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Nature Inspired Optimization for Electrical Power System

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Cover of 'Nature Inspired Optimization for Electrical Power System'

Table of Contents

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    Book Overview
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    Chapter 1 Teaching-Learning-Based Optimization for Static and Dynamic Load Dispatch
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    Chapter 2 Application of Elitist Teacher–Learner-Based Optimization Algorithm for Congestion Management
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    Chapter 3 PSO-Based Optimization of Levelized Cost of Energy for Hybrid Renewable Energy System
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    Chapter 4 PSO-Based PID Controller Designing for LFC of Single Area Electrical Power Network
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    Chapter 5 Combined Economic Emission Dispatch of Hybrid Thermal PV System Using Artificial Bee Colony Optimization
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    Chapter 6 Dynamic Scheduling of Energy Resources in Microgrid Using Grey Wolf Optimization
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    Chapter 7 Mixed-Integer Differential Evolution Algorithm for Optimal Static/Dynamic Scheduling of a Microgrid with Mixed Generation
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    Chapter 8 NSGA-II Based Reactive Power Management in Radial Distribution System Integrated with DGs
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    Chapter 9 Short-Term Hydrothermal Scheduling Using Bio-inspired Computing: A Review
Attention for Chapter 2: Application of Elitist Teacher–Learner-Based Optimization Algorithm for Congestion Management
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Chapter title
Application of Elitist Teacher–Learner-Based Optimization Algorithm for Congestion Management
Chapter number 2
Book title
Nature Inspired Optimization for Electrical Power System
Published by
Springer, Singapore, January 2020
DOI 10.1007/978-981-15-4004-2_2
Book ISBNs
978-9-81-154003-5, 978-9-81-154004-2
Authors

Rupali Parmar, Sulochana Wadhwani, Manjaree Pandit, Parmar, Rupali, Wadhwani, Sulochana, Pandit, Manjaree

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