26th International Association for Management of Technology Conference - IAMOT 2017

Energy modelling is not a new concept and has always been utilised in its most basic form as energy balances. The oil crisis of the 1970’s focused attention to the benefits of energy modelling [1, 2]. Energy modelling application has since become a norm from governmental institutions to industries to policy makers for; analysis and optimisation of current energy systems, forecasting energy demand, assisting in policy analysis development and identifying the interaction and relationships between energy-economy, energy-environment and energy-environment-economy [1]. As energy systems developed from simple to complex, so have the energy models evolved from simple supply and demand models to complex and dynamic multi-criteria models incorporating technological detail, economics and econometrics. Numerous energy models are available, which have been developed by organisations such as government, academia, private enterprises, consultants and energy bodies such as the International Energy Agency and the World Energy Council. Most commonly these models have been classified into two categories; top-down, which are macro-economic models and bottom-up, which are detailed technological models [1, 2, 3]. In recent times a third approach has been utilised, the hybrid approach integrating features of both the bottom-up and top-down models. These models have specific objectives/criteria and specific applications due to the internal model assumptions and structure. A significant number of these models require a high level of expertise, technical detail, economic detail and historical data and are time intensive. These requirements can sometimes encumber the use of the models, as they are not readily available, potentially affecting the accuracy, reliability and evaluation time resulting in additional costs and resources. This paper proposes a review of current toolsets together with a proposed novel business centric approach to energy modelling. The approach maximises on current energy evaluation tools limitations, as analysed in this paper, delivering a dynamic option in energy modelling.