摘要
为了预测电力系统稳定性,将大数据用于静态电压稳定性判断中,使用了Matlab中的PSAT软件与LIBSVM软件对数据进行采集、预测和分析,进一步判断电力系统的稳定性.将经典的3机9节点模型进行改造并加入光伏电站,改变负荷系数以及光伏发电量,得出样本数据.取部分样本对支持向量机进行训练.用训练得到的模型进行鞍结分岔点的预测,计算预测准确度.仿真分析的结果表明,该方法简单高效,可以用于电网电压稳定性的预测.
In order to predict the stability of a power system, PSAT toolbox and LIBSVM toolbox of MATLAB are used to collect, predict and analyze the data that is applied to determine the static voltage stability. The classical three-machine nine nodes model was transformed and a photovoltaic device was added to change load coefficient. The sample data was then obtained, some of which was taken for training support vector machines. The model built from the training was then used to predict the saddle node bifurcation point to calculate the prediction accuracy. The results of simulation and analysis show that this method is simple and highly efficient, and thus can be used to predict the stability of power grid voltage.
出处
《南京工程学院学报(自然科学版)》
2016年第1期71-75,共5页
Journal of Nanjing Institute of Technology(Natural Science Edition)
基金
江苏省高校大学生创新创业训练计划项目(201411276048X)