Two agent negotiation model for transmission investment based on non-cooperative game theory

Due to network interactions and economies of scale, it is natural for participants to form coalitions to invest in transmission. Cost allocation is a key problem for each part of such coalition, and negotiations have to proceed between each players. Market uncertainties and information asymmetries both complicate the process. This paper proposed an adaptive two-agent negotiation model based on noncooperative game theory. The Bayesian Nash equilibria path is given via backward induction. This result is useful for players to make optimal decision. A simple three-zone system is used to illustrate the validate of our model. Both theoretical results and initial experiments show that learning is beneficial in this sequential negotiation model.