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 HeuristicsTarget Groups
Lecturers and students of computer science, especially in optimization methods and renewable energies
Natural scientists interested in advanced heuristicsThe AuthorDr. 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.

Autorentext

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.

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