Artificial Intelligence for Renewable Energy Systems

9 Chapter 9Figure 9.1 AMI architecture.

10 Chapter 10Figure 10.1 Traditional RNN unrolled over t timesteps [12].Figure 10.2 LSTM cell [16].Figure 10.3 GRU cell [12].Figure 10.4 ConvLSTM cell.Figure 10.5 Bidirectional RNN.Figure 10.6 Demonstration of the sliding window approach.Figure 10.7 Predictions done by models trained with window size = 6.

11 Chapter 11Figure 11.1 Classification of biofuels.Figure 11.2 AI-based biodiesel model.

1 Chapter 1 Table 1.1 Eigenvalues of six-phase synchronous generator. Table 1.2 Eigenvalues of three-phase synchronous generator.

2 Chapter 4Table 4.1 Some important applications of ANN technology for the development of b...Table 4.2 Some important applications of combination of artificial neural networ...

3 Chapter 5Table 5.1 Brief summary of current research in battery energy storage systems.Table 5.2 Model parameters for SoC estimation [20].Table 5.3 Performance metrics for regression models.

4 Chapter 6Table 6.1 Models for multi-step wind forecasting.Table 6.2 Ensemble models for WPF.Table 6.3 Miscellaneous DL models for WF.

5 Chapter 8Table 8.1 Comparison of the methodologies with the parameters.

6 Chapter 10Table 10.1 Training and test size for generated dataset from each window size.Table 10.2 Performance of all trained models.Table 10.3 Statistical analysis of the prediction done by LSTM model ( widow size ...

1 Cover

2 Table of Contents

3 Title Page

4 Copyright

5 Preface

6 Begin Reading

7 Index

8 End User License Agreement

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Scrivener Publishing100 Cummings Center, Suite 541J Beverly, MA 01915-6106

Artificial Intelligence and Soft Computing for Industrial Transformation

Series Editor: Dr. S. Balamurugan (sbnbala@gmail.com)

Scope: Artificial Intelligence and Soft Computing Techniques play an impeccable role in industrial transformation. The topics to be covered in this book series include Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithms, Particle Swarm Optimization, Evolutionary Algorithms, Nature Inspired Algorithms, Simulated Annealing, Metaheuristics, Cuckoo Search, Firefly Optimization, Bio-inspired Algorithms, Ant Colony Optimization, Heuristic Search Techniques, Reinforcement Learning, Inductive Learning, Statistical Learning, Supervised and Unsupervised Learning, Association Learning and Clustering, Reasoning, Support Vector Machine, Differential Evolution Algorithms, Expert Systems, Neuro Fuzzy Hybrid Systems, Genetic Neuro Hybrid Systems, Genetic Fuzzy Hybrid Systems and other Hybridized Soft Computing Techniques and their applications for Industrial Transformation. The book series is aimed to provide comprehensive handbooks and reference books for the benefit of scientists, research scholars, students and industry professional working towards next generation industrial transformation.

Publishers at Scrivener Martin Scrivener ( martin@scrivenerpublishing.com) Phillip Carmical ( pcarmical@scrivenerpublishing.com)

Edited by

Ajay Kumar Vyas

S. Balamurugan

Kamal Kant Hiran

and

Harsh S. Dhiman

This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

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