The Art of Artificial Intelligence: Three Ways AI is Changing the Business of P&U

With the help of AI and other emerging technologies, utilities can improve long-term business planning around infrastructure investments and maintenance schedules, launch new revenue-generating customer-focused energy services, and proactively optimize operational performance

September 30, 2019. By News Bureau

Artificial intelligence (AI) is poised to unleash the next wave of digital disruption in several different industries – the power and utility (P&U) industry is not an exception. Energy distribution is no longer a linear equation. As new energy and data sources continue to grow, utilities are trying to take a more holistic approach to better understand and manage resources and engage active customers at the edge of the grid. In a nutshell, AI is enabling markets to be more efficient and making it easier for stakeholders to understand operational complexities when it comes to outage and distributed energy resource (DER) management.

With AI-powered solutions, utility operators can leverage comprehensive, real-time models to ensure a more resilient and efficient grid, with machine learning working behind the scenes to analyze disparate data sources and provide actionable insights back to the business and customers. While the opportunities for AI in the utility space are endless, there are a few notable ones delivering direct, tangible benefits already.

Managing Major Weather Events

Having an outage management plan is critical for utilities, as waiting to simply react to a storm event is often costly and ineffective. A proven outage management system, with built-in AI, can minimize the impact of natural disasters via an improved understanding of event scenarios, real-time grid monitoring and more effective use of human resources. With the ability to ingest, normalize and transform massive amounts of data from a variety of sources into accurate and actionable insights, an AI-enhanced Outage Management System (OMS) can analyze past weather patterns and predict future outages. As such, utilities can carry out proactive maintenance measures to help mitigate the impact of potential damage and have the right crews in place to quickly mobilize when damage does occur, making the best of a difficult situation. With this sophisticated type of predictive maintenance, AI is already helping many utilities provide higher quality service with fewer interruptions and shorter outage durations.

Optimizing the DER-Integrated Grid 

Beyond storm preparedness, AI also takes full advantage of greater grid visibility and control from distribution to the connected customer through advanced distribution management.  Electric utilities recognize the need for new distribution network technologies as they strive to accommodate the growth of renewable energy and customers’ increasing interest in grid-connected, customer-owned energy technologies. The distribution grid of the future comes to fruition with a customer-centric platform approach -incorporating and optimizing all DERs, SCADA-enabled devices, and IoT device interactions. These control functions within a common operating model enable utilities to continuously collect and analyze massive amounts of data from hundreds of thousands of smart devices. The AI-infused data analysis then informs timely decisions regarding how to best allocate energy resources and further balance supply and demand all in one place – both in real-time and continuously looking ahead to proactively mitigate grid constraints before they happen.

Distributed energy resource management is another compelling example of how utilities are embracing AI to robustly manage, optimize and modernize their grid. For instance, utilities can proactively identify and engage electric vehicle owners to charge at reduced rates, if they do it outside peak usage hours. Utilities also can provide insights to their solar customers to help them better manage the flow of energy between their photovoltaic system and the electric grid. By helping utilities better understand their users’ patterns and behaviors, AI can help foster two-way customer engagement, which in turn helps customers take advantages of utility DER programs designed to optimize grid management and stability. This interaction is the very foundation a truly connected grid.

Improving Customer Experience

According to a recent Deloitte report, researchers believe that the customer of the future will have a personal relationship with their utility. That will be no easy feat when it is estimated the average customer currently spends less than 60 seconds a month thinking about their utility provider. With the help of AI and advanced analytics, utilities are accelerating this vision. Customers increasingly – in addition to basic power – are able to get personalized services and insights about their electricity usage to help them better manage home energy use and understand their bills and transactions. For example, the combination of smart meter data and AI allows a utility to predict when customers are on track to exceed their normal bill and automatically send a real-time alert to the customer – giving them time to adjust their behavior.  These kinds of behavioral response programs leveraging machine learning and AI are not only helping customers reduce their carbon emissions and costs, but also are essential in helping utilities better balance the load on the grid, especially in peak times. 

Utilities today are facing a perfect storm of evolving distributed energy resources across their networks, a barrage of data, and ever-savvy customers who are looking to their utility to be a trusted advisor in their changing energy journey.  As such, resources can no longer be managed in isolation. With the help of AI and other emerging technologies, utilities can improve long-term business planning around infrastructure investments and maintenance schedules, launch new revenue-generating customer-focused energy services, and proactively optimize operational performance.

Source- Deloitte: Digital innovation: Creating the utility of the future, April 09, 2019


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