Design Optimization of Renewable Energy Systems Using Advanced Optimization Algorithms

✍ Scribed by Venkata Rao Ravipudi, Hameer Singh Keesari

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 395
• Series: Green Energy and Technology
• Category: Library

✦ Synopsis

This book describes applications of Jaya and Rao algorithms on real case studies concerning different renewable energy sources.

In the last few decades, researchers have focused on renewable energy resources like solar energy, bio-energy, wave energy, ocean thermal energy, tidal energy, geothermal energy, and wind energy. This has resulted in the development of new techniques and tools that could harvest energy from renewable energy sources. Many researchers and scientists have focused on developing and optimizing the energy systems to extract and utilize renewable energy more efficiently.

In this book, recently developed Jaya and Rao (Rao-1, Rao-2, and Rao-3) algorithms are introduced for single- and multi-objective optimization of selected renewable energy systems. The results of applications of the different versions of Jaya and Rao algorithms are compared with the other optimization techniques like GA, NSGA-II, PSO, MOPSO, ABC, etc., and the performance of the Jaya and Rao algorithms is highlighted compared to other optimization algorithms in the case of renewable energy systems.

The book also includes the validation of different versions of the Jaya and Rao algorithms through the application to complex single- and multi-objective unconstrained benchmark functions.

The algorithms and computer codes of different version of Jaya and Rao algorithms are included in the book that will be very much useful to readers in industry and academic research.

✦ Table of Contents

Preface
Contents
1 Introduction to Renewable Energy Systems
1.1 Solar Energy Systems
1.2 Wind Energy Systems
1.3 Hydroenergy Systems
1.4 Ocean Thermal Energy Systems
1.5 Geothermal Energy Systems
1.6 Bioenergy Systems
1.7 Nuclear Energy Systems
1.8 Other Emerging Renewable Energy Technologies
References
2 Selected Renewable Energy Systems and Formulation of Their Problems
2.1 Wind Farm Layout
2.1.1 Wake Model
2.1.2 Power Generation Model
2.1.3 Cost Model
2.1.4 Objective Function of the Wind Farm Layout Optimization
2.2 Solar Assisted Energy Systems
2.2.1 Solar-Assisted Brayton Heat Engine System
2.2.2 Solar-Assisted Stirling Heat Engine System
2.2.3 Solar-Assisted Carnot-Like Heat Engine System
2.3 Bio-Energy Systems
2.3.1 Single-Cylinder Direct-Injection Diesel Engine
2.3.2 Turbocharged DI Diesel Engine
2.3.3 Compression Ignition Biodiesel Engine with an EGR System
2.3.4 Microalgae-Based Biomass Cultivation Process
2.4 Hydro Energy and Geothermal Energy Systems
2.4.1 Hydropower Generation and Reservoir Operation
2.4.2 Ground Source Heat Pump-Radiant Ceiling Air Conditioning System
References
3 Advanced Engineering Optimization Techniques and Their Role in Energy Systems Optimization
References
4 Working of Jaya and Rao Optimization Algorithms and Their Variants
4.1 Working of the Jaya Algorithm and Its Modified Versions
4.1.1 Jaya Algorithm
4.1.2 Multi-team Perturbation-Guiding Jaya (MTPG-Jaya) Algorithm
4.1.3 Adaptive Multi-team Perturbation-Guiding Jaya (AMTPG-Jaya) Algorithm
4.1.4 Multi-objective Jaya and Multi-objective AMTPG-Jaya Algorithms
4.2 Working of the Rao Algorithms and Their Modified Versions
4.2.1 Rao Algorithms
4.2.2 Multi-objective Rao Algorithms
4.2.3 Elitist Rao Algorithms
4.2.4 Multi-objective Elitist Rao Algorithms
4.2.5 Self-Adaptive Population Rao (SAP-Rao) Algorithm
4.2.6 Multi-objective SAP-Rao Algorithms
4.3 Performance Indicators
4.3.1 Coverage
4.3.2 Spacing
4.3.3 Hypervolume
4.3.4 Inverted Generational Distance (IGD)
4.4 Computational Results Analysis on Single-objective Optimization of Unconstrained Benchmark Problems
4.4.1 Computational Results Analysis on 30 Unconstrained Standard Benchmark Problems
4.4.2 Computational Results Analysis on Unconstrained Unimodal and Multimodal Standard Benchmark Problems
4.5 Computational Results Analysis on Multi-objective Optimization Benchmark Problems
References
5 Multi-attribute Decision-Making Methods and Their Implementation in Energy Systems
5.1 Simple Additive Weighing (SAW)
5.2 Weighted Product Method (WPM)
5.3 Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE)
5.4 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
5.5 Modified TOPSIS (MTOPSIS)
5.6 Compromise Ranking Method (VIKOR)
5.7 Complex Proportional Assessment (COPRAS)
5.8 Gray Relational Analysis (GRA)
References
6 Optimization of Wind Farm Layouts
6.1 Problem Definition and Wind Scenarios of the Wind Farm Layout Optimization
6.2 Case-I: Fixed Wind Speed and Fixed Direction
6.3 Case-II: Fixed Wind Speed and Variable Wind Direction
6.4 Case-III: Fixed Wind Speed and Variable Wind Direction
References
7 Optimization of the Selected Solar-Assisted Energy Systems
7.1 Optimization of a Solar-Assisted Brayton Heat Engine System
7.2 Optimization of a Solar-Assisted Stirling Heat Engine System
7.2.1 Case Study-1
7.2.2 Case Study-2
7.2.3 Case Study-3
7.3 Optimization of a Solar-Assisted Carnot-like Heat Engine System
References
8 Optimization of the Selected Bio-Energy Systems
8.1 Design Optimization of the Single-Cylinder Direct-Injection Diesel Engine
8.2 Design Optimization of a Turbocharged DI Diesel Engine
8.3 Design Optimization of a Compression Ignition Biodiesel Engine with an EGR System
8.4 Process Optimization of a Microalgae-Based Biomass Cultivation Process
References
9 Optimization of Hydroenergy and Geothermal Energy Systems
9.1 Optimization of a Hydropower Generation System
9.2 Optimization of a Ground Source Heat Pump-Radiant Ceiling Air Conditioning System
References
Appendices
Appendix A. Single-objective Optimization of Standard Benchmark Problems
Appendix A.1. Unconstrained Standard Benchmark Problems
Appendix A.2. Unimodal and Multimodal Benchmark Problems Set-1
Appendix A.3. Unimodal and Multimodal Benchmark Problems Set-2
Appendix B. Multi-objective Optimization Standard Benchmark Problems
Multi-objective Optimization ZDT Test Problems
Appendix C. Codes for Jaya and Rao Algorithms (and their improved versions) for Unconstrained Optimization Problems
C.1 AllAlgorithmsMain.m: Main Program for Executing All Algorithms
C.2 singleobj.m: Jaya and Rao Algorithm Programs
C.3 ERaosingleobj.m: Elitist Rao Algorithm Programs
C.4 SAPRaosingleobj.m: Self-Adaptive Population Rao Algorithm Program
C.5 MTPG singleobj.m: MTPG-Jaya Algorithm Program
C.6 AMTPGsingleobj.m: MTPG-Jaya Algorithm Program
C.7 Unconstrainedbenchmarkfunc.m: 30 Unconstrained Benchmark Function Program
C.8 DandBounds.m: 30 Unconstrained Benchmark Function Variable Dimensions and Their Boundary Programs
Index