The competition among renewable power producers (RPPs) may cause the cleared power of RPPs to be less than the bidding power

while the impact of competition is neglected in the existing price-taker methods. To overcome the above deficiency

this paper develops an optimal bidding strategy

considering the competition among RPPs. First

a bivariate stochastic optimization (BSO) model for a bidding strategy is proposed by considering the variable power output of RPPs and the competition among RPPs. Particularly

the cleared power estimated by the demand-supply ratio is a random variable in the proposed BSO model. Then

the Newton method and particle swarm optimization (PSO) are combined to solve the BSO model in which various probability distribution functions (PDFs) of renewable energy generation are considered. Finally

the effectiveness of the proposed method is verified based on the results of a case study

which shows that the proposed model performed better than the traditional chance-constrained programming (CCP) model in power market competition.