Adaptive Game-based Agent Negotiation in Deregulated Energy Markets

In the emerging deregulated energy paradigm enabled by the Smart Grid, energy provisioning will change drastically. Energy contracts will be negotiated between a potential multitude of parties at high frequency (e.g., several times per day) based on local needs and micro-generation production facilities. In this context, this paper presents an agent-based approach to manage negotiation among the different parties. The goal of the presented work is to propose adaptive negotiation strategies for trading energy in a deregulated market. In particular, we provide strategies derived from game theory, in order to optimize energy production and supply costs by means of negotiation and adaptation. The novelty lies in the adaptation of the class of minority and stochastic games to the energy trading problem in order to model the strategy of the various parties involved. The paper presents also simulation results of a scenario with a large number of energy buyers, a small set of prosumers (energy consumers and producers using renewable micro-generation facilities) and a few large-scale traditional electricity suppliers.