POWER LOAD FORECASTING SYSTEM BASED ON LONG SHORT-TERM MEMORY NEURAL NETWORK

Title:

POWER LOAD FORECASTING SYSTEM BASED ON LONG SHORT-TERM MEMORY NEURAL NETWORK

Document Type and Number:

WIPO Patent Application WO/2018/161723

Kind Code:

A1

Abstract:

A power load forecasting system (10) based on a long short-term memory neural (LSTM) network, wherein the LSTM network comprises an input layer, an LSTM network layer, and an output layer. The system comprises: an information receiving module (101) used for transmitting input power load data and region feature factor at a historical moment to the input layer; a modeling module (102) used for training and modeling the power load data and the region feature factor at the historical moment by means of the LSTM network layer, in order to generate a deep neural network load forecasting model; a power forecasting module (103) used for forecasting the power load in a region by means of the deep neural network load forecasting model, and generating a forecasting result of the power load in the region by means of a regressor connected to the LSTM network layer; and a result output module (104) used for outputting the forecasting result of the power load in the region by means of the output layer. By constructing a load forecasting model for multi-task learning on the basis of an LSTM network, power consumption loads in multiple regions can be precisely forecasted, and the forecasting effect is improved.

Inventors:

YANG YANDONG (CN)
DENG LI (CN)
LI SHUFANG (CN)
ZHANG GUANJING (CN)
GE XINKE (CN)

Application Number:

PCT/CN2018/072372

Publication Date:

September 13, 2018

Filing Date:

January 12, 2018

Export Citation:

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Assignee:

X TRIP INF TECH CO LTD (CN)

International Classes:

G06Q50/06; G06N3/02; G06Q10/04

Foreign References:

CN106952181A	2017-07-14
CN103093285A	2013-05-08
CN103854068A	2014-06-11
CN105608512A	2016-05-25
US20150254554A1	2015-09-10

Other References:

LIU, TONGTONG: "The Method of Short-term Load Forecasting based on long short-term memory", HEILONGJIANG SCIENCE AND TECHNOLOGY INFORMATION, vol. 31, 30 November 2016 (2016-11-30), pages 81

Attorney, Agent or Firm:

X-TRIP INFORMATION TECHNOLOGIES CO., LTD (CN)

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