2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)

1 / 2017-08-25 16:10:29

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.

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.