A novel reliability-oriented assessment method for coastal urban region spatial resource and power yield analysis for offshore wind farms

This study presents a comprehensive methodology for optimizing and evaluating offshore wind farms, focusing on maximizing energy production while minimizing costs. The approach integrates an improved marine spatial resource classification method, which considers both natural and social factors, to determine available sea area. And a 3D wake model is used to accurately calculate the Annual Electricity Production (AEP) and Levelized Cost of Electricity (LCOE) and combined with numerical simulations to determine the most efficient wind farm layout. Validation using 24 years of wind data from Hong Kong demonstrates the methodology's effectiveness. The results reveal a potential construction area of 246.44 km² for offshore wind farms in Hong Kong. Among five turbine models evaluated, the 12 MW model achieves the highest AEP and lowest LCOE. The LCOE is highly sensitive to both the actual energy output of the turbine and the costs associated with turbine and infrastructure installation. With 88 turbines installed, the wind farm could generate approximately 102,191 GWh annually, accounting for 5.515 % of Hong Kong's final energy consumption in 2022. This study highlights the significant potential of offshore wind energy in addressing energy demands and environmental goals.

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Publication Details

Journal
Energy Reports
Published
2025-03-05
DOI
https://doi.org/10.1016/j.egyr.2025.02.054
Citations
3
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
14.98

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article

A novel reliability-oriented assessment method for coastal urban region spatial resource and power yield analysis for offshore wind farms

Shaohai Zhang, Lin Lu, Linghe YE
3 citations
Energy Reports
Wind Energy Research and Development
14.98
article

A novel reliability-oriented assessment method for coastal urban region spatial resource and power yield analysis for offshore wind farms

Shaohai Zhang, Lin Lu, Linghe YE
article en
3 citations

Abstract

This study presents a comprehensive methodology for optimizing and evaluating offshore wind farms, focusing on maximizing energy production while minimizing costs. The approach integrates an improved marine spatial resource classification method, which considers both natural and social factors, to determine available sea area. And a 3D wake model is used to accurately calculate the Annual Electricity Production (AEP) and Levelized Cost of Electricity (LCOE) and combined with numerical simulations to determine the most efficient wind farm layout. Validation using 24 years of wind data from Hong Kong demonstrates the methodology's effectiveness. The results reveal a potential construction area of 246.44 km² for offshore wind farms in Hong Kong. Among five turbine models evaluated, the 12 MW model achieves the highest AEP and lowest LCOE. The LCOE is highly sensitive to both the actual energy output of the turbine and the costs associated with turbine and infrastructure installation. With 88 turbines installed, the wind farm could generate approximately 102,191 GWh annually, accounting for 5.515 % of Hong Kong's final energy consumption in 2022. This study highlights the significant potential of offshore wind energy in addressing energy demands and environmental goals.

Energy ReportsVol. 13
Hong Kong Polytechnic University (HK), Zhejiang Ocean University (CN)
Guangdong Science and Technology Department
Sustainable cities and communities
Openalex Percentile: Top 2%
Wind Energy Research and Development
14.98
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