{"id":742,"date":"2020-09-03T19:08:50","date_gmt":"2020-09-04T00:08:50","guid":{"rendered":"http:\/\/polywaterv2.wpengine.com\/?p=742"},"modified":"2025-05-19T15:38:22","modified_gmt":"2025-05-19T20:38:22","slug":"the-aging-of-power-transformers","status":"publish","type":"post","link":"https:\/\/www.polywater.com\/en\/knowledge-hub\/the-aging-of-power-transformers\/","title":{"rendered":"The Aging of Power Transformers"},"content":{"rendered":"
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To counter the negative consequences of the aging behavior of power transformers, users need to optimize the operation of their transformer populations from both a technical and a commercial point of view. This is a complex issue with no definitive answers. Aging refers to the natural degradation of the insulation system that consists of traditional, solid components like paper, press board, and plywood, and fluids such as insulating mineral oil. Of these, the solid insulating materials are most important as they cannot be replaced without completely rebuilding the transformer. This means users need to understand the aging processes of these materials to make a viable assessment of the general and remaining service life of transformers.<\/p>\n

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Transformer design and technology have undergone significant changes over the past 40 years. This makes it more difficult to assess how a transformer will age because aging will depend on the behavior of new materials and alternative insulating fluids. Nevertheless, existing transformer fleets still comprise systems insulated with traditional materials such as cellulose and mineral oil. Users also must assume that “standardized” assessments (e.g., Loading Guides in IEC and IEEE) are, by their nature, unreliable. These guides do not consider specific transformer design, materials or operating modes. In this sense, there is no such thing as the ideal \u201ctransformer.\u201d<\/p>\n

Understanding the aging behavior of these materials alone is not enough to determine a specific transformer’s condition. The insulating materials mentioned above all play a factor. There are more influences to consider. These influences include aging accelerators, transformer design, and DGA history. Adding a full range of factors makes assessing how a given transformer is aging even more complex and requires an integrated approach. Any method based on a single value, e.g., the degree of depolymerization, is of little use, particularly if that value is obtained from furan analysis.<\/p>\n

I will walk you through an integrated approach that will help evaluate all of the following: assessing individual factors, the accelerators, the operating conditions, and the influence of different transformer designs.<\/p>\n\n\n\n
Related Content: <\/strong>Mapping Transformer Populations<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Aging Profile<\/strong><\/h2>\n

The literature often assumes that aging is a linear process. However, this contradicts actual experience in the field, which has shown that aging is actually non-linear. The aging process is driven by a number of accelerators that are mutually exponentiating.<\/p>\n

The graph below illustrates this non-linear process:<\/p>\n

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The graph shows the trajectories of various chemical and physical phenomena generated as the transformer ages. The key concept is shown in the diagram\u2019s green line, which represents what may be called the residual substance. This parabolic trajectory appears time and time again in transformer aging assessments and negates the presumption of a linear aging process.<\/p>\n

Replacing the term \u201cremaining lifetime\u201d with \u201cresidual substance\u201d can be useful. Lifetime is relative and depends on the conditions of service and other factors. Residual substance is similar to the content of water in a bottle. It may be consumed quickly, slowly, or even actively conserved. Apply this principal to each transformer to optimize its lifetime.<\/p>\n

Transformers are the \u201csneakiest” assets in a plant. Once a transformer enters the “C” range (Figure 1), it may not fail at all. Many cases exist where transformers remained in operation for several years after entering this end-of-life (EOL) state. However, once a transformer has reached this stage, its future performance may no longer be reliably estimated.<\/p>\n

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From a responsible operator’s point-of-view, the transformer is now beyond viable and calculable. At this point, it is a “gamble” where every extra day is a kind of “bonus.” Plenty of operators take this bet, and under certain conditions, this gamble may even be considered appropriate. However, the overall risk should remain a calculable risk, including the strong chance of fire in the event of catastrophic failure. At this stage, it\u2019s important to consistently monitor a transformer.<\/p>\n

Aging Rates<\/strong><\/h2>\n

Transformers age in different ways and at different rates. This is due to the interaction of various aging accelerators.<\/p>\n

Accelerators<\/strong><\/h2>\n