Classification and aggregation of energy components

The 21^st century society is in the middle of a massive energy transition with climate mitigation being at the center of all concerns. Renewable power production is on the rise for several years, supported by political and economic incentives in order to cut on CO2 emissions and support this energy transition. Power producers are therefore adding more and more renewable energy technologies to their portfolio while centralized fossil-fuel based power plants are being phased out. This has resulted in the popularisation of distributed energy resources (DER's) which are modular and more flexible technologies located directly on the consumer end (decentralized). This development has introduced significant variability and lack of predictability in power systems which as consequence have increased the requirement for system flexibility. Hence, it is important to couple various energy system infrastructures and networks (e.g. electricity, gas and heat) that are highly interconnected and compose the total energy system. These are found to be operated independently while, having a better understanding of their synergies could be a valuable knowledge to complete the energy transition. The core research question that this PhD study will address is: How to perform aggregation in a multi-carrier energy system environment where components use for flexibility are subject to conflict of interest constrained by more than one system? System level aggregation concepts in a fully integrated energy system to ensure security of supply while avoiding congestion in a cost-effective manner with a particular focus on control will be studies. This research will eventually result in methods for classification and aggregation of components, including the network and associated constraints, and express the technologies at more generic, statistical and scalable levels.