Prediction of Primary Frequency Regulation Capability of Power System Based on Deep Belief Network

• 作者: Chen Xue Cong Wang Nan Yang Wei Cui Wujing Li Xin Bai Yunlong Zhu
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 工学
• 关键词: Primary frequency control Power system Deep belief neural network PREDICTION
• 年，卷（期）: 2020,（2）
• 页码范围: 423-435
• 页数: 13页
• 分类号: TP3

摘要

The primary frequency response ability plays a crucial role in the rapid recovery and stability of the power grid when the grid is disturbed to generate a power imbalance.In order to predict the primary frequency control ability of power system,a new model is proposed based on deep belief networks.The key feature of the proposed model lies in the fact that it considers three key factors,i.e.,disturbance information,system state feature,and unit operation mode.Through this way,it predicts the primary frequency control ability of the power system accurately.The simulation results on real power system data verify the feasibility and accuracy of the proposed model.