A comparison of optimizers in a unified standard for optimization on wind farm layout optimization. (1st February 2021)
- Record Type:
- Journal Article
- Title:
- A comparison of optimizers in a unified standard for optimization on wind farm layout optimization. (1st February 2021)
- Main Title:
- A comparison of optimizers in a unified standard for optimization on wind farm layout optimization
- Authors:
- Croonenbroeck, Carsten
Hennecke, David - Abstract:
- Abstract: Wind Farm Layout Optimization (WFLO) is a vivid field of research dealing with the difficult problem of optimally arranging a given number of wind turbines inside a local area (wind farm). There are several types of objective functions, varying optimization strategies, different sets of underlying data, assumptions and simplifications to the problem, among other issues making fair comparisons of problem solving techniques challenging. We discuss a new unified framework that provides highly accurate data, a modular approach to economically driven objective functions, and a unified and fair benchmark for mathematical optimizers that are easily plugged into that framework. Finally, we provide an exemplary work flow and use it to show a comparison study of optimizing techniques within the framework, focussing on types of optimizers frequently used in this field. Highlights: Using R package "wflo", we show a typical WFLO work flow. We run a selection of optimizers on a standardized WFLO environment. Genetic algorithms and simulated annealing perform best, but slow. WFLO researchers worldwide should use WFLO to have their contributions comparable.
- Is Part Of:
- Energy. Volume 216(2021)
- Journal:
- Energy
- Issue:
- Volume 216(2021)
- Issue Display:
- Volume 216, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 216
- Issue:
- 2021
- Issue Sort Value:
- 2021-0216-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-02-01
- Subjects:
- Wind energy -- WFLO -- Wind farm layout optimization -- Optimization -- NP-Hard -- R package -- Wake models -- Open data -- Genetic algorithm -- Benchmark
C61 -- C65 -- Q42
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2020.119244 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16055.xml