冀北地区年度最大负荷的支持向量机建模预测

国网冀北电力有限公司肩负着保障首都供电安全、服务冀北地区经济社会发展和服务国家新能源发展的特殊使命。在分析影响负荷变化的外部环境的前提下,使用支持向量机(support vector machine,SVM)和误差反向传播算法(back propagation,BP)神经网络对冀北地区年最大负荷进行建模预测。误差对比分析表明支持向量机的预测精度更高;从预测结果看,冀北地区年最大负荷波动较小,年均增长率为0. 78%。预测结果可为冀北地区电力发展提供参考。

Research on Modeling Forecast of Annual Maximum Load in Northern Hebei Province Based on Support Vector Machine

The electric power in northern Hebei Province, shoulders the special mission of ensuring the power supply security of the capital, serving the economic and social development of northern Hebei and serving the new energy development of the country. On the premise of analyzing the external environment that affects the load, this paper used support vector machine and BP neural network model to forecast the annual maximum load in northern Hebei. The error analysis showed that the forecast accuracy of support vector machine is higher; from the prediction results, the annual maximum load in northern Hebei fluctuates less with an average annual growth rate of 0.78%. The forecast result can provide a reference for the development of electric power in northern Hebei Province