Emotional Deep Learning Programming Controller for Automatic Voltage Control of Power Systems

In recent years, the rapid development of artificial intelligence, especially deep learning technology, makes machine have application scenarios in fields power system stability analysis, coordination along with scheduling and load forecasting. This paper designs an emotional programming controller (EDLPC) for automatic voltage control systems. The designed EDLPC contains neural network (EDNN) structure Q-learning algorithm. Besides, a specially defined proportional-integral-derivative (PID) is added to networks (DNNs) as actuator EDNN realize tuning PID parameters. terms control, combines advantages controller, meanwhile adopts reinforcement algorithm optimize From perspective learning, embedding prior knowledge into output instructions helpful weaken fitting problem training process. Compared outputs DNN under two cases, could gain highest performance smaller deviations. simulation results verify feasibility effectiveness proposed method