Multi-objective lightning search algorithm applied to wind farm layout optimization
Sinvaldo Rodrigues Moreno,
Juliano Pierezan,
Leandro dos Santos Coelho and
Viviana Cocco Mariani
Energy, 2021, vol. 216, issue C
Abstract:
The wind farm layout design is an expansive and complex task involving a wide knowledge. Usually, attention is given on high energy efficiency, considering as active constraints the energy loss due to wake effect. Nevertheless, future advancements have identified that highly efficient and maximum power can be formulated as a multiobjective optimization problem. Thus in this study is proposed a novel multi-objective based on lightning search algorithm (MO-LSA) to design the wind farm layout more efficiently, considering to minimize three objectives including the cost of annual energy production, the overall wind farm’s area, and the wake effect’ losses. Also, to develop a realistic model are applied concepts of the convex hull, to provide an accurate assessment related to the overall land area. Different wind speed scenarios are evaluated with constant and variable wind direction. To compare the performance from MO-LSA three multi-objective optimization algorithms from the literature were used. In terms of results, the MO-LSA provided the best Pareto front for the scenarios analyzed regarding the metrics applied to evaluate them, also with well-distributed solutions along of all searching space, reflecting in alternative wind park layouts with better efficiency in terms of power output and investment costs.
Keywords: Wind farm layout; Energy; Wake effect; Multi-objective optimization; Evolutionary algorithms (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220323215
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:216:y:2021:i:c:s0360544220323215
DOI: 10.1016/j.energy.2020.119214
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().