In evolving electricity markets, wind power producers (WPPs) would increase their profit through strategic bidding. However, generated power by WPPs is highly random, which may result into heavy imbalance charges. In markets dominated by wind generators, they would optimize their offered bids, considering rival behavior. In oligopolistic day-ahead electricity markets, this strategic behavior can be represented as a Stochastic Cournot model. Wind uncertainty is represented by scenarios generated using Auto Regressive Moving Average (ARMA) model. With a consideration of wind power uncertainty and imbalance charges, strategic WPPs can maximize their expected payoff or profit through the proposed Nash equilibrium based bidding strategy. Nash equilibrium is obtained using payoff matrix approach. Proposed approach is evaluated on two realistic case studies considering different technical constraints. Obtained results shows that proposed bidding strategy mechanism offers quantum increase in profit for WPPs, when their behavior is modeled in a game theoretic framework. Flexibility of approach offers opportunities for its extension to associated challenges. (C) 2014 Elsevier Ltd. All rights reserved.