A SHORT-TERM LOAD FORECASTING APPROACH BASED ON IMMUNE SUPPORT VECTOR MACHINES

On the basis of analyzing the parameter performance of support vector machine (SVM), an immune support vector machines method for short-term load forecasting is presented in which the parameters in SVM method are optimized by immune algorithm. Through the simulation of interaction between antigens and antibodies the immune algorithm, which is designed according to mechanism of the immune systems of human and other mammals, can effectively surmount the premature convergence and promote the diversity of colony. The calculation results from short-term load forecasting example of actual power network show that the presented immune SVM method can offer more accurate forecasting result than SVM method.