An evolving energy landscape
As the energy landscape evolves, the modern grid is becoming increasingly complex. Legacy assets must interact with rapidly growing renewable generation, electrification is driving new and unpredictable load patterns, and distributed systems require faster, more automated decision-making. To deliver safe, stable and affordable energy, operators need real-time intelligence that provides visibility, foresight and explainable insights across the entire system.
Key Challenges in the Energy Sector
- Increasing renewable generation, creating uncertainty and operational risk.
- Changing load from electrification and EV uptake, pushing assets towards new peaks and congestion.
- Distributed and dynamic network behaviour that demands faster insights at LV and MV levels.
- Limited visibility across large asset portfolios, including secondary substations and customer-side activity.
- Pressure to reduce losses, improve reliability, and support net-zero commitments.
- Regulatory expectations for transparency, auditability and explainable decision-making.
Core Capabilities for Energy & Utilities
Real-Time Forecasting – renewable generation, network load, voltage and fault risk can all be anticipated and mitigated before it affects operations.
Explainable Anomaly Detection – identify unusual behaviour across assets, feeders, substations and customer-side loads to enable engineers to focus on the higher risk issues.
Soft Sensors – improve responsiveness by inferring network parameters in real time, through our AI-based virtual instrumentation.
Causal understanding – understand the relationships between factors driving consumption, network faults, losses, overloads or power-quality issues.
Scenario & What-If Modelling – support capacity planning, flexibility evaluation, reinforcement deferral and operational optimisation for systems evolving in real time.
Edge & Hybrid Deployment – deploy alongside SCADA, telemetry and substation data for real-time local intelligence enabling secure by design solutions in air gapped networks.
Integration with Control Systems – connect with DERMS, ADMS, EMS, flexibility platforms and automation systems for closed-loop response.
How Reliable Insights Helps
Reliable Insights provides real-time, explainable AI that informs and strengthens operational decision-making across generation, distribution and large-scale consumption. Our deterministic approach creates reliable and highly accurate models in seconds, enabling near-real-time forecasts, anomaly alerts, causal understanding and virtual measurements, at scale, without scaling up your data-science team.
This allows control engineers, planners and asset managers to act with confidence, reduce uncertainty and optimise their networks in real time.
Use Cases
Use Case: Robust forecasts
Forecasting on Secure Networks
Short-term demand forecasting for grid-level assets operating in disconnected or constrained environments.
Use Case: Industry forecasts
Kiln gas usage forecasts
Prediction of kiln and furnace gas consumption based on prevailing conditions and use patterns.
Use Case: Network resilience
Real time network constraints
Estimating voltage, load, temperature or quality parameters where sensors are unreliable, missing or cost-prohibitive.