摘要
以沿海及山地复杂地形条件下的风电场为例,采用为期10 d的风电场测风塔实测风速资料,对比了两种预测方法在时效为4 h的超短期风速预测中的性能。其一为采用WRF数值模式预报的物理方法,其二为BP神经网络的统计方法;并探讨了两种风速预测方法的实用价值及意义。结果表明,与物理模拟方法相比,统计方法在4 h的超短期风速预测中,无论是预测准确性及计算效率都有一定的优势。
Wind farms at complex terrain condition like coastal areas and mountainous areas for instances are taken to contrast. The results are two prediction methods with ten-days observations from wind-towers, the one method was WRF simulation and the other was BP neural network statistical prediction. The accuracy of wind pre- diction in 4 hours term between two methods was analyzed. The practical value and significance of the two methods were also discussed. Results show the statistical prediction had obvious advantages in accuracy and computation ef- ficiency in 4 hours term compared with the physical simulation.
出处
《科学技术与工程》
北大核心
2013年第11期2965-2969,共5页
Science Technology and Engineering
基金
江苏省科技支撑计划(BE2010200)
江苏高校优势学科建设工程(PAPD)
长江学者和创新团队发展计划资助
关键词
复杂地形条件
风电场风速预测
统计预报
物理模拟
方法对比
complex terrain wind speed prediction statistical prediction physical simulationmethods comparison