Construction and Application of Optimisation Model for Multi-Object Coordinated Scheduling of Microgrids by Integrating Deep Learning and Game Theory

Key Points

• This research aims to develop a model that improves the scheduling of microgrids by using deep learning and game theory.
• Developed an optimisation model combining deep learning techniques and game theory principles.
• Applied the model to multi-objective scheduling tasks involving microgrids.
• Evaluated the model's effectiveness in real-world scenarios.
• The optimisation model significantly improved the scheduling efficiency of microgrids.
• Achieved better resource allocation and coordination among multiple microgrids.