[REPORT] Utility Outage Prediction 2.0 : Embracing Advanced Analytics & Machine Learning Solutions

It’s more than just knowing that a storm is coming from a trustedforecast source. It is utilizing that information to understand how a storm will impact a utility’s service territory. Using a decision support tool like an outage prediction model gives organizations the opportunity to take a proactive rather than reactive stance to preparation and response to impactful weather. This enables a more efficient response which lowers cost while keeping customers and regulators happy.

The ability to access timely information prior to a storm about the incoming is available today. What is not always available in a meaningful, easy-to-use manner is the connection between weather and its impact on the utility system. That connection is critical to determining the level of impact a utility can expect so they can decide what actions they need to take in advance. This creates a key question for energy providers: How can predictive tools like an outage prediction model create operational and financial benefits for their organizations? This paper looks to:

  • Understand utility comfort levels, struggles and use of weather information and outage prediction tools
  • Quantify the financial and operational impacts of unfavorable, and the cost of making storm mobilization decisions based on weather forecasts
  • Identify the opportunities and challenges of using an outage prediction model to improve storm preparation and mobilization decisions

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