小波模糊神经网络在电力系统短期负荷预测中的应用

该文研究了基于小波模糊神经网络的电力系统短期负荷预测新方法。根据小波变换自适应可调时频窗的特点，利用小波分析对负荷样本做序列分解，对高尺度负荷分量采用常规预测方法，其他负荷分量则采用模糊神经网络处理技术，最后通过序列重构，得到完整的负荷预测结果。算例计算表明，新方法具有较高的预测精度和适应能力。

NEW SHORT-TERM LOAD FORECASTING PRINCIPLE WITH THE WAVELET TRANSFORM FUZZY NEURAL NETWORK FOR THE POWER SYSTEMS

This paper presents a new method based on the wavelet transform (WT) fuzzy neural network for the short-term load forecasting. By the WT, the different load sequence components are projected to the different scales. For the low scales in multiresolution analysis (MRA) results, the fuzzy neural network is very suitable for the load frequency resolution and is then applied. At the same time, the matching conventional forecasting methods are used in high scales. After reconstruction, the forecasting results are obtained. Simulation resultsdemonstrate that the proposed method can provide forecastprecision.