The Influence of Heat Loss on Wind Generators to Implement Condition-Monitoring System Based on the Application of the Polynomial Regression Model

This paper presents an application of a condition-monitoring system (CMS) based on a polynomial regression model (PRM) to study the influence of heat loss on a wind generator's temperatures. Monitoring the wind generator temperatures is a significant for efficient operation, and plays a key role in an effective CMS. Many techniques, including prediction models can be utilized to reliably forecast a wind generator's temperature during operation and avoid the occurrence of a failure. PRMs arewidely used in situations when the relationship between the response and the independent variables are curve-linear. These techniques can be used to construct a normal behavior model of an electrical generator's temperatures based on recorded data. Many independent variables affect a generator's temperature; however, the degree of influence ofeach independent variableonthe response is dissimilar. In many situations, adding a new independent variable to the model may cause unsatisfactory results; therefore, the selection of the variables should be very accurate. A generator's heat loss can be considered a significant independent variable that greatly influences the wind generator with respect to the other variables. A generator's heat loss can be estimated in intervals by analyzing the exchange in the heat between the hot and cold fluid through the heat exchangers of wind generators. A case study built on data collected from actual measurements demonstrates the adequacy of the proposed model.