Résumé
Renewable energy mix systems (RES) are crucial for sustainable energy transitions, but their integration with power grids poses technical, economic, and regulatory challenges. This paper addresses the critical challenges and methodologies associated with modeling RES integrated with power grids, essential for the global transition to sustainable energy. It examines the complexities of integrating variable renewable sources like wind and solar, highlighting technical, financial, environmental, and regulatory barriers through a comprehensive literature review. To overcome these obstacles, a decision centric framework is proposed, utilizing a Global Information System (GIS) based approach to optimize site selection, energy mix, and grid stability. This framework employs machine learning for enhanced grid feasibility assessments along with contingency analysis, incorporating predictive maintenance and demand supply balancing, alongside detailed simulations using tools like DigSILENT PowerFactory and Any-Logic. The methodology culminates in a decisional model that balances technical, economic, and environmental factors, ensuring the development of robust and efficient renewable energy systems.