Short-term load prediction method based on GBDT (gradient boosting decision tree)

A short-term load forecasting and decision tree technology, which is applied to load forecasting in AC networks, AC network circuits, electrical components, etc., can solve problems such as low load forecasting accuracy, and achieve controllable generalization errors, fewer adjustment parameters, and convergence fast effect

Active Publication Date: 2018-09-14
国网山东省电力公司营销服务中心(计量中心) +2
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[0004] In the embodiment of the present invention, a short-term load forecasting method based on a grad...

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  • Short-term load prediction method based on GBDT (gradient boosting decision tree)
  • Short-term load prediction method based on GBDT (gradient boosting decision tree)
  • Short-term load prediction method based on GBDT (gradient boosting decision tree)

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Embodiment Construction

[0052] In order to clearly illustrate the technical features of this solution, the present invention will be described in detail below through specific implementation modes and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and / or letters in different instances. This repetition is for the purpose of simplicity and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted herein to avoid unnecessarily limiting the...

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Abstract

An embodiment of the invention discloses a short-term load prediction method based on a GBDT (gradient boosting decision tree). The method comprises the following steps: acquiring historical load dataof N days before the prediction-waiting day, and forming an original data set A0; screening a data set B for constructing training samples from the original data set A0; constructing total sample set(X, Y) required for constructing a GBDT prediction model by the data set B; training and constructing a whole-day GBDT prediction model by the total sample set (X, Y), and prediction whole-day load vector of the prediction-waiting day according to the whole-day GBDT prediction model; segmenting the total sample set (X, Y) into 24 sample subsets by the hour, training and constructing hour GBDT prediction models respectively, and predicting 24-hour load vectors of the prediction-waiting day according to the hour GBDT prediction models; predicting the final load vector of the prediction-waitingday according to combination of the whole-day load vector and the 24-hour load vectors. The short-term load prediction precision is improved by sufficiently mining characteristics in the historical load data and constructing the different GBDT models.

Description

technical field [0001] The invention relates to the technical field of power system load forecasting, in particular to a short-term load forecasting method based on a gradient boosting decision tree. Background technique [0002] Load forecasting is to determine the load data at a specific time in the future based on many factors such as system operating characteristics, capacity increase decision-making, natural conditions and social influences, under the condition of meeting certain accuracy requirements, where load refers to the power demand (power) Or electricity consumption, load forecasting is an important content in power system economic dispatch. Accurate load forecasting can economically and rationally arrange the start and stop of power grid internal generator sets, maintain the safety and stability of power grid operation, reduce unnecessary rotating reserve capacity, reasonably arrange unit maintenance plans, ensure the normal production and life of the society, ...

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Application Information

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IPC IPC(8): H02J3/00
CPCH02J3/00H02J3/003
Inventor 张志郭亮徐新光梁波李琮琮孙东董贤光李付存杜艳王清陈祉如朱红霞
Owner 国网山东省电力公司营销服务中心(计量中心)
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