A novel stochastic model for the gencos self-scheduling in a restructured electricity market

This paper presents the formulation of a novel stochastic model for the GenCos´ self-scheduling (GSS) problem in a restructured electricity market. The stochastic model is designed for GenCos´ portfolio management utilizing the GSS which is a self scheduling for profit maximization. The proposed model incorporates a probabilistic approach for the evaluation of composite reliability of generation, load forecast and fuel prices using different probability distributions. Different scenarios will be generated from the Monte Carlo simulation. Each scenario is an input to GSS. The results of different GSS runs will be displayed in form of profit/loss probability distribution to analyze the risk in an uncertain power market. This model can be used by GenCos in some restructured markets where GenCos are responsible for self scheduling, to commit and schedule their units for selling power, spinning and non-spinning reserves in order to maximize their own profit and would be interested in determining the risk associated with different scenarios. The proposed model can be used for exploring the arbitrage opportunities between energy and ancillary services.