It is very important to account for the temporal and spatial dependencies of system properties when modelling energy systems.  This is because neither the energy demands nor the availability of primary energy resources (e.g. renewables) are uniformly distributed and constant over time. In order to deploy assets strategically, it is important to understand the impact of different decisions relating to the size and location of different technologies for generation/conversion, storage and transport. Without a model that explicitly accounts for these spatial dependencies, transport of resources cannot be modelled properly and it will not be possible to discriminate between alternative energy provision strategies (e.g. choosing between centralised generation with a large transportation network versus distributed generation with lower transportation costs). Temporal aspects, on the other hand, are necessary to account for the dynamic nature of demands and resource availability and to consider short-term operational issues as well as long-term planning.

However, solving such spatio-temporal models is extremely challenging due to their size and complexity.  Including high spatial and temporal details results in very large models that can be intractable and complexity can arise from the need to model resource transport and storage in detail. Storage of resources is important when considering intermittent availability of resources (e.g. renewables) and in dealing with peaks in demand and the mismatch between energy production and demand for energy services.

In this workshop, we will consider the current state-of-the-art in integrated energy network models that include both spatial and temporal details.  The focus will be on the different modelling techniques and solution procedures that can be used to solve these highly complex models.  We will also discuss the challenges and future directions for spatio-temporal energy systems modelling.