Helping electric utilities deploy smart grid technologies. By analyzing real-time sensor data (from smart meters and grid devices), we optimize the distribution network. For example, our systems can detect feeder overloads or voltage imbalances and automatically re-route power via smart switches to prevent outages. We integrate weather and demand forecasts to balance load dynamically (e.g., preemptively dispatching stored energy before a heatwave-driven peak). In advanced metering regions, we analyze fine-grained usage data to design demand-response programs (incentivizing customers to cut usage during peaks), which can flatten demand curves and defer new capacity investment.

Applying AI to critical assets (generation turbines, pipelines, grid transformers) to foresee failures. We analyze equipment sensor data (vibrations, pressures, temperatures) to predict issues before they cause outages. For instance, we might forecast when a wind turbine’s gearbox is likely to fail, allowing maintenance teams to service it during a low-wind period. In pipelines, acoustic or pressure sensors can detect leaks faster than manual inspection. By preventing catastrophic failures and unplanned downtime (e.g., pipeline bursts, transformer blowouts), predictive maintenance saves costs and improves safety. We pair these forecasts with optimized scheduling tools so repair crews and spare parts are ready exactly when needed.

Managing the variability of solar and wind power with AI. We build models that predict renewable output (e.g., solar generation based on sky conditions, wind farm output from weather forecasts). Combining these with demand forecasts, utilities can plan when to dispatch backup power or charge storage systems. We also optimize battery/storage usage (charging when excess renewable energy is available, discharging during peaks). By maximizing renewable utilization and minimizing curtailment, these models help stabilize the grid and lower costs. For utilities dealing with many distributed energy resources (e.g., customer solar panels), we provide analytics for two-way energy flows and virtual power plant coordination.

Empowering consumers to manage usage. We create consumer-facing apps and analytics that show users how they consume energy and offer personalized saving tips (e.g., “Your AC use is higher than similar homes; upgrading insulation could save $200/year”). For commercial and industrial customers, we enable automated demand-response programs (adjusting thermostats or processes during peak prices). We also use data segmentation to identify customers likely to adopt new services (EV charging, solar installation) and target them with relevant offers. By engaging customers with data and automated suggestions, utilities foster conservation and satisfaction.

Fortifying critical infrastructure against cyber and physical threats. We secure SCADA and control systems by monitoring for anomalies (e.g., unusual control commands) and strictly segmenting IT and OT networks. We help comply with energy standards (NERC CIP) by enforcing strict access controls, encryption, and continuous auditing. We also use analytics for resilience: simulating outage scenarios (with AI-assisted N-1 analysis) to identify grid weak points, and planning mitigations like automated switches or microgrids. For extreme weather, we integrate forecasts to pre-position repair crews (e.g., predicting which distribution lines will be at highest risk). These measures shorten outage restoration times and reduce the impact of storms or attacks.