Short-term load prediction method based on time sequence

A short-term load forecasting, time series technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as difficulty in achieving forecasting accuracy, and achieve the effect of improving management level

Inactive Publication Date: 2016-06-22
SHANGHAI MUNICIPAL ELECTRIC POWER CO
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Problems solved by technology

[0008] The power supply branch company undertakes the task of power supply in the area under its jurisdiction. Due to the rapid development of urban construction in the area under its jurisdiction in rec

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  • Short-term load prediction method based on time sequence
  • Short-term load prediction method based on time sequence
  • Short-term load prediction method based on time sequence

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with embodiment.

[0043] Usually the historical data of the load is sampled and recorded at a certain time interval. For a load record, its most important feature is that the load is always a variable that conforms to a certain statistical law, and is a random variable. The process described by this variable is a random process.

[0044] The basic principle of stochastic time series analysis is that the load sequence Y t can be simulated by the output of a linear filter whose input signal is a random sequence {e t}, often called white noise. Random inputs have a zero mean and unknown fixed variance.

[0045] According to the different characteristics of linear filters, time series models for processing single time series can be classified into: autoregressive model (AutoregressiveModel, AR), moving average model (MovingAverageModel, MA), autoregressive moving average model (AutoregressiveIntegrated...

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Abstract

The invention discloses a short-term load forecasting method based on time series, which belongs to the technical field of power supply. It conducts statistical analysis on the historical load of the existing regional power grid, and preprocesses the collected daily power consumption data to obtain a stable, normal, zero-mean time series; establishes a mathematical model based on the historical data of daily power load , use this mathematical model to describe the statistical regularity of the random variable change process of electric load; on the basis of this mathematical model, establish the mathematical expression of daily electric load forecasting, and predict the future load. In this technical solution, the power load to be measured is used as the dependent variable, and the past value of the power load is used as the independent variable. The obtained mathematical model successfully reflects the relationship between the dependent variable and the independent variable as well as the interference factors hidden in it. , especially suitable for short-term daily electricity load forecasting. It can be widely used in the fields of load forecasting and load management in power systems.

Description

technical field [0001] The invention belongs to the technical field of power supply, and in particular relates to a load forecasting method used in a power system. Background technique [0002] Load forecasting is the basis and premise of power system planning. [0003] With the rapid development of my country's economy and society and the rapid advancement of urbanization, cities have increasingly become important load centers, and the load forecasting work of urban power grids has attracted more and more attention. [0004] In recent years, the load forecasting methods of urban power grids have been continuously developed, and the load forecasting methods are also constantly changing. While meeting the needs of urban power grid planning and construction, it has strongly supported the scientific decision-making of urban power grid development. [0005] There are many factors that affect the change of urban power grid load. Compared with the large power grid load, the fluct...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 王颖韬任立丽吴静朱佳佳高靖宇朱江
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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