Personalized user short-term load forecasting algorithm based on decision-making tree

A short-term load forecasting and decision tree technology, which is applied in forecasting, calculation, data processing applications, etc., can solve the problems that user load forecasting has not been carried out in depth, and achieve the effect of realizing user short-term load forecasting and accurate user short-term load forecasting

Active Publication Date: 2015-12-23
STATE GRID CORP OF CHINA +3
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Problems solved by technology

At this stage, only the short-term load forecasting of the system and the short-term busbar

Method used

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  • Personalized user short-term load forecasting algorithm based on decision-making tree
  • Personalized user short-term load forecasting algorithm based on decision-making tree
  • Personalized user short-term load forecasting algorithm based on decision-making tree

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Embodiment Construction

[0032] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0033] Such as figure 1 As shown, the present invention proposes a personalized user short-term load forecasting algorithm based on a decision tree, which is characterized in that:

[0034] 1. Volatility component decision

[0035] First, identify the fluctuation component of the user load, and judge whether the zigzag fluctuation is significant, and the absolute average value of the fluctuation component exceeds 10%, which is considered significant. If it is significant, it will enter the fluctuation component extraction link, remove the zigzag fluctuation, and use the discrete wavelet transform to perform triple wavelet decomposition on the user load curve. If it is not significant, it will...

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Abstract

The invention discloses a personalized user short-term load forecasting algorithm based on a decision-making tree. The algorithm is characterized in that the algorithm comprises the following steps: carrying out fluctuating component identification on user load, and judging whether the sawtooth fluctuation thereof is obvious; if so, entering a fluctuating component extraction step, and then, obtaining power consumption mode number; and if not, directly obtaining the power consumption mode number. For the user, of whom the power consumption mode number is larger than 7, a nearest daily load forecasting method is adopted; for the user, of whom the power consumption mode number is within the range of 2-6, a user side short-term load forecasting method based on power consumption mode excavation is adopted; and for the user, of whom the power consumption mode number is only 1, a cluster forecast reduction method is adopted. According to the algorithm, by carrying out data mining on historical load of the user, the power consumption modes of the user are extracted; the personalized user short-term load forecasting algorithm is established according to the number of the power consumption modes; and therefore, accurate user short-period load prediction is realized.

Description

technical field [0001] The invention belongs to the field of power system demand side management, in particular to a short-term load forecasting algorithm for personalized users based on a decision tree. Background technique [0002] Orderly use of electricity is an important part of demand-side management, which refers to the control of part of the demand for electricity in accordance with the law through administrative measures, economic means, and technical methods under the circumstances of insufficient power supply and emergencies, and maintains the order of power supply and consumption. management work. After the reform and opening up, the country's economy has accelerated and the supply and demand of electricity have been tense, so orderly electricity consumption has played an important role. [0003] Intelligent and orderly power consumption automatically generates an orderly power consumption plan by using intelligent agent technology by analyzing the user load cha...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 易永仙范洁颜庆国陈霄杨斌薛溟枫童星周玉金萍郭兴昕崔高颖
Owner STATE GRID CORP OF CHINA
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