are well developed and widely implemented. Unfortunately, the official literature provides little guidance on the practical M&V of industrial DSM projects. This prompted a detailed literature analysis of numerous publications to ascertain the industry norm. The diverse results obtained are categorised, normalised and graphically presented to highlight shortcomings in present M&V processes. This thesis develops several practical methodologies and guidelines to address the needs highlighted by the literature analysis. Three chapters are dedicated to the development and verification of these solutions. The first entails the evaluation of data quality with the aim of producing an accurate and error-free dataset. The second develops, evaluates and ultimately selects a baseline model representative of normal system operations. The final chapter presents project performance and uses existing methods to monitor system changes and project performance over the long term. The new methodologies are designed to simplify the practical implementation of different processes. Results are graphically presented thereby enabling quick and intuitive evaluation whilst adhering to present M&V requirements. This makes the M&V process accessible to all stakeholders and enables the transparent development and improvement of all processes. The practical application of the new methodologies is verified by using 25 industrial case studies. The results obtained are validated using data obtained from independent third parties. This proves the functionality of the methodologies and highlights trends that can be evaluated in future studies. The new methodologies improve the accuracy and efficiency of the evaluation process. The potential annual impacts amount to R27 million for DSM stakeholders and R19 million for M&V teams. The extrapolation of these results indicates a massive potential impact on international projects. These results, albeit estimates, confirm the significant contribution of the new methodologies. I would like to officially thank Prof. Eddie Mathews and Prof. Marius Kleingeld for granting me the opportunity to work under their guidance. Thanks to all the staff at the Centre for Research and Continued Engineering Development Pretoria, who created the ideal environment for working and learning. I would also like to thank TEMM International (Pty) Ltd for the bursary without which my studies would not be possible. Finally, I would like to thank my fellow students as well as all the industry professionals whom I had the privilege of working with. On a personal note, I would like to thank God for making all things possible. Thank you my dearest family, friends and all who had a profound impact on my life. For you I quote Paulo Coelho’s Alchemist: “And, when you want something, all the universe conspires in helping you to achieve it.”. Thank you for your love, sacrifice, support and being part of my universe. I dedicate this work to you. / PhD (Electrical Engineering), North-West University, Potchefstroom Campus, 2014

Energy cost-reduction projects implemented on complex industrial systems present several challenges. The involvement of multiple project stakeholders associated with programmes such as demand side management (DSM) further increases potential risks. The process of determining project impacts is especially important due to the direct financial impact on stakeholders. A good understanding of the independent measurement and verification (M&V) process is therefore vital to ensure an unbiased process. A review of existing M&V frameworks and guidelines found that M&V protocols and templates are well developed and widely implemented. Unfortunately, the official literature provides little guidance on the practical M&V of industrial DSM projects. This prompted a detailed literature analysis of numerous publications to ascertain the industry norm. The diverse results obtained are categorised, normalised and graphically presented to highlight shortcomings in present M&V processes. This thesis develops several practical methodologies and guidelines to address the needs highlighted by the literature analysis. Three chapters are dedicated to the development and verification of these solutions. The first entails the evaluation of data quality with the aim of producing an accurate and error-free dataset. The second develops, evaluates and ultimately selects a baseline model representative of normal system operations. The final chapter presents project performance and uses existing methods to monitor system changes and project performance over the long term. The new methodologies are designed to simplify the practical implementation of different processes. Results are graphically presented thereby enabling quick and intuitive evaluation whilst adhering to present M&V requirements. This makes the M&V process accessible to all stakeholders and enables the transparent development and improvement of all processes. The practical application of the new methodologies is verified by using 25 industrial case studies. The results obtained are validated using data obtained from independent third parties. This proves the functionality of the methodologies and highlights trends that can be evaluated in future studies. The new methodologies improve the accuracy and efficiency of the evaluation process. The potential annual impacts amount to R27 million for DSM stakeholders and R19 million for M&V teams. The extrapolation of these results indicates a massive potential impact on international projects. These results, albeit estimates, confirm the significant contribution of the new methodologies. I would like to officially thank Prof. Eddie Mathews and Prof. Marius Kleingeld for granting me the opportunity to work under their guidance. Thanks to all the staff at the Centre for Research and Continued Engineering Development Pretoria, who created the ideal environment for working and learning. I would also like to thank TEMM International (Pty) Ltd for the bursary without which my studies would not be possible. Finally, I would like to thank my fellow students as well as all the industry professionals whom I had the privilege of working with. On a personal note, I would like to thank God for making all things possible. Thank you my dearest family, friends and all who had a profound impact on my life. For you I quote Paulo Coelho’s Alchemist: “And, when you want something, all the universe conspires in helping you to achieve it.”. Thank you for your love, sacrifice, support and being part of my universe. I dedicate this work to you. / PhD (Electrical Engineering), North-West University, Potchefstroom Campus, 2014