Distributed intelligence (DI) is a disruptor. The introduction of the DI concept a few short years ago is already becoming the industry norm. There are two main drivers for distributed intelligence: optimizing grid operations and transforming the consumer experience.
On the grid operations side, the expansion of distributed generation into the grid means that the utilities no longer have control generation and power flow.. Therefore, the traditional centralized control model just doesn't work. Instead, the distribution grid must become a living, breathing organism that can respond in real time to grid conditions at the edge, to sense and act locally to optimize and correct grid conditions as they occur. This is a key driver for the focus and investment in distributed intelligence that is occurring across the utility and energy management space. In short, distributed intelligence moves the solution - the analysis, the decision-making, and the action – closer to the problem, at the edge of the grid.
On the consumer side, utilities face two challenges. First is the customer expectation for advanced, proactive information and services, consistent with their every-day experiences with other products and services. Second is the reality that the dominant forces driving grid change - consumer solar, electric vehicles, decarbonization – are occurring within customer homes and businesses, and the only way to effectively balance and optimize the grid is through coordinated participation with customers and their generation and loads. This new level of customer engagement at the every edge of the distribution grid is the other key driver for the focus and investment in distributed intelligence that is occurring across the utility and energy management space . As we look into the future, it’s not too hard to see prosumers acting as utilities, selling electricity to their neighbours, all managed in real time by intelligent points of presence right at the transformation point between the prosumers/consumers and the utility grid, interacting directly with consumer generation and loads to balance and maintain stability of the grid.
As utilities consider investments in Advanced Metering Infrastructure (AMI), there are three things to consider. First is that an investment in Advanced Metering Infrastructure (AMI) is a 15-to-20 year marriage with the technology. Utilities must consider the ability for the technology to evolve and expand supported use cases over that 15-20 year period. With the rate of change today, it’s not possible to envision and up-front “spec” the functions and use cases that may be required 10 years from now. AMI devices with a distributed compute platform and the ability to deploy new use cases through apps at the edge provide that flexibility over the life of the solution.
Second is that development, deployment, maintenance, and administration of the “apps” that provide new use case and functionality must occur over a very large population of devices, continually over the life of the solution. As a result, the technology must not only provide the distributed compute capability at the edge, but also the high scale centralized administrative and management systems and processes that are required to effectively utilize this capability and to enable use case development and deployment from a broad ecosystem of vendors.
Third is the AMI business case. If we look at the industry, many utilities are faced with a traditional AMI business case that sits right on the ROI threshold for a business case to justify AMI expansion versus not. Distributed intelligence allows expansion of the AMI business case to use cases in operational areas of the utility that are traditionally outside the AMI scope, pushing the overall business case ROI to the level required for regulatory approvals.
With an AMI investment, its important to plan for the future and justify the business case today. Distributed Intelligence enables that to happen.
https://emea.itron.com/en/w/elfack-2025
Itron, Inc.
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