AI Compliance in Energy

Module 1: Introduction to AI & Regulatory Landscape in Energy

• Define the scope of AI in power systems, utilities, and grid operations
• Analyze examples of AI use in generation, distribution, demand response, and DERs
• Examine the global regulatory landscape, including the EU AI Act and national AI regulations

Module 2: Standards & Governance Frameworks

• Implement ISO/IEC 42001 for AI management in utilities
• Develop data governance principles for energy AI systems
• Build trustworthy AI models using explainability, fairness, and transparency principles

Module 3: Smart Grid Stability & AI Model Assurance

• Forecast energy demand using AI-driven models
• Develop explainable AI models for grid operations
• Ensure AI lifecycle compliance using MLOps best practices

Module 4: Carbon Accounting & AI

• Automate GHG tracking and reporting using AI
• Design AI models for emissions forecasting
• Integrate ISO 14064-2 for measuring and verifying AI-enabled emissions reductions

Module 5: Cybersecurity & Critical Infrastructure Protection

• Implement NERC CIP controls for critical infrastructure
• Develop AI models for anomaly and intrusion detection
• Identify AI-specific cyber-physical risks

Module 6: AI in Energy Markets – Fairness, Bias & Collusion

• Detect collusion and ensure market fairness using AI
• Develop transparent market algorithms
• Prevent anti-competitive behavior using AI

Module 7: Resilience & Incident Management for AI Systems

• Develop incident response plans for AI failures and cybersecurity breaches
• Ensure AI-enabled DERMS and grid resilience
• Establish a legal and liability framework for AI-driven decisions