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Genetic Optimization Techniques for Sizing and Management of Modern Power Systems

Om Genetic Optimization Techniques for Sizing and Management of Modern Power Systems

Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms. The work is suitable for researchers and practitioners working in power systems optimization requiring information for systems planning purposes, seeking knowledge on mathematical models available for simulation and assessment, and relevant applications in energy policy.

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  • Språk:
  • Ukjent
  • ISBN:
  • 9780128238899
  • Bindende:
  • Paperback
  • Sider:
  • 350
  • Utgitt:
  • 29. september 2022
  • Dimensjoner:
  • 227x21x152 mm.
  • Vekt:
  • 588 g.
  På lager
Leveringstid: 4-8 virkedager
Forventet levering: 30. desember 2024
Utvidet returrett til 31. januar 2025
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Beskrivelse av Genetic Optimization Techniques for Sizing and Management of Modern Power Systems

Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms. The work is suitable for researchers and practitioners working in power systems optimization requiring information for systems planning purposes, seeking knowledge on mathematical models available for simulation and assessment, and relevant applications in energy policy.

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