Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches

About 75% of the world's energy consumption takes place in cities. Although their large energy consumption attracts a large number of research projects, only a small fraction of them deal with approaches to model energy systems of city districts. These are particularly complex due to the existence of multiple energy sectors (multi-energy systems, MES), different consumption sectors (mixed-use), and different stakeholders who have many different interests. This contribution is a review of the characteristics of energy system models and existing modeling tools. It evaluates current studies and identifies typical characteristics of models designed to optimize MES in mixed-use districts. These models operate at a temporal resolution of at least 1 h, follow either bottom-up or hybrid analytical approaches and make use of mixed-integer programming, linear or dynamic. These characteristics were then used to analyze minimum requirements for existing modeling tools. Thirteen of 145 tools included in the study turned out to be suitable for optimizing MES in mixed-use districts. Other tools where either created for other fields of application (12), do not include any methodology of optimization (39), are not suitable to cover city districts as a geographical domain (44), do not include enough energy or demand sectors (20), or operate at a too coarse temporal resolution (17). If additional requirements are imposed, e.g. the applicability of non-financial assessment criteria and open source availability, only two tools remain. Overall it can be stated that there are very few modeling tools suitable for the optimization of MES in mixed-use districts. •A broad overview of the properties of energy system models.•The characterization of models designed to optimize energy systems in urban districts.•A comparison of 145 different energy system modeling frameworks and generators.•13 tools are suitable for the optimization of multi-energy systems in mixed-use districts.•Two of these 13 tools fulfilled optional needs, such as open source availability.