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© 2017

Evolutionary Wind Turbine Placement Optimization with Geographical Constraints

Book
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Table of contents

  1. Front Matter
    Pages I-XXII
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. Daniel Lückehe
      Pages 3-12
    3. Daniel Lückehe
      Pages 13-32
  3. Placement Model

    1. Front Matter
      Pages 33-33
    2. Daniel Lückehe
      Pages 35-53
    3. Daniel Lückehe
      Pages 55-70
  4. Constrained Placement Optimization

    1. Front Matter
      Pages 71-71
    2. Daniel Lückehe
      Pages 73-105
    3. Daniel Lückehe
      Pages 107-129
    4. Daniel Lückehe
      Pages 131-162
  5. Conclusions

    1. Front Matter
      Pages 163-163
    2. Daniel Lückehe
      Pages 165-175
  6. Back Matter
    Pages 177-195

About this book

Introduction

Daniel Lückehe presents different approaches to optimize locations of multiple wind turbines on a topographical map. The author succeeds in significantly improving placement solutions by employing optimization heuristics. He proposes various real-world scenarios that represent real planning situations. Advanced evolutionary heuristics for the turbine placement optimization create not only highly optimized solutions but also significantly different solutions to give decision-makers optimal choices. As a matter of fact, wind turbines play an important role towards green energy supply. An optimal location is essential to achieve the highest possible energy efficiency. 

Contents
  • Solving Optimization Problems
  • Wind Prediction Model 
  • Geographical Planning Scenarios
  • Constrained Placement Optimization
  • Constraint Handling with Penalty Functions
  • Advanced Evolutionary Heuristics
Target Groups
  • Lecturers and students of computer science, especially in optimization methods and renewable energies
  • Natural scientists interested in advanced heuristics
The Author
Dr. Daniel Lückehe defended his PhD thesis in the PhD program “System Integration of Renewable Energy” at the Carl von Ossietzky University in Oldenburg, Germany. As postdoctoral researcher he conducts research in computational health informatics at the Leibnitz University in Hanover, Germany.

Keywords

Algorithms Constraint Handling Penalty Functions Multimodal Computing Methodologies Evolutionary Algorithms Multimodal Optimization

Authors and affiliations

  1. 1.OldenburgGermany

About the authors

Dr. Daniel Lückehe defended his PhD thesis in the PhD program “System Integration of Renewable Energy” at the Carl von Ossietzky University in Oldenburg, Germany. As postdoctoral researcher he conducts research in computational health informatics at the Leibnitz University in Hanover, Germany.

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