Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting - Lecture Notes in Electrical Engineering

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.

ISBN:	9789811964893
Publisher:	SPRINGER NATURE
Imprint:	Springer Nature Singapore
Published date:	02 Mar 2023
Language:	English
Number of pages:	280
Weight:	-1g
Height:	235mm
Width:	155mm

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