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Neural Networks
Book chapter

Neural Networks

Dagmar Niebur, Ganesh Kumar Venayagamoorthy and Ekrem Gursoy
Advanced Solutions in Power Systems: HVDC, FACTS, and Artificial Intelligence, pp 755-783
26 Sep 2016
DOI: https://doi.org/10.1002/9781119175391.ch16

Abstract

artificial neurons electric load forecasting generation scheduling neural net applications neural networks nonlinear power system renewable energy systems signal processing system synchronous machine control
Neural networks (NNs), also called artificial neural systems, neurocomputers, parallel distributed processors, or connectionist models, are an attempt to mimic at least partially the structure and functions of brains and nervous systems of living creatures. An NN is information or signal processing system composed of a large number of simple processing elements, called artificial neurons or simply nodes, which are interconnected by direct links which cooperate to perform parallel distributed processing in order to solve a desired computational task. This chapter presents an overview on neural net applications with recent and specialized reviews of the areas of neural nets for electric load forecasting. It reviews applications to synchronous machine control, renewable energy systems, and generation scheduling. The chapter introduces several NN models for nonlinear power system monitoring, identification, and control. The model provides an approximation or a classification in a certain function space of the unknown mapping between input vector and output variables.

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