SEAL-MicroGrid: Steerable LLM-Based Reasoning for Secure Multi-Agent Microgrid Control
Abstract
A novel framework combining steerable LLM reasoning (SEAL) with multi-agent microgrid control systems to enhance security, efficiency, and resilience. The system uses LLM-based agents to detect attacks, optimize power distribution, and coordinate responses while maintaining grid stability through calibrated reasoning paths.
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Research Gap Analysis
Current microgrid control systems lack sophisticated reasoning capabilities for security and optimization, while recent LLM advances haven't been applied to critical infrastructure control. This research bridges that gap by combining steerable LLM reasoning with practical grid control requirements.
SEAL-MicroGrid: Steerable LLM-Based Reasoning for Secure Multi-Agent Microgrid Control
Motivation
Microgrids face increasing cybersecurity threats and operational complexity as they integrate more renewable sources and smart devices. Current control systems struggle to handle sophisticated attacks while maintaining optimal performance. Meanwhile, recent advances in LLM reasoning calibration (SEAL) and multi-agent systems offer promising capabilities for complex decision-making but haven't been applied to microgrid control.
Proposed Approach
The SEAL-MicroGrid framework combines three key innovations:
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Steerable Reasoning Agents: Adapt SEAL's thought-type categorization (execution, reflection, transition) to microgrid control scenarios. Each agent specializes in specific grid functions (power distribution, attack detection, fault response) with calibrated reasoning paths.
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Secure Communication Layer: Implement Agent-in-the-Middle (AiTM) attack detection using LLM-based message verification. Agents validate communication authenticity through contextual analysis and cross-reference historical patterns.
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Hierarchical Control Structure:
- Cloud layer: Long-term optimization and strategy planning
- Edge layer: Real-time response and local control
- Device layer: Direct hardware interface and monitoring
Expected Outcomes
- Reduced attack surface through intelligent message filtering
- 15-30% improvement in response time to grid disturbances
- More efficient resource allocation through optimized reasoning paths
- Enhanced system resilience through coordinated multi-agent responses
Potential Applications
- Smart city power distribution networks
- Industrial microgrids with critical reliability requirements
- Renewable energy integration systems
- Military base power infrastructure
- Remote community power systems
The framework provides a foundation for next-generation secure and intelligent grid control systems that can adapt to emerging threats while maintaining optimal performance.
Proposed Methodology
Implement a three-layer system combining SEAL's reasoning calibration with secure multi-agent control architecture. Use specialized agents for different grid functions, coordinated through a secure communication layer with built-in attack detection.
Potential Impact
Could revolutionize microgrid security and efficiency by enabling intelligent, coordinated responses to attacks and disturbances. Applications in critical infrastructure protection, renewable energy integration, and smart city development.