BIBFRAME Work

Title

Evolutionary Wind Turbine Placement Optimization with Geographical Constraints

Type

  • Text
  • Monograph

Contribution

Lückehe, Daniel (aut)

Subject

Language

Classification

Content

Summary

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.

Table of Contents

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

Authorized Access Point

Lückehe, Daniel. Evolutionary Wind Turbine Placement Optimization with Geographical Constraints

Admin Metadata

  • Date: 2026-09-11T20:13:20.236299+00:00
  • Agent: cbc
  • Status: c
  • Derived from: 21771627

Admin Metadata

  • Date: 2026-09-11
  • Cataloger id: Unknown
  • Description level: http://id.loc.gov/ontologies/bibframe-2-6-0/
  • Description language: eng
  • Description authentication: pcc

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