An evolutionary game theory application in a smart grid context

This technical report describes first experiences in applying evolutionary game theory to a case of smart grid coordination. The use of evolutionary game theory to model population dynamics has been e↵ectively used in domains such as biology and economics but applications to cases of smart grid coordination have not been widespread. In this work, we explicitly model a population consisting of clients of demandside flexibility aggregators and demonstrate a proof of concept analysis of the relationship between an aggregator‘s market share, its e ciency and the payment rate toward its self-interested clients. Simulations are used to provide expected payo↵ values as input for the evolutionary game theoretic analysis. Preliminary results show that the payment rate towards clients has a significant influence on the ability to maintain a market share when competing aggregators are present and that evolutionary game theory provides interesting tools for analyzing such cases of strategic interaction between self-interested clients. An evolutionary game theory application in a