An Advanced Modeling System for Optimization of Wind Farm Layout and Wind Turbine Sizing Using a Multi-Level Extended Pattern Search Algorithm

Patrick Moriarty, Bryony DuPont, Jonathan Cagan

Research output: Contribution to journalArticlepeer-review

67 Scopus Citations

Abstract

This paper presents a system of modeling advances that can be applied in the computational optimization of wind plants. These modeling advances include accurate cost and power modeling, partial wake interaction, and the effects of varying atmospheric stability. To validate the use of this advanced modeling system, it is employed within an Extended Pattern Search (EPS)-Multi-Agent System (MAS) optimization approach for multiple wind scenarios. The wind farm layout optimization problem involves optimizing the position and size of wind turbines such that the aerodynamic effects of upstream turbines are reduced, which increases the effective wind speed and resultant power at each turbine. The EPS-MAS optimization algorithm employs a profit objective, and an overarching search determines individual turbine positions, with a concurrent EPS-MAS determining the optimal hub height and rotor diameter for each turbine. Two wind cases are considered: (1) constant, unidirectional wind, and (2) three discrete wind speeds and varying wind directions, each of which have a probability of occurrence. Results show the advantages of applying the series of advanced models compared to previous application of an EPS with less advanced models to wind farm layout optimization, and imply best practices for computational optimization of wind farms with improved accuracy.

Original languageAmerican English
Pages (from-to)802-814
Number of pages13
JournalEnergy
Volume106
DOIs
StatePublished - 2016

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ltd.

NREL Publication Number

  • NREL/JA-5000-65632

Keywords

  • Extended pattern search algorithm
  • Systems optimization
  • Wind farm modeling
  • Wind farm optimization

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