Accurately predict vegetation-induced outage risk and optimize mitigation returns with AI, allowing you to:
- Fine-tune your vegetation management budget to see improvement of more than 20%
- Increase grid reliability and public safety by identifying and targeting high-risk spans
- Understand the implications of budget changes and make informed adjustments through streamlined scenario planning
- Gain midcycle or hazard-tree budget efficiencies for quick wins
Predict storm-induced outages and mobilize crews with AI, increasing grid reliability and making better use of storm management budgets so you can:
- Increase outage prediction accuracy by more than 20% three to five days ahead of a storm
- Coordinate crews and mutual assistance in advance, improving response time
- Plan crew sizes and decide when and where to send crews, reducing costs by up to 20%
- Achieve less prediction variability during the prediction window
Meet your energy savings goals with an AI-powered solution that combines historical customer data and smart meter data to develop a granular, individual forecast for your customer base, empowering you to:
- Identify the best customers to focus on to boost the success and cost-effectiveness of a demand response program or portfolio
- Enable on-demand or automated event scheduling
- Proactively engage and manage participants for optimal results
Built on years of practical innovation and measurable results, E Source Digital Grid Solutions enable utilities to quickly and continually improve how they manage their most consequential use cases—from vegetation and storm outage management to capital optimization. You’ll be able to not only identify risk across the grid, but also optimize what to do about that risk to improve safety and reliability most efficiently and affordably.
Use machine learning to optimize your program portfolio and serve customers as an audience of one. The E Source Audience of One solution maximizes customer engagement by using data and ethnographic research to serve customers as individuals rather than segments to optimize the lifetime value a utility delivers to each customer.
