1 / 2017-08-25 16:12:45
Elman neural network model for short term load forecasting based on improved demand response factor
Electricity price reform; short-term load forecasting ; neural network; prediction accuracy.
全文待审
妮 肖 / 昆明理工大学
The Central Committee of the Communist Party of China were found under the state council [2015] no. 9, the first key task is to power system reform, "orderly promote the reform of electricity prices, making electricity price formation mechanism", is to be determined by electricity market price. In order to adapt to the policy of electricity reform and to improve the prediction accuracy of short-term power load, a demand response model based on time-varying function is introduced by studying the demand response load, and the influencing factors of demand response are introduced in the traditional input. According to the Elman neural network is easy to fall into local extremum, improve its incentive function to optimize the prediction model.In order to establish the Elman neural network model for short term load forecasting based on improved demand response factor.
重要日期
  • 会议日期

    12月12日

    2017

    12月14日

    2017

  • 09月04日 2017

    初稿截稿日期

  • 09月30日 2017

    初稿录用通知日期

  • 10月15日 2017

    终稿截稿日期

  • 12月14日 2017

    注册截止日期

主办单位
Hong Kong Section IE/PE/IA/PEL Joint Chapter
协办单位
Hong Kong Section IE/PE/IA/PEL Joint Chapter
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