Big data-based electrical load prediction system

A technology of electricity load and forecasting system, which is applied in the field of power system, can solve problems such as no strict explanation, difficulty in determining, and unreasonable situation of obvious increase and decrease trend of historical data, etc.

Inactive Publication Date: 2016-01-13
广州威沃电子有限公司
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Problems solved by technology

[0057] The exponential smoothing method described above is an interval prediction method limited by historical data. It is not accurate enough to predict the future trend of things, and it is even more unreasonable for the obvious increase or decrease trend of historical data.
Although, some books introduce that when the historical data presents a "linear trend", it can be processed by multiplying the difference between the output of primary smoothing and the

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  • Big data-based electrical load prediction system

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Embodiment Construction

[0106] The following describes specific implementation cases of the present invention in conjunction with the accompanying drawings:

[0107] Such as figure 1 As shown, the electricity load forecasting system based on big data uses an error back propagation neural network method to predict the future electricity load of a certain place. The error back propagation neural network method includes an input layer and a hidden layer. And output layer, set:

[0108] The input vector in the input layer is ……, ,..., ;

[0109] The hidden layer output vector is ……, ,..., ;

[0110] The output vector of the output layer is ……, ,..., ;

[0111] The expected output vector is ……, ,..., ;

[0112] The weight matrix from the hidden layer to the output layer is represented by W, and the ……, ,..., , Where the column vector Is the weight vector corresponding to the kth neuron in the output layer; the weight matrix between the input layer and the hidden layer is represented by V, ……, ,......

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Abstract

The invention discloses a big data-based electrical load prediction system. According to the system, a prediction is carried out on the electric load capacity of one place in the future by an error back-propagation neural network method; the error back-propagation neural network method comprises an input layer, a hidden layer and an output layer; a mathematic model of the error back-propagation neural network method can be established through a function relationship among the input layer, the hidden layer and the output layer; input layer information corresponds to historical data of the electric load capacity; output layer information corresponds to predicted data of the electric load capacity; and the hidden layer corresponds to the function relationship between the predicted data and the historical data. According to the big data-based electrical load prediction system, the prediction is carried out the electric load capacity in the future by the error back-propagation neural network method; and the mathematic model of the error back-propagation neural network method is established, so that the prediction result is relatively accurate; the error can be accurately calculated; and a great convenience is brought to life.

Description

Technical field [0001] The invention relates to the field of power systems, in particular to a power load forecasting system based on big data. Background technique [0002] In the power system, if the total electricity load of a city in the next month can be known in advance, the power plant can adjust the operating time of the generator set, arrange the shutdown time of a generator in advance, and perform maintenance, which can be effective Extend the service life of the generator and improve its efficiency and reliability. For another example, if the total electricity load of a certain area in the next month can be known in advance, then the substation can adjust the operating time of the transformer group, arrange the downtime of a certain transformer in advance, and perform maintenance, which can effectively extend the transformer’s Life span and improve its efficiency and reliability. Similarly, if a mine or a factory can predict the electricity consumption in the next sta...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 张晓炜
Owner 广州威沃电子有限公司
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