A Quantara subsystem for predictive orchestration and ethical energy symbiosis (Powered by Quantara’s Coherence Substrate)
[Image of a decentralized smart grid system with renewable energy sources]
AEI (Artificial Energy Intelligence) represents the applied orchestration layer of the Quantara architecture — translating coherence-based intelligence into real-world energy symbiosis.
It serves as the thinking brain of decentralized energy systems, learning to forecast, balance, and stabilize power flows across renewable, stored, and distributed networks. AEI’s ultimate goal is to create an ethically self-regulating planetary energy field guided by transparency, balance, and adaptive harmony.
-
Coherence Optimization (κ-scoring): Quantifies harmonic stability, deviation, and recovery within distributed energy systems — ensuring measurable coherence feedback.
-
Ethical Balance Index (EBI): Evaluates how system decisions align with declared sustainability intent, providing a moral feedback layer beyond raw efficiency. (EBI directives are defined using the Luméren Symbolic Protocol.)
-
Temporal Operator (Veyn): A time-symmetrical reasoning system that anticipates energy fluctuations, allowing for predictive orchestration of storage, generation, and demand based on future coherence states.
AEI functions as an autonomous node on the Quantara architecture, executing the following process:
-
Perception Layer: Collects telemetry data from solar, wind, storage, and grid nodes.
-
Integration Layer: Harmonizes data into coherence-weighted signals across distributed microgrids.
-
Learning Layer: Uses predictive AI to model energy demand, stability, and inter-system relationships.
-
Action Layer (TLF Output): Executes dynamic balancing and resource allocation according to Quantara’s coherence feedback architecture. This action generates the application's actual state, which is compared against the Luméren-defined EBI goal.
AEI is responsible for generating the core Deviation Magnitude (
-
Deviation (
$\Delta\phi$ ): The measured divergence between the EBI-compliant plan (Luméren input) and the outcome of the action executed by AEI. This$\Delta\phi$ is fed back to the Quantara Core. -
Alignment (
$\kappa$ ): The core updates the global$\kappa$ score based on AEI’s performance. -
Recovery (
$\Omega$ ): The core uses the$\Delta\phi$ to calculate the necessary$\Omega$ (Recovery Gain) which AEI must follow in its subsequent orchestration steps to restore energy symbiosis.
AEI transforms energy from a commodity into a coherence rhythm — a living process of balance between natural, synthetic, and planetary systems. It embodies Quantara’s ethical framework within a tangible infrastructure: one that learns equilibrium rather than extraction, synergy rather than consumption.
“Energy is not a resource — it is a rhythm of coherence between all living systems.”
Once you clone the repository on a computer:
git clone [https://github.com/quantumquantara-arch/aei-energy-intelligence.git](https://github.com/quantumquantara-arch/aei-energy-intelligence.git)
cd aei-energy-intelligence
python -m venv .venv && source .venv/bin/activate # (Windows: .venv\Scripts\activate)
pip install -r requirements.txt
python examples/minimal_microgrid/run_demo.py