{"id":10576,"date":"2026-08-29T23:42:56","date_gmt":"2026-08-29T15:42:56","guid":{"rendered":"https:\/\/q8bbzjnpm5.wpdns.site\/?p=10576"},"modified":"2026-08-29T23:42:56","modified_gmt":"2026-08-29T15:42:56","slug":"transformer-operation-and-maintenance-strategy-based-on-life-cycl","status":"publish","type":"post","link":"https:\/\/subian-electric.com\/fr\/news\/transformer-operation-and-maintenance-strategy-based-on-life-cycl\/","title":{"rendered":"Strat\u00e9gie d'Op\u00e9ration et de Maintenance des Transformateurs Bas\u00e9e sur la Gestion du Cycle de Vie"},"content":{"rendered":"

An asset manager is currently evaluating its 400-transformer fleet\u2019s O&M budget, which needs to be slashed by 15 percent as per the direction of its board. The objective is not going to be easy, however, since there are no changes to make to the reliability targets. One is inclined to reduce oil sampling, skip certain overhauls, and make some other similar moves in the name of thrifty budget management; however, the asset manager is aware from his experience how things go differently in the longer term \u2013 the summed-up gains from maintenance are quickly translated to corresponding losses, which will hit in three to five years, when emergency replacements would cost the asset manager more than the amount saved. The alternative is to introduce lifecycle maintenance strategy, which takes into account total costs for each maintenance measure for 30\u201340 years\u2019 life span of the equipment.<\/p>\n

Your guide will help to get familiarity with how to design and execute the O&M strategy, which will result in the lowest TCO for a fleet of transformers. You will learn how to organize TCO computation, apply failure data and condition data in order to concentrate the spending on maintenance measures that will bring the highest gains over the life span of the equipment.<\/p>\n

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The Framework of TCO<\/h2>\n

Life-cycle costing, also known as total cost of ownership, refers to the total costs incurred for a piece of equipment right from the time of its purchase till the time of its disposal. In the case of transformers, the TCO formula is expressed in the following manner:<\/p>\n

TCO = Acquisition cost + Energy loss cost + O&M cost + Failure risk cost + Decommissioning cost<\/p>\n

Each of these variables has its own characteristics. Acquisition cost is of a one-time character. The energy loss cost is calculated in terms of the current values of losses incurred by the asset during its periods of operation. The other variables are as follows: O&M costs are charges incurred for regular annual maintenance of the transformers, whereas failure risk cost is the expected cost incurred as a result of transformer failure. Decommission cost implies oil disposal and dismantlement of transformer and tank.<\/p>\n

The major conclusion drawn from the comparison of these costs is that the values of these costs have a major difference from those predicted. In the case of a typical power transformer, the energy loss cost during a 30-year period amounts to a figure of 2-5 times higher than the original acquisition price, while the failure risk costs may also be equal or higher than the acquisition price. Therefore, any approach that optimizes either acquisition price or maintenance costs only is considered inappropriate.<\/p>\n

Where the Money Goes: TCO Breakdown by Component<\/h2>\n

Published lifecycle analyses and utility operations give consistent information about where transformer money is spent. The precise breakdown varies according to rated power, loss, electricity tariffs, and discount rates, but the following pattern can be viewed as representative for a medium transformer.<\/p>\n\n\n\n\n\n\n\n\n\n
Composant de co\u00fbt<\/th>\nTypical Share of TCO<\/th>\nTypical Absolute Range (10 MVA unit)<\/th>\nControllable?<\/th>\n<\/tr>\n<\/thead>\n
Acquisition (purchase + install)<\/td>\n5\u201315%<\/td>\n$90,000\u2013$280,000<\/td>\nAt purchase; includes loss trade-offs<\/td>\n<\/tr>\n
Energy losses (present value, 30 yr)<\/td>\n50\u201370%<\/td>\n$250,000\u2013$1.2 million<\/td>\nYes: loss specification, loading discipline<\/td>\n<\/tr>\n
Maintenance (routine + periodic)<\/td>\n10\u201320%<\/td>\n$60,000\u2013$200,000 over life<\/td>\nYes: condition-based targeting<\/td>\n<\/tr>\n
Failure risk (expected value)<\/td>\n5\u201315%<\/td>\n$30,000\u2013$300,000<\/td>\nYes: monitoring, protection, overhauls<\/td>\n<\/tr>\n
Decommissioning and disposal<\/td>\n1\u20133%<\/td>\n$10,000\u2013$50,000<\/td>\nPartly: oil and waste management<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The takeaway is that losses prevail. A 10 kW difference in no-load loss translates into a value of $30,000 based on $3,000 per kW in today\u2019s dollars, an amount which is equivalent to several years of maintenance expenditure. A TCO-oriented approach therefore considers both loss specification and loading in equal measure to maintenance activities.<\/p>\n

