Feiyu Liu
Power system, artificial bee colony (ABC) algorithm, rough set, power load forecasting (PLF), simulated annealing (SA) algorithm
In response to the problem of redundant power grid data, this study proposes a sample processing model based on rough sets, which can process power grid data. Then, a power system load forecasting model based on an artificial bee colony (ABC) algorithm is designed, and the simulated annealing algorithm is introduced to perfect it. The experiment showed that the information retention rates of rough set model, fuzzy set theory model, grey system theory model, and probability graph model were 97.1%, 92.5%, 86.3%, and 84.1%, respectively. The accuracy of the research model was higher than that of other models. In the validation set, the accuracy of the four algorithm models was 0.94, 0.87, 0.85, and 0.83. This proves that the proposed improved ABC algorithm can effectively predict and schedule power loads, providing a solution for the scheduling problem of the power system.
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