Liam Warren, ABB’s UK transformer service operations manager, explains how a new approach to asset management can provide greater visibility and predictability for asset managers, enabling them to decide on the appropriate preventive maintenance plans and to target new investment for maximum effect.
Looking for the maximum return on fixed assets is part of everyday business - whether in the electricity utilities or general industry. Deregulation of the energy market and increasing pressure to reduce costs are forcing managers to look continually for ways to reduce the lifecycle costs of their installed assets and improve return on investment.
The situation is especially acute in the case of power transformers. A substantial proportion of the worldwide transformer population is nearing the end of its lifetime, and there is an urgent need to optimize transformer fleet performance through higher availability. Naturally, this has to be achieved at the lowest possible cost and with minimal environmental impact.
In the past, it was usual for asset-related decisions to be based primarily on accumulated experience. Capital expenditure was mostly trigged by high growth in energy demand and power assets were replaced by new and more powerful installations long before reaching the end of their useful lifecycle. But in today’s rapidly changing environment, with its severe technical and financial constraints, asset managers need to base their strategic decisions on precise and reliable data in order to convince the ultimate decision makers.
However, one of the most frequent challenges faced by transformer owners is the lack of reliable information on asset condition and the difficulty in defining improvements that are justified from both a financial and technical point of view. ABB’s Mature Transformer Management Programme (MTMP) is designed to fill that information gap. This methodology is based on four steps.
Step 1: tranformer fleet screening
Large transformer fleets (from 20 to over 100 units) are evaluated using readily available data such as type of application, time in operation, gas in oil, power factor, maintenance history and major events or experience with sister units.
The aim is to obtain a general ranking for the population, based on technical and economic criteria, and to identify clusters of units requiring further investigation or some basic maintenance.
This first-step screening also provides key information for estimating an outline budget for future maintenance or unit replacement, and identifies the units that should be given priority.
Step 2: transformer design and condition assessment
A smaller number of units (typically 10 to 20) are selected from Step 1 and modern design, testing and quality assurance tools are used to evaluate their design and construction. In addition, advanced diagnostic tests are performed to assess each of the principal properties of the transformer, including: mechanical condition, thermal condition (ageing of the insulation), electrical condition of the active parts and the condition of the accessories such as tap-changer(s), bushings, over-pressure valves, air-dryer system, pumps and relays.
This process provides important information about the condition and suitability of the units and enables the identification of the appropriate maintenance, repair or retrofit activity required to ensure their reliability.
Actions could include: listing of spare parts to be kept in stock, a prioritized list of on-site maintenance measures, and proposals to relocate units, decrease their load or replace them. Costs are reduced, as action is restricted to certain components and is only taken when it is really needed.
For example, if the actual condition of an ageing transformer is suitable for overloading but not for short-circuit operation, action could be focused on just improving the rigidity and clamping of the winding blocks.
Step 3: life assessment/profiling
Life assessment/profiling ranks the transformer population according to the evaluated reliability of each unit. Priority can then be given to taking corrective or preventive action on the most critical units to improve the overall reliability of the fleet and reduce the costs associated with the risk of unplanned outage.
Maintenance priorities are driven both by technical considerations related to the condition of the units and also the overall strategy of the company that owns the assets. Several asset management scenarios are therefore possible. An important criterion directly linked to the strategy of the asset owner is to minimize the lifecycle cost of the assets or the total cost of ownership.
ABB has taken the life assessment approach a stage further by working in conjunction with utility companies to develop a financial model that evaluates the lifecycle cost of a transformer fleet or individual unit over a given period. The model enables the end-user to derive the maximum value from the exercise and helps decision makers and asset owners identify the most financially efficient maintenance scenario.
Step 4: implementation of engineering solutions
Based on the results of this rigorous analysis programme, engineering solutions are identified to achieve risk reduction, life extension and the general health improvement of the fleet. These solutions include:
• preventive and corrective maintenance
• field repair and retrofit • relocation and transportation
• testing and advanced diagnostics
• factory repair • planned transformer replacement.
In addition to the traditional transformer maintenance and repair techniques, some new technologies are now being adopted, including on-line oil regeneration, on-site repair, low frequency heating and ‘better than new’.
On-line oil regeneration has demonstrated technical and economical advantages when applied to old transformers with aged acidic oil. It is more environmentally friendly than oil replacement and shows a much better efficiency over a long time.
ABB has developed an extremely efficient and cost-effective on-site repair service that effectively takes the factory to the transformer. It is ideal for remote locations where transportation is difficult and costly. However, on-site repair is also increasingly popular as a way of getting mission critical transformers back on line quickly, at a fraction of the cost and lead-time required to install a new replacement unit.
A low-frequency heating (LFH) system can dry transformer active parts much faster, without compromising quality. The remaining moisture content of the solid insulation is typically below one per cent. The drying time can be less than half that for a traditional hot oil and vacuum process. This reduction in lead-time when drying a wet transformer or repairing a failed unit on site could be vital. For operators who need to boost the power of their existing units, ABB offers a ‘better than new’ service under which coils are rewound with Nomex® high-temperature insulation material. This results in significant improvements in lifetime and reliability. As well as the cost advantages for the unit, side benefits include: lower environmental impact than scrapping, no construction needed to prepare the site (the footprint remains identical), and lower weight than conventional units.
Conclusion
The MTMP approach to asset management provides vital evidence to support transformer owners deciding whether to maintain or replace their fleet.
On a long-term strategic level, a significant benefit of such a study is that it provides a clear picture of the maintenance and renewal investments required over the next 20–30 years to deliver the required asset reliability and availability. It provides solid information to compare different asset management strategies and to select the approach that best supports the organization’s overall technical and financial strategy. A programme to extend the lifetime of aged units will, for example, postpone investments in new units and so improve the cash flow of the company.
In the medium term, asset managers can identify how best to use maintenance and replacement budgets. Funds can be allocated to units that show the best return on investment, while reducing technical and operational risks.
In the short term, the method enables the maintenance manager to quantify the costs and benefits of each planned maintenance action.