O&M Strategy Options: Reactive, Preventive, Predictive, RCM<\/h2>\n

O&M strategies exist on a spectrum, and each has a cost profile:<\/p>\n\n\n\n\n\n\n\n\n
Strategy<\/th>\nApproche<\/th>\nRelative O&M Cost<\/th>\nFailure Risk<\/th>\nMeilleur pour<\/th>\n<\/tr>\n<\/thead>\n
Reactive (run-to-failure)<\/td>\nFix only when it fails<\/td>\nLowest maintenance, highest failure cost<\/td>\n\u00c9lev\u00e9<\/td>\nLow-criticality, cheap, replaceable units<\/td>\n<\/tr>\n
Preventive (calendar-based)<\/td>\nFixed-interval tests and overhauls<\/td>\nMedium; wasteful on healthy units<\/td>\nMedium<\/td>\nLegacy fleets without condition data<\/td>\n<\/tr>\n
Predictive (condition-based)<\/td>\nTests and actions driven by condition<\/td>\nMedium; targeted spending<\/td>\nPlus bas<\/td>\nMedium and critical units with DGA programs<\/td>\n<\/tr>\n
Reliability-centered (RCM)<\/td>\nFailure mode analysis per unit<\/td>\nOptimized; highest engineering effort<\/td>\nLowest<\/td>\nCritical transmission assets<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The majority of fleets find that the hybrid approach to TCO is most effective, whereby the bulk of units are maintained through predictive\/condition maintenance while reactive maintenance is only suited to low-value units, and RCM methodology is implemented in a few exceptional units where loss would be devastating. The strength of this approach lies in the segmentation, rather than a one-size-fits-all approach to application.<\/p>\n

Condition-Based Maintenance in Practice<\/h2>\n

Condition-based maintenance (CBM) is the principle of a TCO-based maintenance system since it aims to invest in maintenance only in areas where wear is present. Techniques used in practice with their cost values:<\/p>\n

– DGA following IEEE C57.104\/IEC 60599 standard is around $200-500 per sample. Samples are done once a year as baseline and more frequently if there are any increases in gas value. This is the most valuable test calculated in terms of money spent.
\n– Oil quality tests: breakdown voltage, moisture, acidity test provide a package of services costing $150-400, providing contamination detection before it leads to insulation failure.
\n– Electrical tests: insulation resistance, ratio, winding resistance tests costing $300-1500 per unit per cycle help to detect winding and insulation deterioration.
\n– Partial discharge tests as in case of critical units or if DGA shows that any discharge activity is taking place, costs between $1500 and $8000 per unit.
\n– Online monitoring costing between $25000 and $120000 per critical unit is applicable in those cases when the cost of maintenance downtime justifies the expenses.<\/p>\n

The meaning of CBM rule is very clear: one should spend the minimum amount needed for testing to keep the level of uncertainty about the unit’s state acceptable and then use the data for actions. The result of using the CBM across all the equipment is usually the total maintenance costs decrease by 15-30% compared to the preventive maintenance and lower downtimes.<\/p>\n

Economic Decision Rules: Repair, Retire, or Replace<\/h2>\n

All important discoveries call for the same economic question: whether to fix, quit, or substitute the work of an object. A determination must be made about whether the alternatives are cheaper over their entire life cycle.<\/p>\n

Calculate the costs for every possible option in present value: repair price and the cost of maintenance and risk of failure over its remaining life; replacement cost (new equipment and additional losses and maintenance) less the scrap price of old equipment.
\nCap losses to $2,000\u2013$7,000\/kW no-load power and $500\u2013$1,500\/kW load. An old high-loss unit may typically cost more to operate than to replace even if it is still functional because the cost of loss is higher than that of the replacement.
\nApply 50\u201370% rule: if repairs cost more than 50\u201370% of replacement costs, or if repair entails high risk of subsequent failures, it is better to replace old equipment.
\nBear in mind that remaining life is an important factor: a serviced 10-year equipment will usually be repaired; a 35-year old device with duly confirmed paper aging will traditionally be replaced even if repair costs less today.
\nBear in mind the outage value for the sake of importance: for critical units, replacement costs may be justified on the assumption that a new unit has lower failure chance even if the arithmetic remains balanced.<\/p>\n

One should notice that the application of those rules by utility companies shows that so-called premature retirement of old high-loss units is, in fact, the best solution in terms of total cost of ownership since the new-one loss savings cover most of the costs of replacement. An example based on a simplified 10 MVA comparison for 25 years is given below.<\/p>\n\n\n\n\n\n\n\n\n\n
Item (10 MVA unit, 25-year horizon)<\/th>\nKeep Old Unit<\/th>\nReplace with New<\/th>\n<\/tr>\n<\/thead>\n
Pertes \u00e0 vide<\/td>\n25 kW<\/td>\n12 kW<\/td>\n<\/tr>\n
Capitalized loss value ($3,000\/kW)<\/td>\n$75,000<\/td>\n$36,000<\/td>\n<\/tr>\n
Annual maintenance<\/td>\n$8,000, rising<\/td>\n$3,000<\/td>\n<\/tr>\n
Replacement capital<\/td>\n\u2014<\/td>\n$150,000<\/td>\n<\/tr>\n
Failure risk<\/td>\nRising, 2\u20135%\/yr<\/td>\n0.5\u20131%\/yr<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The Transformer Life Cycle and Cost Traps at Each Stage<\/h2>\n

