Abstract
In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.
Highlights
At present, as a result of the constant grown of societies, the physical assets on electric power systems suffer a continuous demand for high system reliability, power quality and cost benefits
Different methodologies have been developed to assess the condition of power transformers (PT), mostly known as health indices (HI) [6,7,8], and when the importance of the unit or the consequences of failure is taken into account, the assessment methodology is known as risk index (RI)
The main goal of the RI outcome is to serve as an indicator of the need of acting either in maintenance or inspection, especially when the company has adopted a scheme of reliability-based maintenance (RBM) and/or condition-based maintenance (CBM) [10]
Summary
As a result of the constant grown of societies, the physical assets on electric power systems suffer a continuous demand for high system reliability, power quality and cost benefits. An asset manager needs to justify all the maintenance or replacement decisions To achieve this goal, it is necessary to count on reliable information about the condition and the importance of the unit in the context of the whole system. As for the strategic importance of the unit, it is necessary to know technical and operative characteristics, such as loading, geographic location, or the existence of critical loads Once this information has been obtained, the acquired data need to be processed in a way that enables the asset manager to draw conclusions about the state of the unit. When dealing with a set of transformers, more than a ranking, an asset manager needs to categorize the units in groups with similar characteristics to apply maintenance actions.
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