Orchestrator
Orchestrator
Chain of Debate Architecture
// Agent Communication Protocol in AI Foundry
{
"message_type": "debate_proposal",
"from": "trader_agent",
"to": ["risk_governor", "asset_manager"],
"proposal": {
"action": "SELL",
"volume_mwh": 8.5,
"price_eur": 65,
"confidence": 0.92
},
"requires_consensus": true,
"timeout_ms": 1000
}
Multi-scale temporal pattern identification across daily, weekly, and monthly cycles
Real-time energy price patterns showing daily peaks, weekly cycles, and seasonal trends
Seasonal-Trend decomposition captures evolving seasonal patterns with 0.92 R² accuracy
FFT identifies 24h, 168h, and 8760h dominant frequencies in energy pricing
Multi-resolution analysis detects irregular seasonal changes and price volatility
Weather data, currency rates, and renewable generation forecasts
Temperature: 0.89 correlation
Wind Speed: Multi-height sampling
Solar Irradiance: 950 W/m² forecast
EUR/USD: Cross-border trading
VECM Models: Cointegration analysis
Lag Structure: 1-48 hour optimization
Supply/Demand: Grid balance
Outages: Plant availability
Transmission: Congestion pricing
Dynamic Weighting: Factor importance
Temporal Patterns: Time-varying impact
Feature Selection: Automated relevance
Comprehensive comparison across accuracy, interpretability, and computational requirements
Best for: Linear patterns, interpretability, confidence intervals
Best for: Non-linear patterns, multivariate inputs, maximum accuracy
Best for: Production systems, optimal accuracy, robust performance
Statistical rigor for risk-aware algorithmic trading
95% confidence intervals (blue band) with prediction line (orange) for automated trading decisions
2.0σ confidence level triggers position entry with dynamic volatility adjustment
VaR constraints and circuit breakers at 5× historical volatility
Kelly criterion with uncertainty discounts based on interval width
Manages agent initialization, scaling, and termination across the distributed system
Handles inter-agent communication and chain of debate consensus protocols
Enforces business rules, compliance checks, and risk management policies
Ingests real-time meteorological data from multiple sources and generates renewable energy production forecasts
Runs advanced time-series forecasting models (LSTM, ARIMA) for energy price prediction and market analysis
Executes buy/sell decisions based on market opportunities identified through multi-agent consensus
Monitors all trading activities to ensure compliance with risk limits, regulations, and contract obligations
Tracks battery health, charge cycles, warranty constraints, and optimal asset utilization strategies
Unified Data Platform for End-to-End Analytics
Raw data ingestion from market feeds, weather APIs, asset sensors, and historical trading records
Cleaned, validated, and transformed data with standardized schemas and business rules applied
Analytics-ready datasets optimized for ML training, real-time inference, and business intelligence