Services Catalogue

The Real-Time Energy Anomaly & Waste Intelligence service equips the Municipality of Athens with a continuous, automated intelligence layer for detecting abnormal electricity consumption behaviour and quantifying energy waste across its public building portfolio. Rather than waiting for anomalies to surface through quarterly bill reviews, the service identifies deviations from expected consumption as they emerge in the live meter feed, ranks them by financial impact, and presents building operators with a prioritised action queue. The service builds an evolving waste register that supports both operational decision-making and strategic reporting on energy efficiency progress.

The Real-Time Power Management for TSO-DSO Operations service uses an integrated TSO-DSO network model to analyse how planned or simulated flexibility activations (particularly BESS) influence voltages, power flows, and disturbance propagation across the grid boundary. The service supports better coordination between transmission and distribution operators by helping both sides assess risks earlier and develop more coordinated power management strategies.

The ML-Based Outage Root Cause Identification service uses machine learning to identify patterns in large volumes of SCADA event logs and relate ongoing outage events to previously resolved incidents. By comparing current event sequences with historical incidents, the service returns the most similar past cases with their likely root causes, supporting faster interpretation of outage situations and more consistent disturbance assessment by distribution system operators.

The Dynamic AI-Enhanced Transmission Grid Stability Assessment service delivers data-driven analytical capabilities for assessing the stability of power transmission systems based on instantaneous grid state snapshots. Unlike conventional simulation-based approaches, the service uses similarity-based analytics to retrieve historically or synthetically observed grid states resembling the current operating condition, providing probabilistic and evidence-based insights into potential disturbances and transient instability risks.

This service focuses on the interpretation and advanced analysis of disturbance events recorded by protection relays within the transmission power system. Using AI, the service processes and contextualises fault records to support protection system experts in detecting, reviewing, labelling, and classifying fault and non-fault events. By systematically organising protection relay event data, the service provides continuous situational awareness of transmission system conditions and enables consistent event classification across the network.

The Performance Evaluation service quantifies forecasting performance for offshore renewable energy assets by comparing forecasted and measured production. It identifies systematic errors, detects bias, and provides standardised performance metrics to support continuous improvement of forecasting models. The service supports both real-time monitoring and historical back testing of forecast accuracy.

The Fault Classification and Location service detects, classifies, and localises faults in offshore renewable energy assets using real-time telemetry data. The service identifies abnormal behaviour across electrical, mechanical, and operational signals, assigns fault types to predefined categories (voltage anomalies, current imbalances, converter faults, cable faults, sensor issues), and estimates likely fault locations within the asset or subsystem.

This service classifies and manages the operational states of offshore renewable energy assets — normal, derated, and safeguard — using AI-based classification of real-time telemetry and environmental conditions. When enabled, the service can issue control actions via API to adjust asset operation, supporting safe and efficient management that reduces wear and improves asset lifetime.

The Anomaly Detection for Preventive Maintenance service analyses telemetry data from offshore renewable energy assets to detect deviations from expected operational patterns and estimate the likelihood of component degradation or failure. By providing early warning capabilities, the service enables timely maintenance interventions that reduce downtime and extend asset lifetime.

The Wave Power Generation Short-Term Forecasting service delivers AI-enabled short-term forecasts of electrical power generation for offshore wave energy assets, covering horizons from 0 to 48 hours ahead. Using historical generation data, real-time telemetry, and environmental conditions from the Aguçadoura test site in Portugal, the service supports operational planning, grid balancing, and market participation of offshore renewable energy assets.