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1. Introduction 2. Overview of Smart Grid Systems 2.1 Definition and Components 2.2 Importance for Modern Energy Supply 2.3 Current Challenges and Limitations 3. Basics of Artificial Intelligence 3.1 Key Concepts and Algorithms 3.2 Applications in Energy Management 3.3 Limitations and Ethical Considerations 4. Integration of AI in Smart Grids 4.1 Potential Benefits and Applications 4.2 Challenges of Integration 4.3 Case Studies of Successful Integration 5. AI Techniques for Enhanced Efficiency 5.1 Machine Learning Algorithms 5.2 Predictive Analytics in Energy Demand 5.3 Autonomous System Control 6. Impact on Energy Efficiency 6.1 Measuring Efficiency Improvements 6.2 Environmental and Economic Benefits 6.3 Future Prospects and Innovations 7. Security and Privacy Concerns 7.1 Threats in AI-Integrated Systems 7.2 Strategies for Enhanced Security 7.3 Privacy Issues and Solutions 8. Conclusion and Future Directions 8.1 Summary of Key Findings 8.2 Recommendations for Stakeholders 8.3 Future Research Opportunities
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