With the transition to a more sustainable, distributed, and 'smart' energy system, local energy grids are undergoing significant changes. One of the primary challenges for these local grids is maintaining grid stability, which requires constant balancing of supply and demand. Because local grids were not designed for distributed energy generation and large loads such as electric vehicle charging, their limited capacity is now leading to congestion. In this dissertation we present our research on supply-demand matching mechanisms for fair congestion management. The local networks populated by users can be represented by radial multi-agent commodity flow systems.
We find that notions of fairness regarding congested commodity flow networks can either focus on local or global fairness. We find that the mix of producers and consumers requires slight adaptation of notions of fairness, with agents envying one group while welcoming the other. Furthermore, we find that it is possible to combine notions of fairness with welfare optimization by letting individual agents decide which of the two is more important, and protecting their fair shares.
Promotor: prof. dr. ir. Han La Poutré (CWI/Delft University of Technology)
