Application of wind energy resource assessment system based on big data storage

Qi Shi; Guannan Lv; Bo Ai; Benshuai Li; Peipei Wang; Wenjun Feng; Hengshuai Shang

doi:10.1117/12.3048057

3 October 2024 Application of wind energy resource assessment system based on big data storage

Qi Shi, Guannan Lv, Bo Ai, Benshuai Li, Peipei Wang, Wenjun Feng, Hengshuai Shang

Author Affiliations +

Proceedings Volume 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024); 132721T (2024) https://doi.org/10.1117/12.3048057
Event: 5th International Conference on Computer Vision and Data Mining (ICCVDM 2024), 2024, Changchun, China

Abstract

This paper constructs an interactive offshore wind power resource assessment system based on the 30-year data of ERA5 wind farm from the European Center for Medium-Range Weather Forecasts (ECMWF), combined with the offshore wind power big data storage technology of Apache Cassandra database and the wind energy resource assessment model, and following the current national standards and technical specification documents. In this paper, 6 wind turbines in Changyi wind farm are randomly selected for authenticity, reasonableness and completeness analysis and verification, which verifies the feasibility of constructing wind farms in this sea area, and provides scientific site selection basis and wind resource assessment reference for the construction of offshore wind farms in China.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qi Shi, Guannan Lv, Bo Ai, Benshuai Li, Peipei Wang, Wenjun Feng, and Hengshuai Shang "Application of wind energy resource assessment system based on big data storage", Proc. SPIE 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024), 132721T (3 October 2024); https://doi.org/10.1117/12.3048057

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