Nash strategies for load serving entities in dynamic energy multi-markets

In this paper the problem of developing bidding strategies for the participants of dynamic energy-multi markets is studied. Attention is given to strategic bidding of load serving entities (LSE) in these markets. We model energy multi-markets as non-linear dynamical systems and use discrete-time Nash bidding strategies. Attention is given to a problem, where the objective functions are quadratic in the deviations of trajectories from desired trajectories and quadratic in the control deviations from the nominal controls. It is assumed that each power marketer can estimate his/her competitors' benefit functions and their minimum and maximum values. The optimal bidding strategies are developed mathematically using dynamic game theory. We deal with games that are non-linear in the state equations. We linearize these equations for complex non-linear energy multi-markets and use discrete-time Nash strategies. We show that the actual dynamic excursions from the operating point where we linearize are small so that the linearization is valid. The developed algorithm is applied to an IEEE 14-bus power system for two cases: (1) No transmission capacity constraints, (2) Transmission capacity limit constraints on two groups of transmission lines. We show that the LSEs' expected profits are higher for our method than those for other methods in the literature.