energy scheduling in power market under stochastic dependence structure

since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. they dispatch their power energy generation units in the uncertain environment of power market. as a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling strategies under uncertainty. however, dependence structure between stochastic variables has been almost ignored in the literature. copula function is a new concept in the probability and statistics field which has the capability to represent the dependence structure among stochastic variables. however, copula function has recently taken into account in power system studies by some articles. in this article, self-scheduling strategy of a generation utility owning thermal units is investigated while the dependence structure among stochastic load and market price variables is taking into account. we assume that the generation utility is a price-taker agent in a power market, and it also has to meet the load of a specific region as a retailer. the results indicates that as the stochastic dependence structure among load and price variables is considered in modeling load and price scenarios, the output of unit commitment problem changes so that the revenue of generation utility increases.