Price-Taker Self- Scheduling Using Stochastic Programming

In this paper, self-scheduling issue of a power producer in aincomplete competitive market is adressed using stochastic programming where a Price-taker producer has been considered. So, it does not have the ability to affect the market power and the self-scheduling is solely done through price prediction. Differentuncertainties have been consideredas:price uncertainties, forced outage of unit as well as generation reallocation. The CVaR index has beenused for modeling of risk. The objective markets in this study are bilateral contract, day ahead energy market, ancillary services include spinning reserve and regulation, and spot market decisions. Here, an innovative method for bilateral contracts has been proposed to increase the profit of market without ignoring any regulatory rules. The Monte Carlo method is implemented to generate enough number of scenarios, and an innovative method is presented toreduce the number of scenarios

Keywords:

self-scheduling , scenario generation , scenario reduction , scenario regeneration , stochastic programming