基于数值天气预报的风能预测系统

随着世界范围内风电事业的飞速发展,大量大容量风电机组直接接入高压输电网络,是对电网安全运营、电能质量保证的重大挑战,迫切需要使用风能预测系统来对风电机组的发电功率进行预测。提出一种基于数值天气预报以及人工神经网络的混合型风能预测系统。该系统以基于数值天气预报的风速和风向预测数据作为输入数据,以自组织神经网络作为预处理模型,以径向基函数网络模型作为预测模型,并依据特定风电机组或风场的发电量的历史数据对输出数据进行修正。用该预测系统对河北某风电场进行了实例计算,得到可接受的预测结果,表明系统可行。

Forecasting system based on numerical weather prediction

Along with the rapid development of wind power industry in the world,the integation of large number of wind turbines with high capacity to high voltage transmission networks is a great challenge for grid operation security and power supply quality.Wind power forecasting systems are needed for wind turbine power generation.A hybrid wind power forecasting system is proposed based on numerical weather prediction and artificial neural networks.By using historical wind speed and direction data as inputs,self-organizing maps model as the pretreatment model and radial basis function network model as the forecasting model,the forecasting system was used in a wind farm in Hebei province with the correction by historical outputs of a specific wind turbine or wind power generation field.The prediction results are acceptable,which shows the feasibility of proposed model.