A bi‐level optimization model and improved algorithm for wind farm layout

Abstract Wind farm can obtain the maximize profit by optimizing micro‐locations and cables. The factors that affect profit include the power output of wind turbines, cost and et al., where power output is affected by wake effect, cable cost is related to the length and type of collector cable. The profit is calculated on the premise that the costs and power loss of collector cable are determined. Obviously, there is a hierarchical relationship between the above problems. Therefore, a bi‐level optimization model with constraints is constructed in this paper, where the upper‐level objective function is the maximum profit, and the lower‐level objective functions are consists of minimum the cable cost and the power loss of collector cable; Moreover, an improved algorithm (IDEDA), based on differential evolution and Dijkstra, is used to optimize above model; Finally, simulation experiments are carried out for IDEDA and four algorithms for two different wind conditions, and the results show that IDEDA performs better compared to the other four algorithms in terms of profit and cable cost.

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Publication Details

Journal
IET Renewable Power Generation
Published
2024-08-29
DOI
https://doi.org/10.1049/rpg2.13005
Citations
1
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
1.30

Funders

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article

A bi‐level optimization model and improved algorithm for wind farm layout

Erping Song
1 citations
IET Renewable Power Generation
Wind Energy Research and Development
1.30
article

A bi‐level optimization model and improved algorithm for wind farm layout

Erping Song
article en
1 citations

Abstract

Abstract Wind farm can obtain the maximize profit by optimizing micro‐locations and cables. The factors that affect profit include the power output of wind turbines, cost and et al., where power output is affected by wake effect, cable cost is related to the length and type of collector cable. The profit is calculated on the premise that the costs and power loss of collector cable are determined. Obviously, there is a hierarchical relationship between the above problems. Therefore, a bi‐level optimization model with constraints is constructed in this paper, where the upper‐level objective function is the maximum profit, and the lower‐level objective functions are consists of minimum the cable cost and the power loss of collector cable; Moreover, an improved algorithm (IDEDA), based on differential evolution and Dijkstra, is used to optimize above model; Finally, simulation experiments are carried out for IDEDA and four algorithms for two different wind conditions, and the results show that IDEDA performs better compared to the other four algorithms in terms of profit and cable cost.

IET Renewable Power GenerationVol. 18(13)
Qinghai University (CN)
Qinghai University
Affordable and clean energy
Openalex Percentile: Top 13%
Wind Energy Research and Development
1.30
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