Design of simplified online ultra-short term photovoltaic output forecasting algorithm for low cost microgrid
CHEN Xiao-ke
CHEN Qi-fang
HE Ting
HUANG Jin-cheng
Abstract：Based on the engineering requirement of user side photovoltaic (PV) microgrid,a simplified online short term PV output forecasting algorithm is studied for embedded system application.Extreme learning machine with kernel (ELM_K) algorithm is adopted as the main part.The traditional time sequence of training dataset is replaced with characteristic sequence of history data,therefore,the amount of storage place of training data is reduced.Because of the optimal training dataset is selected from original training dataset by trend weighted similarity,the accuracy is improved,also the amount of calculation and runtime of forecasting algorithm is reduced.The test results of embedded system show that the performance of proposed online short term PV output forecasting algorithm on accuracy,runtime and storage occupation can satisfy the requirement of low cost embedded system application.
Keywords：photovoltaic output forecastingultra-short termsimplifiedextreme learning machine with kernel
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 1658-1666 )