Optimal utilization of power transformers through virtual sensing

Abstract

Power transformers are the most critical and expensive assets for utility companies and are expected to last for at-least 30-40 years. Unfortunately, many of them have failed before reaching their rated life. In order to prevent such premature failures, utility companies usually deploy real time asset management system by installing thermal sensors (e.g. fiber-optical sensor) inside the tank of large transformers (∼500MVA). However, being expensive, sensor deployment may not be commercially viable for small and medium size (<=250MVA) transformers. This paper proposes an asset management scheme of such power transformers through virtual (sensor-less) sensing. It simulates transformer internal heating phenomena (like hot-spot temperature, insulation aging, loss of life, etc.) using easily available SCADA measurements, ambient temperature from on-line weather forecast, and transformer assets data. It predicts future load and incentive and optimizes transformer operation by analyzing the economic incentive for carrying power and payoff for the loss of life calculated from virtual sensing. Proposed scheme is evaluated and implemented in Fortum's transformers in Finland and experimental results are presented. © 2013 IEEE.