Energy system optimization at the municipal level: An analysis of modeling approaches and challenges

Highlights: • Energy system optimization models support decision making at the municipal level. • Adequate models exhibit approaches which are able to abstract the deployment environment. • Modeling approaches of selected energy system optimization models are analyzed. • Assessment of modeling approaches regarding municipal system characteristics is given. • Future research challenges and initial solutions are outlined. -- Abstract: The development of sustainable system strategies at the municipal level is a challenging task since various factors like the business portfolio, the technological progress, the actor base, the regulatory framework and the market status might influence the results of an assessment. Given the complexity, system interdependencies between different alternatives need to be considered. One possibility to support decision makers is to apply Energy System Optimization Models (ESOMs). This paper reviews selected ESOMs with a high level of modeling detail and thus with high spatial, temporal and contextual resolutions that can be applied to support the decision-making process at municipalities. The main objective is to identify modeling approaches and future challenges to design such systems using several modeling frameworks. First, necessary system elements and interrelations are elaborated based on existing municipal system descriptions. The requirements are included in the derived definition of Integrated Multi-Modal Energy System (IMMES). Second, selected ESOMs are analyzed in terms of the requirements of the system definition. In doing so, existing fundamental approaches are demonstrated. Third, challenges for new mathematical approaches are provided. This review shows that a few modeling approaches are quite prevalent. Future design of models can be directly based on these practices. Additionally, most of the reviewed ESOMs only fulfill certain requirements of IMMES with a more complex approach. Concluding, future ESOMs need to address six research challenges: integrated view, business modeling, spatial planning, complexity level, temporal resolution and uncertainty analysis.