SHIP POWER LOAD FORECASTING USING SUPPORT VECTOR MACHINE
Zhu Shi-feng · Proceedings of the CSEE · 2004
Ship power system is an isolated power system, and the several generators are controlled to run or stop according to accurate load forecasting respectively. A new short-term load forecasting method for ship power system based on support vector machine (SVM) is presented. Three methods of the load forecasting, the SVM based on radial basis function kernel, the multi-layer back-propagation neural network and the radial basis function neural network, are compared for actual load data sampled at different operation modes from a large-scale container ship. The simulation results show that the SVM method can achieve greater accuracy than other methods, and is effective for ship power load forecasting.