Mixed integer linear programming model for space constrained coupled electricity and heat sectors with generation and network expansion planning

The main point of coupled energy systems modeling is to have as many sectors and systems as feasible, as to incorporate all the possible interactions between them, thus yielding a more accurate representation of reality. This paper presents a lightweight large-scale generation and transmission expansion model that simultaneously incorporates physical space and electric network constraints, heat and power interactions, fuel constraints, renewable constraints based on natural resource, electric demand and different heat demands classified by temperature range. It is modeled as a mixed integer linear problem that yields the best accuracy obtainable from a state of the art linear formulation. The model presented is meant for studies in the transition towards an emission-neutral system, generating an ideal target system configuration or the transition states to reach it. The results of various what-if scenarios enabled a qualitative validation of the model which shows new and optimized system configurations as a result of the interactions between fuel availability, natural resources, different technologies, tax and regulations, load evolution, etc. A comparison with a heuristic clustering method is perform and shows the advantages and shortcomings of these methods. Scalability tests performed on large models show satisfactory results with manageable solving times.