Evolutionary Wind Turbine Placement Optimization with Geographical Constraints - Softcover

Lückehe, Daniel

Softcover

ISBN 10: 3658184647 ISBN 13: 9783658184643

Verlag: Springer Vieweg, 2017

Inhaltsangabe

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. 

 

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Über die Autorin bzw. den Autor

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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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.

Details zur Ausgabe

• Verlag: Springer Vieweg
• Erscheinungsdatum: 2017
• Sprache: Englisch
• ISBN 10: 3658184647
• ISBN 13: 9783658184643
• Einband: Tapa blanda
• Auflage: 1
• Anzahl der Seiten: 220
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Deutschland