White paper: Transforming utility operations with asset image analytics

As utility companies face increasing pressures to modernize infrastructure and enhance operational efficiencies, asset image analytics has evolved from a “nice to have” into a strategic imperative. By implementing AI-driven inspections using visual data from drones, satellites, LiDAR, and even cell phone cameras, utilities can enhance strategic decision-making capabilities and operational readiness.

Download our white paper Transforming utility operations with asset image analytics: Strategies and impacts to learn:

Business drivers for asset image analytics

Behind the integration of asset image analytics within utility operations are several key business factors grounded in both economic pressures and operational challenges.

Following are just a few of the factors driving the need for innovation in the utility sector’s approach to asset management and grid modernization.

Escalating operating costs

Utilities are under constant pressure to manage and reduce operating expenses. Asset image analytics can significantly reduce the costs associated with manual inspections and maintenance by reducing truck rolls while enabling more precise identification of issues and targeted interventions.

Increased inspection needs

Aging infrastructure and heightened regulatory demands necessitate more frequent and detailed asset inspections. Traditional methods are often costly and labor-intensive, whereas image analytics allows for rapid, comprehensive assessments of multiple assets over large geographical areas, improving both efficiency and effectiveness.

Compliance requirements

Regulatory bodies often require frequent inspections, adherence to maintenance standards, and detailed documentation. For example, the North American Electric Reliability Corporation (NERC) Standard PRC-005 requires the implementation of maintenance programs for all protection systems, automatic reclosing, and sudden pressure relaying systems affecting the reliability of the Bulk Electric System (BES) to ensure they are kept in working order. Image analytics can streamline compliance processes by providing accurate, up-to-date visual data that can be easily archived, retrieved, and formatted for regulatory reporting.

Pressure to maximize reliability metrics

To assess the quality of utilities’ management practices, the Federal Energy Regulatory Commission (FERC) has developed a series of reliability metrics:

• System Average Interruption Duration Index (SAIDI): The total duration of the average utility customer’s interruption of service lasting 5 minutes or longer
• System Average Interruption Frequency Index (SAIFI): How often the average customer experiences an interruption of 5 minutes or greater
• Customer Average Interruption Duration Index (CAIDI): The average time required to restore service after an interruption
• Customer Average Interruption Frequency Index (CAIFI): How many interruptions each impacted customer experiences
• Momentary Average Interruption Duration Index (MAIDI): The total duration of momentary disruptions (less than 5 minutes)
• Momentary Average Interruption Frequency Index (MAIFI): How often the average customer experiences momentary disruptions

These indices help utilities and regulators evaluate how well the system provides an uninterrupted power supply to customers. Because utilities can leverage image analytics to identify and address potential issues faster and more accurately, they can advance toward reducing outage frequency and duration, leading to improvements across indices and to the overall reliability of their service.

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