In order to fully explore the influence of high proportion of new energy in the power grid on load forecasting,wind power solar power load data is used as the research object to forecast the load changes through a load forecasting method combining modified time convolution network(TCN)and joint sequential scenario.Firstly,the historical data is analyzed based on the 3 σ criterion to eliminate the abnormal data,then the joint sequential scenario is applied to depict the correlation between load demand and power output of new energy,and classify different load prediction scenarios.Afterwards,load prediction feature extraction is performed based on random forest(RF)algorithm to construct RF-TCN network prediction model,and the prediction results are corrected by Bootstrap algorithm.Finally,the data of a region of Gansu province is taken for example simulation and four comparative examples are set.The simulation results prove the effectiveness of the proposed method and expect to play a positive role in the construction of the new power system.
new power system/joint sequential scenario/power system with high proportion new energy/load forecasting/3 σ criterion/temporal convolution network(TCN)/random forest(RF)/Bootstrap algorithm
维普
万方数据