Non invasive procedure for performance evaluation of induction machines

Abstract

Renewable energy is gaining a wider importance due to the limited availability of fossil fuels, increasing demand and the threat of carbon prints. Wind energy is one of the most feasible and promising sources of renewable energy across the world. A rapid development in Wind Energy Conversion system has been observed since the 1990 s and various Wind Turbines and Wind Generators have been built. Wind Energy Conversion system has become a viable and reliable means for electric power generation. The use of Self-Excited Induction Generators (SEIG) in wind turbine is a common choice because it is superior to other kinds with wide range speed applications. It is simple and reliable, it has a rugged construction, it does not require a separate D.C source for excitation and it has an inherent overload protection, cost effective and requires less maintenance. However, it is essential to install sufficient number of induction generators, for the optimal usage of wind resources. It is also necessary to examine and monitor the performance of Induction Generator to ensure the fair use of wind energy conversion system. The analysis of the performance of such generators, therefore, is crucial and critical in terms of their design and operation. If the performance of induction generators is evaluated, well in advance, it is possible for the manufacturers to design an effective energy conversion system. A simplified non-invasive procedure is adopted for the first time using Circle Diagram Approach (CDA) and Radial Basis Function Neural Network (RBFNN) for analyzing the performance of Induction Generators. newline