Do not underestimate intelligent automation in utilities

The traditional utilities business model is under pressure worldwide. The move to green energy, prosumer clients, and diminishing regulations is significantly impacting business models around the world. The industry needs to move toward digital more aggressively. More agility and business intelligence are required.

Intelligent automation is the path to that future. It will manage the balance between demand and supply, boost efficiencies across the entire value chain, reinvent the customer experience, and transform business models.

Intelligent automation is the combination of automation and artificial intelligence to create systems that make real-time changes and adaptations to operations based on input from sensors. The Capgemini Research Institute (CRI) recently spoke with 530 business leaders about intelligent automation in energy and utilities, including oil and gas, electricity, water, and energy services.

The report analyzed more than 80 use cases to assess maturity, complexity, and benefits. Not surprisingly, it shows the forerunners are leading the way to a new energy and utilities dynamic.

Seize the opportunity

The CRI report showed many utilities are targeting the wrong projects. More than one third of energy and utilities companies (38%) are focusing on projects that are easy to implement but which deliver small benefit. Fewer than one in five (18%) are targeting the sweet spot of quick wins with big value.

It is time to push forward and be bold. Think beyond support projects and get real results, like some of these companies:

• Xcel Energy, a US-based electric and gas utility, uses data from sensors on wind turbines to develop high-resolution wind forecasts through AI techniques. The company reduced costs to end customers by $60 million annually by increasing the efficiency of generation.
• GE Renewable Energy is using machine learning to support yield optimization. It builds virtual wind farms in a cloud-based platform that mimics a real-world, physical design. The model runs wind patterns and calculates electrical output to optimize production on an individual turbine level. GE expects to generate a 20% boost in energy production, resulting in $100 million in savings over the lifetime of a 100 megawatt farm.
• Vermont Electric Power Company (VELCO) uses advanced data science and machine-learning techniques to develop a hyperlocal weather forecasting system. It applies this weather model to all its solar and wind farms in Vermont, and has reduced average energy forecasting errors by 6% for solar and 9% for wind. Every 1% of load reduction means better resource allocation and saves ratepayers $1 million per year.
• Better complaints management has made a significant difference for Exelon, a US-based electricity and gas utility. Its AI-powered chatbot, developed to resolve customer complaints on issues such as outages and bills, has reduced customer churn and generated deeper insights into their consumers’ needs.
• Swiss Energy leader Alpiq has implemented its Gridsense technology, which uses algorithms to measure parameters such as grid load, electricity consumption and generation, weather forecasts, and electricity prices. It provides better insights into consumer behavior, optimizes generators, reduces peak loads, balances loads, and stabilizes the distribution grid.

Automation and AI will be instrumental in meeting the new demands of the market, including addressing climate change. It is time to seize the opportunity of intelligent automation and the power of digital technologies.

Randy Cozzens is an Executive Vice President and North American Energy, Utilities, and Chemicals Market Unit Lead at Capgemini and can be reached at randall.cozzens@capgemini.com.