风能资源分析与服务平台设计和实现

Design and Implementation of a Wind Energy Resource Analysis and Service Platform for China

  • 摘要: 为提升我国风能资源的合理开发和高效利用, 2022年初启动了风能资源分析与服务平台研制。平台采用大数据和气象信息分析技术, 融合高分辨率风能资源数据集、气象灾害与台风历史数据、气象预报数据以及基础地理信息等, 研制形成了包括风能资源查询分析、台风等气象灾害评估与预报预测信息分析、可开发量分析、风机宏观评估、风机自动排布、测风塔管理以及项目管理等业务与服务功能。为满足大数据量的存储和分析需求, 设计了基于地理哈希编码的存储结构、按层高分表以及多节点部署等方法, 同时创新性使用提取山顶、山脊线、图像识别及分类等算法, 结合气象、气候、高程、遥感图像等条件, 构建风能资源评估模型并应用在风机自动布机业务。该平台已在国内多家风电企业本地化部署并应用, 主要提供风能资源评估、风机布局、近海风能资源分析及风电场选址等服务, 结果表明:平台能够识别风能资源丰富区域, 并为风电场选址提供可量化的指标数据, 为风电场建设从规划、设计到实施提供科学依据。

     

    Abstract: National Climate Center starts designing and constructing Wind Energy Resource Analysis and Service Platform (WERASP) in January 2022, with the aim of enhancing rational development and efficient utilization of wind energy resources. Taking advantage of big data, the platform integrates and aggregates high-resolution wind energy resources datasets, meteorological disasters data, historical typhoon data, meteorological forecast data as well as basic geographical information, and thus establishes the business foundation for the purpose of wind energy resources assessment. A range of business and service functions are developed, including wind energy resource query and analysis, meteorological disaster assessment, along with forecast information analysis, exploitable wind energy analysis, wind turbine macro evaluation, automated wind turbine layout, wind measurement tower management, together with project management. A series of solutions are proposed and implemented in response to the critical technical challenges related to storage, concurrency, and analysis of massive data that arise during the development of the platform. Specifically, methodologies such as storage architecture based on GeoHash coding, stratified high-score tables, and multi-node deployment are proposed. By leveraging these approaches, the goal is to effectively tackle challenges posed by big data when ensuring seamless operation and improved performance. Simultaneously, with the aim of more effectively supporting automatic placement of wind turbines, particularly in mountainous regions characterized by relatively intricate terrains, the platform adopts and leverages state-of-the-art algorithms from the weather system identification. Several innovative modifications and implementations are introduced, such as algorithms for extracting mountain summits, ridge lines, image recognition, and classification. The platform is applied under various restrictive conditions, including meteorology, climate, elevation, and remote sensing imagery. Consequently, a wind energy resource assessment model is developed and is extensively applied in the business scope of automatic wind turbine placement. The platform is locally deployed for operational use across a variety of domestic wind power enterprises. It primarily offers a range of professional services, including wind energy resource assessment, optimization of wind turbine placement, analysis of offshore wind energy resources, and site selection for wind farms. Results demonstrate that the platform is highly proficient in discerning regions replete with wind energy resources and providing quantifiable metrics for wind farm site selection. It exerts a crucial and indispensable impact during the entire life cycle of wind farm construction life cycle, beginning the initial planning and design stages and culminating in the final implementation phase. Achievements of this project harbor extensive and profound prospects for augmenting the sustainable harnessing and utilization of wind energy resources within the territory of China, thereby endowing a substantial and momentous impetus to the progression and sophistication of the national wind power industry.

     

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