基于云计算平台实现电网短期负荷预测算法的研究

Research on Short-term Load Forecasting Algorithm Based on Cloud Computing Platform

短期电网负荷预测在任何电力系统的运行决策中都起着重要作用。由于负荷短期预测的实时性要求与在大型数据集上执行复杂的计算过程所需的高计算能力相冲突,提出了基于支持向量回归的短期电网负荷预测算法,并基于云计算平台实现了该算法。将所提预测算法分别在云计算平台和单机计算平台上进行对比实验,结果表明基于云计算平台的实现有效提高了算法执行效率。

Short-term grid load forecasting plays an important role in the operational decision for any power system. Because the real-time requirements for short-term load forecasting conflict with the high computing capability which is required to perform complex processes on large data sets, a short-term grid load forecasting algorithm based on support vector regression is proposed, which is implemented based on cloud computing platform.The proposed forecasting algorithm is compared between the cloud computing platform and the stand-alone computing platform, and the results show that the implementation based on cloud computing platform effectively improves the execution efficiency of the algorithm.