Predicting method for short-term load of power system

A short-term load forecasting and electricity load technology, applied in forecasting, data processing applications, instruments, etc., can solve the problems that traditional mathematical models are difficult to obtain effective prediction accuracy, hyperparameters are difficult to establish, and calculation speed is slow, so as to avoid neural network Effects of training and parameter setting, improving accuracy, improving simplicity and speed

Active Publication Date: 2018-07-06
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
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Problems solved by technology

In order to fully mine data information and improve prediction accuracy, traditional mathematical models often use methods of increasing data dimensions or subdividing data, which can achieve fast and accurate predictions under certain conditions, but when the data dimension is low and the amount of data is small At that time, for complex and changeable power loads, due to its random and non-periodic effects, it is difficult for traditional mathematical models to obta

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  • Predicting method for short-term load of power system
  • Predicting method for short-term load of power system
  • Predicting method for short-term load of power system

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Embodiment

[0061] figure 1 It is a flow chart of a short-term load forecasting method for power system of the present invention.

[0062] In this embodiment, as figure 1 As shown, a method for predicting short-term load of a power system according to the present invention includes the following steps:

[0063] S1. Extract user-side load data from the smart meter

[0064] S1.1. Collect the electricity load data of each user from each smart meter terminal. In this embodiment, the active power is selected as the collected load data;

[0065] S1.2. Superimpose the power load data of each user to obtain regional load data close to the power generation side;

[0066] In this embodiment, the load data of a user-side monitoring point from April 8 to April 28, 2017 is extracted, where the sampling interval is 15 minutes, 96 points a day, a total of 2016 points, and 2016 points Connect to get a load curve of a certain user such as figure 2 Shown

[0067] S1.3. Perform hierarchical clustering of regional ...

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Abstract

The invention discloses a predicting method for short-term load of a power system. Active power of load data is used as a data basis; through dividing the data decomposing frequency to every stable frequency component from high to low, and then predicting a low frequency component and a medium high frequency component by a multiple linear regression and LSTM neutral network; finally, predicted results are overlapped to obtain a complete predicting result; thus the shortcoming that a traditional load predicting method is hard to effectively predict local features of the high frequency ; meanwhile, the change trend of the load can be exactly predicted, the predicting effectiveness under a complex condition is improved.

Description

Technical field [0001] The present invention belongs to the technical field of power load forecasting, and more specifically, relates to a method for forecasting short-term load of a power system. Background technique [0002] With the development of the electricity market and the gradual increase in user demand, the safe and economic operation of the power grid has become critical. Accurate short-term forecasting of power load can effectively ensure the safe operation of the power grid, reduce power generation costs, meet user needs, and improve social and economic benefits. Since the production, transmission, distribution, and supply and consumption of electric energy are almost completed at the same time, electric energy, as a relatively special energy source, is difficult to store in large quantities. This makes the power generation output of the power system consistent with the changes in system load at any time to achieve dynamic balance. Satisfy the relationship between s...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/06375G06Q50/06
Inventor 武鑫黄琦邓带雨李坚胡维昊张真源李晨井实易建波王妮杨云聪
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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