Short-term load forecasting based on improved gene expression programming

Gene expression programming (GEP) was improved (IGEP) to overcome the shortcomings that the initial population is generated randomly, there are no standards to measure the gene, and evolution results got before canpsilat be utilized. Quasi-law of nature that excessive multiplication, environmental factor selecting, using pheromones to measure gene, passing on from generation to generation and self-adaptive mutation rate method are proposed and that make the improved gene expression programming (IGEP) is capable of memory and self-adaptive ability. The improved gene expression programming (IGEP) was applied to short-term load forecasting. Firstly, the load series of the same time but different days are chosen as the training samples. Secondly, the load samples are filtered and processed generally. And finally, the short-term load is forecasted classified by weekday and weekend after eliminating the pseudo-data. Compared with the results forecasted by means of GP and GEP, it proves that the method of IGEP in short-term load forecasting is better.