Utilities engage machine learning to predict what’s next
- Jan 11, 2021 10:06 pm GMTJan 11, 2021 9:00 pm GMT
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The 2020 COVID pandemic has significantly impacted electric utilities across North America. As the crisis began, many utilities found themselves analyzing a variety of operational datasets to enhance situational awareness. The challenge, however, is that historical datasets provide only limited insight into what might be coming next. An operational report, for example, may display where distribution system power outages have recently occurred in the service territory. In order to understand, however, where power outages are likely to occur in the future, utilities must harness the capabilities of machine learning. Moving into 2021, power utilities will more intentionally leverage predictive modeling and machine learning to proactively anticipate customer, operational, workforce, asset, and financial challenges and opportunities.
The first area of opportunity in utility predictive analytics centers on customer experience. In 2021, utilities will need to continue to support their customers on the long road of recovery. By engaging machine learning, utilities can predict which customers are likely to need bill assistance resources and offer targeted communications to build long-term customer loyalty. Digitally progressive utilities may even begin to provide predictive customer next best offer features in customer-facing digital channels.
Operations & Workforce
Next, utilities will more effectively leverage machine learning capabilities to improve operational effectiveness. During the winter and spring storm seasons, utilities may utilize vegetation imagery, outage history, and asset health datasets to predict where outages or system disruptions are likely to take place. Predictive modeling may also help with field and mobile workforce optimization as dispatch operators can position crews proactively to the most vulnerable areas of the network.
Utility SCADA platforms for generation, transmission, and distribution operations produce overwhelming amounts of data that utilities often struggle to convert into actionable insights. As utilities continue to advance their machine learning practices, data scientists can train these massive datasets to separate the signal from the noise, leading to valuable asset management takeaways around maintenance and optimization. These insights can save millions of dollars and directly benefit customers in keeping rates affordable.
Finally, as the road to financial recovery from the COVID crisis becomes clearer, utility data scientists will build predictive machine learning models around receivables, cash flow, and other essential financial indicators to help decision-makers gauge the financial state of the utility. These predictive tools become essential for future planning and effective executive decision-making.
Overall, moving into 2021, power utilities will begin to tap into the heaps of utility datasets in order to gain predictive insights. As data science technologies and patterns becoming increasingly more commonplace, power utilities will be well positioned to engage these insights to enhance the customer experience, reduce operational expenses, and prolong asset life.