基于电网运行数据集的发电机励磁系统调差系数优化整定  

Setting Optimization of Generator Excitation Adjustment Coefficient Based on Power Grid Operation Data Set

作　　者：刘柏林[1] 徐兴伟[2] 

机构地区：[1]华北电力大学电气与电子工程学院,北京市昌平区102206 [2]东北电网有限公司,辽宁省沈阳市110181

出　　处：《电网技术》2017年第2期508-513,共6页Power System Technology

摘　　要：提出了基于电网运行数据集的发电机励磁系统调差系数优化整定方法。通过自组织映射神经网络对电网运行方式数据进行聚类,利用电网运行数据集得到电网典型运行方式及出现概率,并在此基础上分析发电机励磁系统调差系数不同定值方案对电网运行的影响,对发电机励磁系统调差系数进行优化整定。将所提方法应用于吉林省电网,仿真结果表明,该方法充分考虑了负荷变化特征和可再生能源发电运行特性,能有效降低电网有功损耗,提高电网电压水平,减小电压波动。This paper proposes an optimal setting method of ESAC （excitation system adjustment coefficient） based on power grid operation data set. By means of self-organizing feature mapping neural network, typical grid operation modes and occurrence probability are obtained based on the operation data set. On this basis, influences of different values of ESAC on power grid are analyzed, and generator ESAC is optimized. Simulation results of Jilin provincial power grid show that with the proposed method network loss is reduced, power grid voltage level iS improved and voltage fluctuation is decreased at the same time, while operating characteristics of both load and renewable power generation are fully considered.

关 键 词：自组织特征映射 励磁系统调差系数 电网运行数据集 

分 类 号：TM721[电气工程—电力系统及自动化]