Have you noticed that technology never stands still? That’s not exactly a news flash for anyone trying to keeping up with this rapidly evolving environment. Watching for new technological trends is one of the best ways for keeping up with smart grid innovations, but it’s not easy. There is, however, a shortcut that professional tech-watchers have learned. Check out the variety of webinars, podcasts, or virtual panel sessions; they can give searchers an edge. First off, these web events are convenient and easily accessible. Second, where else can you learn directly from the experts so easily?
In terms of popular topics, digitalization is a widespread attention grabber, but there’s an interesting twist as digitalization evolves. The web broadcasts are not zeroing in on the run of the mill digitalization. They’re focused on the combination of digital-based applications and artificial intelligence (AI), but there’s a caveat. It’s important that the digitalization isn’t limited to IT (information technologies) networks. It needs to include the OT (operational technologies) portion too. These environments have to exchange data and interact together rather than operate separately.
Growth of Digitalization
Digital technologies mixed with AI are simplifying the smart grid’s complex digital-based applications, which is helping their acceptance. After all, the more user-friendly the technology is will impact how well it’s received by the marketplace. The research company ResearchAndMarkets recently published some fascinating facts concerning the smart grid market. According to their research, “The global smart grid market is poised for significant growth.” They went on saying, “the global smart grid market, valued at US$55.54 billion in 2024, is projected to grow to US$145.42 billion by 2030.”
That percentage of growth in such a short period of time indicates the technology is meeting the customer’s expectations for grid efficiency, resilience, and improved flexibility. AI-driven smart grid technologies are making grid-enhanced technologies more dynamic, which is helping solve many of the increasing load growth as power grid challenges mount. It’s the real-time data analytics and situational visualization capabilities that enable a better blending of the physical world with the virtual world.
Keeping it simple, it’s the integration of IT and OT. This has been labeled the convergence of IT and OT (IT/OT). Some experts say it’s a transmutation that has made possible a variety of digital-based applications to operate beyond the traditional boundaries so prevalent in traditional organizations. The IT/OT convergence adds more awareness while extending its reach. The integration of AI into smart grid applications has brought a significant tool when it comes to big-data analytics.
Real-Time Decision Making
AI is automating many operational and maintenance tasks, and it’s more responsive with load and energy management platforms to name a few. State-of-the art digital technologies are responsible for bringing the edge of the grid to a new prominence in the power delivery system. It has also made the behind-the-meter more accessible benefiting both sides of the meter, but the introduction of AI is redefining the concept of the modern smart grid. It’s facilitating real-time analysis of the massive amounts of big-data coming from smart grid systems, but it’s more than just this specific data stream.
AI platforms are making information available from multi-databases improving intelligent decision-making. The process is transforming the power delivery system, but it’s still a long way from a totally digitalized power system. So it’s reasonable to say that if we’re going forward, it’s going to take a more coordinated effort. With that in mind, it’s time to talk with an expert. “Charging Ahead” contacted Adnan Chaudhry, the senior vice president Digital Grid at Siemens Energy for his thoughts on digitalization joined with AI.
Mr. Chaudhry began the discussion saying, “Continuing to add assets in the grid alone won’t satisfy the growing hunger for electricity challenging utilities worldwide. To fully use the existing transmission assets on the grid, we need to digitize everything and utilize AI analytics. Digitalization combined with AI is the missing element for taking the power grid’s efficiency to the next level, but many utilities are only starting this process. They may have a digital substation or maybe a few powerlines with dynamic line rating technology. It’s a great starting point, but more is needed to make the most of underutilized assets.”
Chaudhry continued, “How can the power grid handle the increasing power demand? It needs its efficiency increased. Adding lines, generation, or substations is crucial, but a highly time-consuming process, which can’t quickly solve today’s grid congestion or other bottlenecks. It’s not a secret, we have never used the existing grid anywhere near its actual limits. It’s always been constrained by assumptions and the static limits set on its assets. When sensors are added to a line, the data tells the user how much capacity is really available in that line. Many are surprised that it can be 20% or more.”
Mr. Chaudhry explained, “To enhance the grid in a holistic way, it’s essential to add sensors to transformers, switchgear, and other equipment. For real-time operations you need real-time data, as it gives a dynamic overview of network conditions. That’s why Siemens Energy’s digital grid portfolio focuses on digitizing the entire system from end to end. It also takes advantage of external databases that use AI’s predictive analysis to improve various aspects such as planning, load management, operations, and maintenance. AI and machine learning applications have brought predictive maintenance to a new level improving efficiency and productivity.”
Chaudhry continued, “A good comparison of what is happening in the power grid can be found in the automobile industry. Thirty years ago, cars didn’t have sensors. We had no way knowing the condition of the engine, transmission, or other components. Maintenance was determined by the calendar or the vehicle’s mileage. We didn’t know the condition of the engine, so at ten thousand miles the vehicle was brought in for maintenance. Today the vehicle’s instrumentation notifies the driver of any potential problems and recommends maintenance within a specific timeframe. This is exactly what our sensors on the power grid do. Predictive analytics have reduced the number of unscheduled outages and made us more efficient in the process. It’s not a question of whether to digitize or not. It a question of how to do it efficiently and cost effectively!”
Aligning Real & Virtual Worlds
AI-driven digitalization applications are a new approach that many utilities and grid operators are actively pursuing. Some are utilizing a simple approach while others are going deeper into the technology. Companies like GE Digital, Hitachi Energy, Oracle, Schneider Electric, Siemens Energy, and others offer a variety of products.
For several years, American Electric Power (AEP) and Siemens Energy have been working together on the implementation of a digital twin of AEP’s entire transmission network. It’s a massive undertaking considering AEP has over 40,000 line-miles (64,374 line-km), covering 11 states serving nearly 5.6 million customers. According to Siemens Energy, AEP expects to utilize a complete digital model of their physical grid that can quickly adapt to grid changes while increasing renewable capacity efficiently, safely, and reliably.
Late last year, Southern California Edison (SCE) received an achievement award from the Association of Edison Illuminating Companies for its AWARE (Advanced Waveform Anomaly REcognition) platform. This inhouse suite uses AI-driven tools to analyze system real-time data. The data comes from substations, AMI (Advanced Metering Infrastructure), and SCADA (Supervisory Control and Data Acquisition) systems. The AI algorithms identify abnormal patterns in grid behavior. It also “pinpoints the location of potential problems.”
A few months ago, Alphabet Inc. announced their Google and Tapestry units have formed a partnership with PJM Interconnection, the largest regional transmission operator in North America. PJM manages over 88,000 line-miles (141,600 line-km) in 13 states. The collaboration’s goal will apply AI-driven technology to consolidate the dozens of databases and tools used by PJM for their interconnection procedures into a unified model of the PJM network. The unified model will speed up the interconnection process, which will enable PJM to make faster decisions with greater confidence.
The digitalization of the power delivery system is a growing trend and it’s expensive, but the experts are predicting the return will surpass the outlay significantly. When AI technology is combined with smart grid applications it enhances grid stability, optimizes demand management, improves energy efficiency, and the list grows. Mr. Chaudhry said it best, “To fully use the existing transmission assets on the grid, we need to digitize everything and utilize AI analytics.”
It's also extremely important we understand how these technologies work and what their limitations are, which can be a challenge since they are evolving so quickly, but that’s what makes it fun. Capgemini reports that “a planned and holistic approach is needed for grid transformation by digital innovations.” Of course, we have to overcome legacy thinking too. It can hold us back more effectively than any other obstacle, but this could be the next step to the future grid!
