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Power Demand Forecasting and Application based on SVR

  • Qing Guo
  • , Yuyao Feng
  • , Xiaolei Sun*
  • , Lijun Zhang
  • *此作品的通讯作者
  • State Grid Corporation of China
  • CAS - Institutes of Science and Development
  • University of Chinese Academy of Sciences

科研成果: 期刊稿件会议文章同行评审

摘要

Power as one of the most important energy to promote the development of national economy, plays an essential role in the normal operation of all aspects of society. Because of its production and use are difficult to store in large quantities, it is necessary to forecast future demand, which will become an important basis for making power development plans. Considering the complex non-linear relationship between power demand and its influencing factors, it is difficult to describe it accurately with the traditional mathematical models. In this paper, we select six major influencing factors and use the support vector machine to predict future power demand. The prediction accuracy is improved by parameter optimizing. At the same time, the simulation experiment of Shandong Province is conducted to further verify the validity and feasibility of the model.

源语言英语
页(从-至)269-275
页数7
期刊Procedia Computer Science
122
DOI
出版状态已出版 - 2017
已对外发布
活动5th International Conference on Information Technology and Quantitative Management, ITQM 2017 - New Delhi, 印度
期限: 8 12月 201710 12月 2017

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