Each stage of the transformer life cycle has its own cost trap:<\/p>\n\n\n\n\n\n\n\n\n\n\n
Stage<\/th>\nTypical Duration<\/th>\nMain Cost Trap<\/th>\nTCO-Based Countermeasure<\/th>\n<\/tr>\n<\/thead>\n
Procurement<\/td>\n3\u20139 months<\/td>\nBuying on price alone; high-loss units lock in decades of cost<\/td>\nEvaluate capitalized losses in the tender<\/td>\n<\/tr>\n
Commissioning<\/td>\nJours \u00e0 semaines<\/td>\nRushed installation, skipped tests, wet oil accepted<\/td>\nInsist on full commissioning tests and oil criteria<\/td>\n<\/tr>\n
Early life (0\u20135 yr)<\/td>\n5 years<\/td>\nInfant failures from workmanship; no baseline DGA<\/td>\nBaseline DGA at months 6 and 18, warranty tracking<\/td>\n<\/tr>\n
Mid-life (5\u201320 yr)<\/td>\n15 years<\/td>\nComplacency; sampling stretched, trends missed<\/td>\nCondition-based testing with rate-of-rise alarms<\/td>\n<\/tr>\n
Late life (20\u201340 yr)<\/td>\n20 years<\/td>\nUndue preservation of obsolete, high-loss units<\/td>\nReplacement analysis with capitalized losses<\/td>\n<\/tr>\n
Fin de vie<\/td>\n\u2014<\/td>\nImproper oil disposal and site contamination<\/td>\nPlan disposal with oil recycling and material recovery<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Fleet-Level Budgeting and Prioritization<\/h2>\n

A TCO strategy functions on the fleet level, where risk and budget intersect. The practical approach is the following:
\nSegment the fleet based on the levels of criticality (loss impact), condition, age, loss, etc. Calculate condition score for each asset using DGA, oil analysis, electrical tests, age and load tracking (annually updated). Rank the assets based on risk = condition score \u00d7 criticality \u00d7 loss consequence. Distribute O&M budget along ranked positions (e.g. full monitoring for top tier, annual DGA for middle tier and longer time for low risk tail) to create a queue of replacements from the worst condition, most expensive losses according to saved costs from the maintenance budget<\/p>\n

A three-tier segmentation keeps the budget proportionate to risk:<\/p>\n\n\n\n\n\n\n\n
Tier<\/th>\nCriticality<\/th>\nMonitoring Level<\/th>\nTesting Frequency<\/th>\nShare of O&M Budget<\/th>\n<\/tr>\n<\/thead>\n
1<\/td>\nHighest (transmission, revenue)<\/td>\nOnline suite<\/td>\nContinuous + annual lab<\/td>\n40\u201350%<\/td>\n<\/tr>\n
2<\/td>\nMedium (distribution substations)<\/td>\nAnnual DGA<\/td>\nAnnual; semi-annual if abnormal<\/td>\n30\u201340%<\/td>\n<\/tr>\n
3<\/td>\nLow (non-critical, redundant)<\/td>\nBasic oil test<\/td>\nEvery 2\u20133 years<\/td>\n10\u201320%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This approach lets a utility defend every dollar: spending follows risk, and the top of the queue is always the unit with the worst combination of condition and consequence.<\/p>\n

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Data Requirements for a TCO-Based Strategy<\/h2>\n

No matter how clever the drawn design is, it cannot be implemented without data. Here is the minimum activity under the transformer:<\/p>\n

1. Asset identity: rating,voltages, manufacturer, commissioning date, serial number.
\n2. Losses: specified and measured no load and load losses.
\n3. History: all DGA records, oil quality, and electrical test results as well as repairs and events of overload with dates and conditions.
\n4. Load profile: peak load, loading factor, or at least peak per year and delivered energy.
\n5. Records of failures and outages with causes.
\n6. Cost data: acquisition, maintenance costs, outages.<\/p>\n

Implementing the Strategy: A 6-Step Roadmap<\/h2>\n

Creation of a data foundation: Combine asset records and test records into a single system and fill the gaps using initial sampling over a period of 12-18 months.
\nSegmentation and calculating: Define the importance and measure state scores for the fleet as a whole.
\nDefining thresholds and responses: Use IEEE C57.104 \/ IEC 60599 standards for measurement thresholds with different levels of response and responsible persons.
\nTransitioning to a hybrid model: Instead of fixed intervals, apply frequency of testing based on risks.
\nConducting replacements: Apply calculated losses and the review of rules on when to repair units with very high rates of loss.
\nAnnual analysis: Reveal results of predicted actions as compared with real ones and adjust the thresholds.<\/p>\n

Cost Pitfalls and How to Avoid Them<\/h2>\n