Power utilities are facing transformative changes, driven by trends like a sharp increase in electricity consumption, increasing sustainability concerns, and the rising reliance on emerging technologies. As utilities embark on their digital transformation, they can find new ways to work, increasing their efficiencies, and gaining new business insights using artificial intelligence (AI). 

As The American Public Power Association, a non-profit representing public utilities, notes: "AI offers the potential to help the people who work in utilities to be more efficient and more effective." 

Optimizing Efficiencies 

Public and private utilities are often responsible for providing multi-state regions with continuous power, and when the grid is interrupted, the effects are almost immediate. Because of this, utility companies face enormous pressure to maintain uninterrupted service, meet growing demand, and improve the reliability of aging infrastructure. By integrating AI into their operations, utilities can better manage resources, optimize workflows, and improve decision-making processes. Here are some ways that AI is being used in the power utility market: 

1. Predictive Maintenance. The traditional model of scheduled maintenance is inefficient and expensive. With machine learning models that are trained to analyze equipment sensor data, AI can predict the likelihood of failures or breakdowns. This helps utilities prioritize the most critical maintenance activities, reduce unplanned outages, and lower operational costs.  
   
   
2. Grid Stability. Electricity grids are becoming more complex with the rise of renewable energy sources. AI can promote grid stability by analyzing real-time data, predicting supply and demand changes, and adjusting the grid to accommodate current conditions. This flexibility can help prevent blackouts and increase energy efficiency. 
   
   
3. Demand Forecasting. Predictive models can be trained to process historical consumption patterns, weather data, and real-time market conditions to accurately forecast changes in demand. This gives utility companies time to adjust power generation or distribution ahead of time, minimizing waste.  
   
   
4. Remote Inspection of Transmission and Distribution Assets. Utilities need a complete understanding of the condition of their assets at any moment in time. However, manual inspection of transmission lines, pipelines, and other infrastructure poses several risks and challenges. Backroads and difficult terrain can prevent easy access for emergency repairs. Workers face the risk of falling and/or head trauma from falling equipment. The time, resources, and equipment needed drives up costs. Implementing drones removes unnecessary risk, with data captured aerially and then analyzed with machine vision.
    
5. Enhancing Asset Management and Data Collection. Utility companies manage vast networks of assets spread across large geographic areas. With AI, the method for collecting, managing, and tracking data on transmission lines, substations, and other assets can be simplified, providing utilities with the information they need to plan for investments and manage asset life cycles.  
   
   
6. Filling Workforce Skill Gaps. With more than 25% of the utility workforce at the age of 55 or older, we are facing a wave of retirements, and potentially years of knowledge and on-the-job experience lost. AI can help mitigate that loss by automating repetitive tasks, personalizing training programs for younger technicians, and aiding decision making with real-time analysis. With greater and more consistent access to data, the shifting workforce can be managed more efficiently. 

Innovative ways to implement AI will continue to emerge to address new and ongoing challenges. At KCI, we’ve developed a pretrained computer vision model to detect equipment installed on power poles to improve asset inventory efforts and workforce development. The BRYX Power Pole Equipment Detection model is available through our catalog; start a free trial to see how it works!