The increasing importance of renewable energy in mitigating climate change has led to a critical examination of electricity market mechanisms that can support this transition. Virtual bidding, a financial tool used within electricity markets, allows market participants to capitalize on discrepancies between the Day-Ahead (DA) and Real-Time (RT) prices of electricity. The introduction of virtual bidding within electricity markets has introduced significant changes in market dynamics, with implications for environmental outcomes. It supports the transition towards a greener energy mix by favoring the dispatch of renewable resources and contributing to more efficient market conditions.This proposal seeks to explore the impact of virtual bidding and the development of green virtual bidding strategies by leveraging advanced machine learning models.