Spotfire® for Energy & Utilities

Visual data science for energy

Grid load forecasting

As renewable energy comes online, forecasting grid load and generation becomes exponentially more complex due to weather variability and distributed assets.

Spotfire enables visual, real-time exploration of historical consumption, weather data, and generation patterns. Using built-in predictive models and integration with Python/R, operators can forecast demand and renewable supply, identify peak load risks, and simulate “what-if” grid scenarios.

Asset health & maintenance optimization

Utility-scale energy systems, like transformers, turbines, and substations, require proactive maintenance to prevent costly failures. But without a unified view of asset health, maintenance is often reactive or overly scheduled.

With Spotfire, you can visualize and analyze asset health KPIs, failure trends, and service logs. Combine real-time condition analysis (on variables like temperature, vibration, and load cycles) with historical data to optimize maintenance schedules.

Failure prediction & performance optimization

As energy systems grow more complex, especially with distributed renewables and storage, predicting failures and optimizing performance becomes increasingly difficult without advanced analytics.

Use Spotfire to fuse time-series data, operational metrics, and external factors (such as weather or load demand) to detect anomalies, forecast degradation, and optimize performance. Run simulations and AI models to test corrective actions before implementing them.