Energy Distribution Optimisation
Overview
This service provides AI-assisted optimisation for low-voltage electricity distribution networks. With increasing variability from rooftop solar, EV charging, and heat pumps, voltages can drift outside safe limits, reducing power quality and stressing equipment. The service delivers adaptive voltage-control policies that help operators mitigate over- and under-voltage events while respecting operational constraints. Voltage regulation is implemented as a reinforcement-learning control pipeline. Grid telemetry and derived features (e.g., node voltages, power injections, device states) form the state; controllable assets (e.g., inverter reactive power setpoints, tap-changer settings, flexible-load adjustments) form the actions; and constraint-aware reward functions penalise voltage violations, losses, and unnecessary control effort. Training and validation are performed in time-series power-flow simulation and transferred to operational settings via robust evaluation, scenario randomisation, and benchmarking against rule-based baselines.
Outcome
Clients receive a deployable controller or decision-support module that reduces voltage violations across diverse scenarios, alongside monitoring hooks, safety guardrails, and fallback logic. Deliverables include performance reports, configuration for local grid conditions, and a maintenance pathway for updates as grid behaviour evolves.
Service Card
| Category | AI products |
| Domain | Energy, Smart Grids |
| Vertical | Green Transition |
| Target users | Energy Utilities, Grid Operators |
| Service type | Pipeline |
| Outputs | Guidelines, toolkit, models. |
| Requirements | A laptop computer, possibly with GPU. |
| Limitations | |
| Availability | Q3/2027 |
| Licensing | |
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