Applicable models for upscaling of smart local energy systems: An overview

As the transition towards a net-zero gains momentum, smart local energy systems (SLES) will play a key role in delivering clean and sustainable energy in various forms of usage such as heat, electricity, and transportation, to communities where these projects are implemented. Successful SLES have previously shown a combination of cutting-edge engineering technology, as well as social and economic factors coming into play to achieve a set goal. The interdependencies between these contributing factors illustrates the multi-attribute nature of SLES. This article highlights how insightful models can be in upscaling SLESs. The models considered were categorized according to their modes of application, and instances where they have been used for modelling a multi-energy system upscale. Multi-criteria analysis was used to rank these models according to their ability to represent SLES. Four major aspects of upscaling (growth, replication, accumulation, and transformation) were used to weight the criteria using the entropy method and CRITIC method, respectively. The TOPSIS method was used to rank the models and the result indicated that among 21 models considered, the hybrid combination of an optimization model, a weighting model, and a multi-criteria decision model was the closest to the ideal solution.