Transmission & distribution |
integration process demands not only technical expertise but also a strategic approach to ensure that new and old systems communicate effectively without disrupting ongoing operations. In addition, for AI to be effective, it requires high-quality, structured data. Utilities often have vast stores of unstructured or inconsistent data, making it difficult to leverage AI effectively. Establishing robust data governance and quality control is essential to prepare for AI integration. The process of cleaning and organising data can be resource-intensive but is critical for maximising the benefits of AI.
Training and change management also play crucial roles in the successful implementation of AI. Utility workers must be trained not only on how to use new systems but also on how to interpret AI- generated insights effectively. In an industry with an experienced workforce, the cultural shift towards data-driven decision making can be substantial and requires careful management to align staff with new technological processes.
Furthermore, the upfront cost of implementing AI can be a barrier, particularly for smaller utilities or regional co-operatives. However, the long-term cost savings, increased efficiency, and improved
asset management performance justify the investment. To mitigate these costs, some utilities opt for phased implementation strategies, starting with the most critical assets to generate quick wins and establish the value of further investment. Overcoming these challenges requires a proactive co-ordinated effort between AI solution providers and utility companies, focusing on seamless integration, comprehensive training, and strategic investment to ensure that AI tools deliver on their promise to transform utility asset management, while remaining flexible and scalable to best suit the utility’s needs. Such strategic integrations will enable early adopters to enhance their operational efficiencies without overhauling their entire systems.
Looking ahead
Looking ahead, the role of AI in utility management is set to grow exponentially. The Internet of Things and smarter grids are expected to further enhance the capabilities of AI systems. These technologies will allow utilities to not only monitor but also automatically adjust their operations in real-time to optimise energy distribution and respond to potential disruptions before they escalate.
Moreover, as utilities continue to face the challenge of extreme weather, AI will allow them to stay one step ahead in determining the status of vegetation that could fall onto powerlines or catch fire. Advanced data analytics powered by AI can provide enhanced decision making, as AI algorithms analyse vast amounts of data to predict potential failures before they occur.
From discussion to action AI is already transforming utility asset management from a reactive to a proactive discipline. By harnessing the power of AI, utilities are not only improving their operational efficiencies but are also setting the stage for a future where digital resilience defines utility industry leaders.
The journey from theoretical AI applications to practical, impactful implementations is complex but achievable with strategic planning, robust partnerships, and a clear focus on long-term goals. As we move beyond the hype, it becomes clear that AI is not just a tool for innovation but a necessity for the sustainable, efficient, and resilient utility operations of today and tomorrow.
Hitachi Energy puts natural-ester-filled 765 kV transformer to the test
There is nothing particularly new about natural- ester-filled transformers, Hitachi Energy has, for example, been supplying them for over 20 years, with installations in more than 40 countries. However, Hitachi Energy has now successfully tested a 765 kV/400 kV single-phase, 250 MVA natural-ester-filled oil transformer. This “breakthrough innovation makes this
transformer the first in the world at this voltage and power level,” says Hitachi Energy, with “the implementation of ester oil providing a biodegradable and safety-by-design option for operators of ultra-high-voltage AC grids.” The 765 kV/400 kV transformer was designed, manufactured and tested as a further development of Hitachi Energy’s TrafoStar
transformer technology platform. TrafoStar aims to harmonise transformer design, manufacturing processes and quality control measures across all Hitachi Energy power transformer factories worldwide (with more than 30 000 power transformers produced to date).
Transformers have traditionally used mineral oil, well known for its excellent electrical properties, as an insulation and cooling medium. Alternative fluids, such as natural ester, can provide additional safety and environmental performance features.
Natural-ester fluid, as employed in the 765 kV transformer test, has a flash point twice as high as mineral oil and self-extinguishing properties. Combined, these qualities make natural-ester- filled transformers safer than mineral-oil-filled transformers, says Hitachi Energy. In addition, “virgin natural esters are up to 100 percent biodegradable within 28 days,” Hitachi Energy notes, reducing the risk of environmental pollution resulting from insulating fluid leakages. Safety is further enhanced, the company says, thanks to the use of Hitachi Energy’s rupture- resistant TXpandTM
technology.
Testing time for Hitachi Energy’s 765 kV/400 kV single-phase, 250 MVA natural ester-filled oil transformer. Photo: Hitachi Energy
26 | June 2025|
www.modernpowersystems.com
From power generation sites to the end-user, electrical energy passes through an average of four to five transformers, Hitachi Energy notes, observing that 765 kV AC transmission features in power grids in various regions worldwide, including North America, South America, South Africa, and parts of Asia (including China).
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