In electricity markets, electric power producers participate in energy and ancillary services markets. These producers may participate as price takers or price makers in the mentioned electricity markets. Price maker producers try to maximize their profits through exercising their market power. As a definition, market power is the ability of a company or set of companies in market price manipulation aimed at achieving more profit. As the marginal cost of a hydroelectric power plant production is negligible, they are able to produce electrical energy at a very lower price comparing to the market clearing price. Hence, they could act as the price setter in a day-ahead electricity energy market . In this thesis, using a stochastic mixed integer linear programming approach, a price maker hydropower plant is modeled and its optimum performance for participating in a day-ahead energy market and also regulation market is analyzed. The impact of the hydropower plant on the market price is investigated using the residual demand curve. In this thesis residual demand curve is determined through an optimization process. Uncertainties related to the residual demand curves, are taken into account through a scenario-based modeling And also the cascading hydropower plants are modeled and analyzed. Finally, using simulation results it is shown that hydropower producers are able to change the market prices via exercising their market power aim to maximizing their profits. In this thesis we have shown that conventional market power indices are not able to identify the hydropower units market power. So, a new index is defined in such a way that hydropower plants market power is identifiable. Key Words: hydropower producers, price maker producers, stochastic mixed integer linear programing, residual demand curve, energy and regulation market
