Assessment Method of Offshore Wind Resource Based on Multi-dimensional Indexes System
Regular Papers|更新时间:2026-10-15
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Assessment Method of Offshore Wind Resource Based on Multi-dimensional Indexes System
CSEE Journal of Power and Energy SystemsVol. 10, Issue 1, Pages: 76-87(2024)
作者机构:
1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (NCEPU), School of New Energy, North China Electric Power University,Beijing,China
2. School of Physical and Electronic Information Engineering, Qinghai Normal University,Qinghai,Xining,China
3. Royal School of Mines, Imperial College London,London,UK
4. Department of Industrial Engineering, Turkish Naval Academy, National Defence University,Istanbul,Turkey
5. Department of Energy Systems, SINTEF Energy Research, Trondheim,Norway
6. Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim,Norway
Xiaomei Ma, Yongqian Liu, Jie Yan, et al. Assessment Method of Offshore Wind Resource Based on Multi-dimensional Indexes System[J]. CSEE Journal of Power and Energy Systems, 2024, 10(1): 76-87.
DOI:
Xiaomei Ma, Yongqian Liu, Jie Yan, et al. Assessment Method of Offshore Wind Resource Based on Multi-dimensional Indexes System[J]. CSEE Journal of Power and Energy Systems, 2024, 10(1): 76-87.DOI: 10.17775/CSEEJPES.2021.09260.
Assessment Method of Offshore Wind Resource Based on Multi-dimensional Indexes System
Traditional assessment indexes could not fully describe offshore wind resources
for the meteorological properties of offshore are more complex than onshore. As a result
the uncertainty of offshore wind power projects would be increased and final economic benefits would be affected. Therefore
a study on offshore wind resource assessment is carried out
including three processes of “studying data sources
conducting multi-dimensional indexes system and proposing an offshore wind resource assessment method based on analytic hierarchy process (AHP)”. First
measured wind data and two kinds of reanalysis data are used to analyze the characteristics and reliability of data sources. Second
indexes such as effective wind speed occurrence
affluent level occurrence
coefficient of variation
neutral state occurrence have been proposed to depict availability
richness
and stability of offshore wind resources
respectively. Combined with existing parameters (wind power density
dominant wind direction occurrence
water depth
distance to coast)
a multi-dimensional indexes system has been built and on this basis
an offshore wind energy potential assessment method has been proposed. Furthermore
the proposed method is verified by the annual energy production of five offshore wind turbines and practical operating data of four offshore wind farms in China. This study also compares the ranking results of the AHP model to two multi-criteria decision making (MCDM) models including weighted aggregated sum product assessment (WASPAS) and multi-attribute ideal real comparative analysis (MAIRCA). Results show the proposed method gains well in practical engineering applications
where the economic score values have been considered based on the offshore reasonable utilization hours of the whole life cycle in China.