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Evolutionary Wind Turbine Placement Optimization with Geographical Constraints [Paperback]

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  • Category: Books (Computers)
  • Author:  L?ckehe, Daniel
  • Author:  L?ckehe, Daniel
  • ISBN-10:  3658184647
  • ISBN-10:  3658184647
  • ISBN-13:  9783658184643
  • ISBN-13:  9783658184643
  • Publisher:  Springer Vieweg
  • Publisher:  Springer Vieweg
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Apr-2017
  • Pub Date:  01-Apr-2017
  • SKU:  3658184647-11-SPRI
  • SKU:  3658184647-11-SPRI
  • Item ID: 100964030
  • List Price: $54.99
  • Seller: ShopSpell
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  • Delivery by: Dec 04 to Dec 06
  • Notes: Brand New Book. Order Now.

Daniel L?ckehe 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. 

 

Solving Optimization Problems.- Wind Prediction Model.- Geographical Planning Scenarios.- Constrained Placement Optimization.- Constraint Handling with Penalty Functions.- Advanced Evolutionary Heuristics.

Dr. Daniel L?ckehe 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.

Daniel L?ckehe 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.&lCĪ