Comparative Study on Prediction Algorithms for Power Grid System Access Failure Times

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Yan, Yi^1 ; Li, Bo^1 ; J., Xiao ; Y., Liang ; Y., Shang ; K., Zhou

Information Center Guangdong Power Grid Company, China^1

关键词: Algorithm analysis;    Comparative studies;    Power grid system;    Prediction algorithms;    Predictive modeling;    Risk predictions;    Root mean square errors;    Time series prediction;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/3/032183/pdf
DOI  :  10.1088/1755-1315/252/3/032183

来源: IOP

【 摘 要 】

As functions of the power grid system gradually increase and its scale becomes larger, the frequency of access failure times will gradually increase. In order to prevent access failures and make countermeasures in advance, we perform model fitting analysis and fault risk prediction for the time series of power grid failure code. In this paper, we use the failure code 404 as the training data and use the SARIMA algorithm, Fbprophet algorithm, holt-winter algorithm, and GM algorithm respectively to construct a time series prediction model. According to the result of the model building and the calculating, we find that the root mean square error of SARIMA algorithm is 258.85, which is the lowest among these algorithms, and the root mean square errors of Prophet and holt-winter algorithm are 749.288 and 809.89, respectively. However, the root mean square error of GM algorithm reaches 1710.95, which is 6 times as many as the SARIMA algorithm. In conclusion, with algorithm analysis and the comparisons of these four algorithms, we recommend the SARIMA algorithm as a predictive model for the power grid system.