Doble In The News

Take a deep dive into understanding oil specifications such as dielectric strength, viscosity, density, volatility, flash point, chemical stability, and other critical properties.

Obtaining real-time operating data on power plant and substation equipment has never been easier. The sensors, transmitters, and systems needed to monitor important parameters are readily available and highly cost-effective. The ability to identify problems early and make repairs prior to catastrophic failure improves system reliability and saves utilities money.

To get the best from your bushing monitor, it is vital to set expectations up at the outset and ensure the monitor, its maintenance and management are included in the asset management plans of the organization. Then we can expect to get sensible data which can be used to both detect bushing deterioration and subsequently support bushing investigation and diagnostics.

This article by Doble’s Dr. Tony McGrail in Transformers Magazine explores the intricacies of DGA monitor accuracy, emphasizing the challenges in extracting dissolved gases from transformer oil. Despite international standards like IEC 60567 recommending a maximum accuracy of 15% for complete DGA systems, real-world application, as reflected in CIGRE brochures, suggests a potential deviation closer to 50%. The implications of varying accuracies on diagnoses, particularly when employing diagnostic tools like the Duval triangle, are analyzed.

Matthew Carrara, President of Doble Engineering and ESCO Utility Solutions Group (USG), had the opportunity to interview with Authority Magazine for their series called “Moving From Command & Control to Coaching & Collaboration; How Leaders and Managers Can Become Better Coaches”.

As the U.S. prepares to ramp up production of transformers and other grid components, the focus must be on quality and not just quantity.

Matters of NERC PRC and NERC CIP compliance intersect during protection system testing on substation networks. In the modern regulatory environment, the benefits of computer-based relaying are challenged by the costs of cyber security and disrupted or insufficient relay testing practices. The way forward demands interconnected data and the ability to track critical metrics automatically. Organizations can modernize while ensuring compliance readiness by implementing systems that integrate protection and cyber domains into scalable management platforms.

When primary station equipment trips out, it is often the substation maintenance engineers who must review the situation, get the data needed to make an informed decision, and then ‘make the call’…

The design life of a transformer is usually about 20 to 25 years. In the United States, estimates show the average age of a transformer is currently around 42 years, which means a number of even older units are still in service. As with all things, transformers age and degrade over time. Transformer failures can come from a variety of sources including through faults, faulty crimps and brazes, corrosive sulfur, poor design, water intrusion, collateral damage from a bushing or load tap changer (LTC) failure, incorrectly sized leads, and a host of other issues. Overall, however, the demise of a transformer from normal aging is linked directly to the condition of the solid insulation (i.e. paper, cellulose).

We should have expectations when applying condition monitoring to transformers. If we know what to expect then we can identify measurements which are unexpected or anomalous and worthy of deeper investigation.

ESCO Technologies Inc. (NYSE: ESE) today announced that it has entered into an agreement to acquire I.S.A Altanova Group S.R.L. (Altanova), a well-established, leading supplier in the field of advanced condition assessment technologies centered around partial discharge (PD) measurement and analysis, as well as test instruments for electrical apparatus (www.altanova-group.com).

AI systems provide a lot of promise in the analysis and evaluation of power system data. This article shows some of the benefits of the application of AI, identifying the strengths and weaknesses of the approach, and provides a way forward to apply AI in a meaningful and controlled manner.

Did you choose the correct oil for your transformer application? This is the one big question I am confronted with after reading through this outstanding article written by the three authors, Lance Lewand, Eileen Finnan, and Melissa Carmine-Zajac. All of them are highly respected in the industry. Interesting to see the long road oil analysis has come and the progress that has been made in the transformer oil industry, to ensure a high-quality product fit for a specific purpose. The criteria are set out to guide us to evaluate the insulating fluid when considering a fit candidate for lifetime optimization and reliability.

An asset health index (AHI) summarises a lot of disparate data into a single value in order to estimate the condition of the asset, such as a transformer. The big question is: does everyone understand what the AHI really means? Technical information used to derive an AHI is lost. At the same time, looking at the AHI value, the end-user can get a feeling that they know all they need to know, which sometimes can be misleading.

Sweep frequency response analysis (SFRA) is a popular test to confirm the mechanical and electrical integrity of a transformer. However, the resulting traces can be difficult for field personnel to interpret due to the visual nature of the data. It is more straightforward to compare numbers against prior data or against a stated limit than to interpret subtle differences in SFRA traces. If setup-related issues are not addressed during the testing process, return trips are often required to take additional shots to represent the transformer more accurately. These trips cost time and resources, so being able to identify a setup problem early can keep extra work to a minimum. A trained eye can focus in on a problem area quickly and identify a test setup issue promptly. Such confidence only comes at the expense of hours spent analyzing data. This article discusses common setup problems and their impacts.