Primary Frequency Control Ability Evaluation of Valve Opening in Thermal Power Units Based on Artificial Neural Network

作     者：LIAO Jinlong LUO Zhihao YIN Feng CHEN Bo SHENG Deren LI Wei YU Zitao LIAO Jinlong;LUO Zhihao;YIN Feng;CHEN Bo;SHENG Deren;LI Wei;YU Zitao

作者机构：Institute of Thermal Science and Power SystemsZhejiang UniversityHangzhou 310027China Electric Power Research Institute of State Grid Zhejiang Electric Power Co.LtdHangzhou 310027China 

出 版 物：《Journal of Thermal Science》 (热科学学报（英文版）)

年 卷 期：2020年第29卷第3期

页      面：576-586页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080802[工学-电力系统及其自动化] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Electric Power Research Institute of State Grid Corporation of China in Zhejiang province 

主　　题：primary frequency control valve opening main steam pressure thermal power unit artificial neural network evaluation 

摘      要：With the development of new energy,the primary frequency control(PFC)is becoming more and more important and *** improve the reliability of the PFC,an evaluation method of primary frequency control ability(PFCA)was ***,based on the coupling model of the coordinated control system(CCS)and digital electro-hydraulic control system(DEH),principle and control mode of the PFC were introduced in *** simulation results showed that the PFC of the CCS and DEH was the most effective control ***,the analysis of the CCS model and variable condition revealed the internal relationship among main steam pressure,valve opening and *** term of this,the radial basis function(RBF)neural network was established to estimate the *** the simulation curves fit well with the actual curves,the accuracy of the coupling model was *** this basis,simulation data was produced by coupling model to verify the proposed evaluation *** low predication error of main steam pressure,power and the PFCA indicated that the method was *** addition,the actual data obtained from historical operation data were used to estimate the PFCA accurately,which was the strongest evidence for this method.