Turbine siting in relation to wind speed: Insights from historical deployment patterns for energy system modeling

Wind turbine output heavily depends on the wind speed at the deployment site. Energy system optimization models (ESOMs) typically allocate turbines in a cost-optimal manner, leading to siting at the windiest locations. However, such allocation methods lack an empirical base and risk overestimating the cost-competitiveness of wind power compared to real-life. This study assesses the historical siting of onshore wind turbines with respect to wind speed across 25 regions and introduces a heuristic method to represent wind power deployment patterns within ESOMs. Additionally, we conduct a comprehensive evaluation of existing wind turbine allocation methods in ESOMs. Our results show that turbines are typically sited at locations with slightly higher wind speeds than the regional mean, and new turbines within each region are consistently placed at sites with similar average wind speeds each year. The heuristics that best match historical deployment patterns tend to allocate 80–100 % of wind capacity to the 70th to 90th percentiles of the windiest areas. The cost-optimal turbine siting approach consistently favors windier locations compared to historical deployment. Overall, the findings present a promising avenue for incorporating historical data to improve the representation of wind power in future energy system modeling. • Most turbines are deployed at sites with wind speeds higher than the regional mean. • Wind turbines are sited at similar average wind speeds over time. • Heuristics based on historical data site wind capacity in the 70–90 % windiest areas. • Cost-optimal siting of turbines in ESOMs deviates from historical deployment.

Authors

Institutions

Publication Details

Journal
Energy Strategy Reviews
Published
2025-11-01
DOI
https://doi.org/10.1016/j.esr.2025.101990
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Turbine siting in relation to wind speed: Insights from historical deployment patterns for energy system modeling

Fredrik Hedenus, Xiaoming Kan, Niklas Jakobsson, Yodefia Rahmad et al.
Energy Strategy Reviews
Integrated Energy Systems Optimization
article

Turbine siting in relation to wind speed: Insights from historical deployment patterns for energy system modeling

Fredrik Hedenus, Xiaoming Kan, Niklas Jakobsson, Yodefia Rahmad, Carin Lundqvist
article en

Abstract

Wind turbine output heavily depends on the wind speed at the deployment site. Energy system optimization models (ESOMs) typically allocate turbines in a cost-optimal manner, leading to siting at the windiest locations. However, such allocation methods lack an empirical base and risk overestimating the cost-competitiveness of wind power compared to real-life. This study assesses the historical siting of onshore wind turbines with respect to wind speed across 25 regions and introduces a heuristic method to represent wind power deployment patterns within ESOMs. Additionally, we conduct a comprehensive evaluation of existing wind turbine allocation methods in ESOMs. Our results show that turbines are typically sited at locations with slightly higher wind speeds than the regional mean, and new turbines within each region are consistently placed at sites with similar average wind speeds each year. The heuristics that best match historical deployment patterns tend to allocate 80–100 % of wind capacity to the 70th to 90th percentiles of the windiest areas. The cost-optimal turbine siting approach consistently favors windier locations compared to historical deployment. Overall, the findings present a promising avenue for incorporating historical data to improve the representation of wind power in future energy system modeling. • Most turbines are deployed at sites with wind speeds higher than the regional mean. • Wind turbines are sited at similar average wind speeds over time. • Heuristics based on historical data site wind capacity in the 70–90 % windiest areas. • Cost-optimal siting of turbines in ESOMs deviates from historical deployment.

Energy Strategy ReviewsVol. 62
Stockholm University (SE), Chalmers University of Technology (SE)
Openalex Percentile: Top 65%
Integrated Energy Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.