NEST - Deterministic Pre-Consequence Control for Energy and Carbon Reduction

Recibidas : Estas son todas las innovaciones que Team for the Planet ha recibido a través de su formulario de presentación de innovaciones

NEST is a deterministic pre-consequence control and validation architecture designed to reduce avoidable energy use, carbon emissions, operational instability, and system-wide inefficiency before these consequences occur. It retrofits around existing infrastructure, evaluating proposed operational actions before execution to ensure they are admissible within defined energy, carbon, reliability, safety, cost, and operational boundaries. Its key capabilities include pre-consequence control, whole-flow coherence, multiple intervention states, and signed evidence/replay.

El sector empresarial
Energy
Descubra nuestro campo de acción arrow_forward
Fecha de presentación 22 de julio de 2026 Urbanización Limassol, Chipre

El proyecto en detalle

Nota: este formulario debe ser cumplimentado en su totalidad por las personas que proponen la innovación.

¿Qué problema se ha resuelto?

Modern energy systems, controlled by complex automation and AI, can generate individually valid actions that lead to undesirable wider consequences (e.g., increased emissions, instability, inefficiency). Conventional systems detect these issues only after they occur.

¿Cómo se resuelve?

NEST integrates with existing control systems (EMS, BMS, ICS, AI controllers, etc.) and evaluates proposed actions before they are executed. It determines admissibility based on energy, carbon, reliability, safety, and cost constraints, then either allows, routes, repairs, holds, quarantines, or denies the action. It provides signed evidence for each decision.

¿En qué se diferencia esta solución?

Deterministic pre-consequence control, whole-flow coherence, multiple controlled intervention states, retrofit compatibility, signed consequence evidence, and acting before consequences occur, unlike conventional systems that react post-event. It provides a validation layer for AI and automated decisions.