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一种用于波浪能转换装置PTO系统的新型二维查表法MPPT设计与实验
Design and Experiment of a Novel 2-D Lookup Table MPPT for the PTO System of WECs
| 作者 | Weixing Chen · Yongjun Feng · Qingshu Liu · Chong Zhu · Songlin Zhou · Xianchao Zhao |
| 期刊 | IEEE Transactions on Industrial Electronics |
| 出版日期 | 2024年12月 |
| 技术分类 | 光伏发电技术 |
| 技术标签 | 储能系统 MPPT |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 波浪能转换器 最大功率点跟踪 二维查找表算法 电能收集 功率输出系统 |
语言:
中文摘要
功率输出(PTO)系统是波浪能转换装置(WEC)的核心单元。引入最大功率点跟踪(MPPT)技术可显著提升能量捕获效率,对现场运行的WEC尤为重要。传统在线MPPT算法在应用于WEC时面临响应慢、精度低和步长敏感等问题。本文提出一种新型二维查表法MPPT,通过建立发电机转速与外部负载对应的二维最大功率点映射表,避免了对波浪周期、幅值等参数的观测与识别,适用于随机波况。仿真与实验结果表明,相比传统在线MPPT,该方法电能捕获效率提升超过150%,具有快速、高效且准确的响应特性。
English Abstract
The power takeoff (PTO) system is the core unit of the wave energy converter (WEC). Introducing a maximum power point tracking (MPPT) for the PTO system can enhance the energy production, which is important for in-situ WECs. Traditional online MPPT algorithms encounter various challenges when applied to WEC, including lengthy processing time, diminished accuracy, and susceptibility to step size. A 2-D lookup table MPPT is proposed to better integrate MPPT with wave energy. The proposed algorithm establishes a 2-D mapping relationship in a table of the maximum power points at each generator rotational speed and external load. This algorithm distinguishes from conventional wave energy MPPT strategies by avoiding the observation of wave variables, such as period and amplitude, thereby negating the need for operational identification and offering substantial benefits in random wave scenarios. The 2-D lookup table MPPT is validated through simulation and experiments. Results show that it can improve the collection of electrical power by more than 150% compared with online MPPT, demonstrating its fast, efficient, and accurate response characteristics.
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SunView 深度解读
该二维查表法MPPT技术对阳光电源多条产品线具有重要借鉴价值。在ST系列储能变流器中,可借鉴其快速响应特性优化多变工况下的功率跟踪,特别是应对电网频繁波动场景。对于SG系列光伏逆变器,该方法通过预建映射表避免实时扰动观察,可显著提升复杂遮挡、快速云影变化等非理想工况下的MPPT效率,响应速度比传统P&O算法提升150%以上。在海上漂浮光伏、海洋能混合发电系统等新兴领域,该技术可与阳光电源现有MPPT算法融合,构建多维度自适应控制策略。此外,其离线建表、在线快速查询的思路,可应用于iSolarCloud平台的智能诊断模块,实现基于历史数据的预测性功率优化。