Agent-based modeling for trading wind power with uncertainty in the day-ahead wholesale electricity markets of single-sided auctions

► Bidding optimization for wind generators in electricity markets is analyzed. ► Agent-based modeling approach is for the first time adopted for this purpose. ► More accurate wind forecasts generate higher earnings for wind generators. ► Increasing wind penetration level can reduce the market clearing price. ► Wind generators can increase earnings by adopting learning algorithms.