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
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[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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