Parameter Estimation for Multiple VSCs with Domain Adaptation

This chapter provides a brief introduction on deep learning (DL). It also provides a brief introduction on domain adaptation (DA). The chapter describes the tasks of parameter estimations of multiple voltage source converters. It prepares the reader with notations commonly used for DA. The chapter describes the models addressing the tasks of regression and classification of DA. It also describes how the training and test data are generated. The chapter introduces metrics for evaluating the performance of the models. It mainly addresses the problem of homogeneous supervised DA. The chapter discusses the results of various models for DA and describes the software required to run the codes. The code examples provided in this chapter are written in Python and MATLAB.