AI in Utilities

AI IN UTILITIES

The industry of utilities can benefit greatly from AI by automating repetitive tasks. Previously, the industry was highly dominated by manual work. Automation can help businesses within utilities to cut costs, optimize efficiency and enhance customer service.

The industry of utilities is highly dependent on short-term load forecasts. Machine learning can help businesses to predict real-time supply and demand, in order to reach the optimized load dispatch. Likewise, real-time adjustments provided by AI can help a business to attain optimized generation efficiency across all assets. AI can also be used for asset inspections and predictive maintenance, automatically identifying defects and predicting failures. In this way, AI can help businesses fix problems before they evolve, or even occur, as well as replacing time intensive and perhaps risky manual inspections.

Modern natural language processing and data analytics are of high value in this industry. Running large scale analytics and machine learning on customer data can also help businesses in utilities to set prices that maximize margins and reduce customer churn.

The areas where utilities can benefit from AI are ever expanding.

Areas of AI application in Utilities

  • Applications can help deepen customer insights, allowing businesses to create individual offers and services, rewarding and retaining most profitable customers.
  • Virtual agents can respond to customer queries and provide instant service around the clock.
  • EV/Battery aggregation, and fleet optimization, demand forecasting.
  • Production and storage forecasting.
  • Service & maintenance. Success predictions and scheduling.
  • Outage predictions.
  • Risk management and forecasting for spot/emissions/regulation markets.
  • Predictive maintenance.

Use cases

 
Prediction of service cases in Utilities
A supervised algorithm predicts service cases, increasing accuracy in planning of service and maintenance
Lead qualification – up to 80% accuracy
A supervised learning algorithm predicts whether a customer is most likely to become a lead.
Churn prediction in Utilities
Creation of a model that analyzes past client lifecycles and likelihood of churn.
Predictive maintenance in Utilities
An algorithm predicts the risk of equipment failure and need for maintenance
Email routing – reducing manual work
Emails get classified by using a supervised learning algorithm, up to 40% reduction in manual work at support desk
Prediction of energy efficiency
An algorithm labels homes with energy efficiency class.
Demand forecasting for energy
Prediction demands with a supervised learning algorithm, predict the demand for energy and manage its production
Chatbots in Utilities
Improving instant communication with clients and having a more dynamic Q&A page that customers like to use
 

Meet the industry leader

Rasmus Hauch

Rasmus Hauch

Utilities, 2021.AI

Rasmus is VP in Engineering and Chief Architect at 2021.AI. Rasmus has an abundance of experience in positions like Program Manager, Lead Architect, and Senior Consultant for various international Financial, Energy, and Telecom customers. His skills include leadership, mentoring and enterprise architecture.

rha@2021.ai in

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