A theoretical line losses calculation method of distribution system based on boosting algorithm

Abstract

Existing intelligent theoretical line losses calculation methods that prevalent on worse line calculation error, are all based on single learning algorithm. In order to overcome this defect, a novel intelligent calculation method based on boosting algorithm is proposed. In this calculation method, the theoretical line losses calculation is abstracted into function fitting problem, in addition, the sample set - which is structured by the lines' information of known theoretical line losses - is input to many single learning algorithms of boosting algorithm for training many sub-calculation model and constituting them as a sequence, which sequence is the final theoretical line losses calculation model. In the sub-calculation model training process, this intelligent method effectively reduces the calculation error by the boosting algorithm's internal mechanism that the large calculation error lines are constantly reinforcement training. Finally the experiment shows that this intelligent calculation method based on boosting algorithm has lower calculation error than traditions.