为提高风功率短期预测的准确率,提出一种基于改进灰狼算法优化加权最小二乘支持向量机(Weighted Least Squares Support Vector Machine,WLSSVM)的短期风功率预测方法。采用C-C法对风功率时间序列的嵌入维数进行了计算,根据计算结果确...为提高风功率短期预测的准确率,提出一种基于改进灰狼算法优化加权最小二乘支持向量机(Weighted Least Squares Support Vector Machine,WLSSVM)的短期风功率预测方法。采用C-C法对风功率时间序列的嵌入维数进行了计算,根据计算结果确定短期风速预测输入量与输出量的关系。利用Tent映射和参数非线性调整策略对灰狼算法进行改进,得到了优化性能更强的改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法,并利用测试函数验证了IGWO算法能够加快迭代收敛,提高计算精度。采用IGWO算法对WLSSVM的惩罚系数和核参数进行优化,建立基于IGWO-WLSSVM的短期风功率预测模型。采用某风电场春夏两个不同季节的风功率数据进行算例分析,结果表明,所提短期风功率预测结果的平均相对误差、均方根误差和最大相对误差更小,风功率预测精度和预测结果的稳定性均优于其他方法,验证了所提方法的有效性和实用性。展开更多
The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road.In order to obtain the s...The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road.In order to obtain the scientific and real-time forecasting result,this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM.Firstly,the factors influencing investment risk of wind energy along the Belt and Road are identified fromthree dimensions:endogenous risk,exogenous risk and process risk.Through the fuzzy threshold method,the final input index system is selected.Secondly,the risk evaluation method based on improved cloud model andGRA-TOPSIS is proposed.Thirdly,a modern intelligent model based on MBA-WLSSVMis designed.In modified bat algorithm(MBA),tent chaotic map is utilized to improve the basic bat algorithm,while weighted least squares support vector machine(WLSSVM)adopts wavelet kernel function to replace the traditional radial basis function to complete the model improvement.Finally,an example is given to verify the scientificity and accuracy of themodel,which is helpful for investors tomake fast and effective investment risk forecasting of wind energy along the Belt and Road.The example analysis proves that the proposedmodel can provide reference and basis for investment corpus to formulate the investment strategy in wind energy along the Belt and Road.展开更多
文摘为提高风功率短期预测的准确率,提出一种基于改进灰狼算法优化加权最小二乘支持向量机(Weighted Least Squares Support Vector Machine,WLSSVM)的短期风功率预测方法。采用C-C法对风功率时间序列的嵌入维数进行了计算,根据计算结果确定短期风速预测输入量与输出量的关系。利用Tent映射和参数非线性调整策略对灰狼算法进行改进,得到了优化性能更强的改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法,并利用测试函数验证了IGWO算法能够加快迭代收敛,提高计算精度。采用IGWO算法对WLSSVM的惩罚系数和核参数进行优化,建立基于IGWO-WLSSVM的短期风功率预测模型。采用某风电场春夏两个不同季节的风功率数据进行算例分析,结果表明,所提短期风功率预测结果的平均相对误差、均方根误差和最大相对误差更小,风功率预测精度和预测结果的稳定性均优于其他方法,验证了所提方法的有效性和实用性。
基金This work is supported by the Fundamental Research Funds for the Central Universities,China(Project No.2018MS148).
文摘The timely and effective investment risk assessment and forecasting are of great significance to ensure the investment safety and sustainable development of wind energy along the Belt and Road.In order to obtain the scientific and real-time forecasting result,this paper constructs a novel hybrid intelligent model based on improved cloud model combined with GRA-TOPSIS and MBA-WLSSVM.Firstly,the factors influencing investment risk of wind energy along the Belt and Road are identified fromthree dimensions:endogenous risk,exogenous risk and process risk.Through the fuzzy threshold method,the final input index system is selected.Secondly,the risk evaluation method based on improved cloud model andGRA-TOPSIS is proposed.Thirdly,a modern intelligent model based on MBA-WLSSVMis designed.In modified bat algorithm(MBA),tent chaotic map is utilized to improve the basic bat algorithm,while weighted least squares support vector machine(WLSSVM)adopts wavelet kernel function to replace the traditional radial basis function to complete the model improvement.Finally,an example is given to verify the scientificity and accuracy of themodel,which is helpful for investors tomake fast and effective investment risk forecasting of wind energy along the Belt and Road.The example analysis proves that the proposedmodel can provide reference and basis for investment corpus to formulate the investment strategy in wind energy along the Belt and Road.
