We consider network flow congestion management modelled after electricity distribution networks. The desired consumption or production of the agents that populate such networks are determined by a higher-level (e.g. national) market mechanism, but this can lead to congestion locally. We first consider congestion solutions in the form of curtailment independent of the price set by the higher-level market. Congestion solutions of this type that satisfy properties of fairness are described in the literature. We contrast these fair solutions with curtailment solutions that maximize total welfare, and we present an algorithmic mechanism that computes such maximal welfare solutions. We then combine the two approaches to compute hybrid congestion solutions where agents can choose to either claim their fair share or to participate in a welfare-maximizing aftermarket. We incentivize aftermarket participation with an individually rational pricing scheme, while offering agents' fair shares at the higher-level price. Our aftermarket solution provides a budget balanced alternative to locational marginal pricing that gives agents the choice to claim their fair share at a fair price.

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doi.org/10.1145/3538637.3538843
Thirteenth ACM International Conference on Future Energy Systems
Intelligent and autonomous systems

Hekkelman, B., & La Poutré, H. (2022). Fairness vs welfare: a hybrid congestion aftermarket. In e-Energy '22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems (pp. 93–104). doi:10.1145/3538637.3538843