The emerging electricity market behaves more like an oligopoly than a perfectly competitive market due to special features such as, a limited number of producers, large investment size (barrier to entry), transmission constraints, and transmission losses which discourage purchase from distant suppliers. This makes it practicable for only a few independent power suppliers to service a given geographic region and in this imperfect market each power supplier can increase its own profit through strategic bidding. The profit of each supplier is influenced to varying extents by differences in the degree of imperfection of knowledge of rival suppliers. A new framework to build bidding strategies for power suppliers in an electricity market is presented in this paper. It is assumed that each supplier bids a linear supply function, and that the system is dispatched to minimize customer payments. Each supplier chooses the coefficients in the linear supply function to maximize benefits, subject to expectations about how rival suppliers will bid. A

A new approach to designing bilateral power transaction bargaining models between two independent utilities in a deregulated electricity market is proposed. In the paper it is assumed that each utility (a seller or a buyer) knows its own operating costs but does not know those of its opponent. The bilateral power transaction problem is then considered as nonco-operative bargaining under incomplete information. Each participant develops its own bargaining strategy based on estimates of the opponent's operating costs and bargaining strategy. Two bargaining models are developed and examples are employed for demonstration.

The new electricity market behaves more like an oligopoly than a laissez-faire market due to special features such as, a limited number of producers, large investment size (barrier to entry), transmission constraints and transmission losses which discourage purchase from distant suppliers. This makes it possible for only a few generating companies to service a given geographic region. In an imperfect market each power supplier can increase its own profit through strategic bidding. The problem of building optimally co-ordinated bidding strategies for competitive suppliers in energy and spinning reserve markets is addressed. Each supplier bids a linear energy supply function and a linear spinning reserve supply function to the energy and spinning reserve markets, respectively, and the two markets are dispatched separately to minimise customer payments. Each supplier chooses the coefficients in the linear energy and spinning reserve supply functions to maximise total benefits, subject to expectations about how rival suppliers will bid. A stochastic optimisation model is first developed to describe this problem and a genetic algorithm based method is then presented to solve it. A numerical example is utilised to illustrate the essential features of the method.

A method to predict the optimal energy production of a profit maximizing power producer in an oligopoly electricity market is presented. The cases where producers have incomplete information about the operating costs of rival producers are highlighted. Cournot noncooperative game theory is used to determine the oligopoly electricity market equilibrium state that corresponds to the optimal supply quantity of each power producer.

stochastic optimization formulation is developed and two methods proposed for describing and solving this problem. A numerical example serves to illustrate the essential features of the approach and the results are used to investigate the potential market power.