CAJ | 학술논문

风电机组集中并网会对电网安全稳定运行带来影响，为了合理规划各类供电机组高效运行，对电力负荷预测的精度提出了更高的要求。电网负荷时间序列具有混沌特性，普通预测方法难以描述其特性和内在规律。利用混沌相空间重构理论对负荷时间序列进行研究，用互信息法和CAO方法分别求得时间延迟和嵌入维数，并由此得到系统最大李雅普诺夫指数，证明其具有混沌特性。然后根据时间延迟和嵌入维数对样本数据相空间重构，在此基础上利用支持向量回归算法（ PSR－SVR）对电力负荷进行预测，支持向量回归采用网格寻优确定参数。最后将预测的结果同时间序列模型和BP神经网络模型的预测结果进行对比，结果表明，这是一种误差小，精度高的电网负荷预测方法器。
풍전궤조집중병망회대전망안전은정운행대래영향，위료합리규화각류공전궤조고효운행，대전력부하예측적정도제출료경고적요구。전망부하시간서렬구유혼돈특성，보통예측방법난이묘술기특성화내재규률。이용혼돈상공간중구이론대부하시간서렬진행연구，용호신식법화CAO방법분별구득시간연지화감입유수，병유차득도계통최대리아보낙부지수，증명기구유혼돈특성。연후근거시간연지화감입유수대양본수거상공간중구，재차기출상이용지지향량회귀산법（ PSR－SVR）대전력부하진행예측，지지향량회귀채용망격심우학정삼수。최후장예측적결과동시간서렬모형화BP신경망락모형적예측결과진행대비，결과표명，저시일충오차소，정도고적전망부하예측방법기。
The impacts of centralized operation of wind turbines on grid′s security and stability operation ask for high requirements for power load forecasting precision in order to realized reasonable planning efficient operation of various power supply units.The time series of grid has chaotic characteristics and it is difficult to describe its characteristics and inherent laws.The chaotic phase space reconstruction theory is adopted to study the power load time series sample data.Time delay and embedding dimension are obtained through the mutual information method and the CAO.Lya-punov exponent of this system is obtained so as to prove that the grid system has chaotic characteristics.Then the phase space is reconstructed according to the time delay and embedding dimension.On the basis of phase space re-construction, support vector regression algorithm is adoped to predict the power load.The grid search method is used for parameter optimization.Finally, the predicted results with the time series prediction model and BP neural network model are compared.The results show that is the proposed method is a high precison load forecasting method with small error.