Short-period load prediction method for microgrid based on SPSS and RKELM

A short-term load forecasting and load forecasting technology, applied in forecasting, instrument, character and pattern recognition, etc., can solve problems such as not very suitable for calculation cost, and achieve the effect of improving accuracy and taking into account calculation efficiency

Active Publication Date: 2018-04-20
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

However, these methods are not very suitable for load forecasting of microgrids with higher load randomness or higher computational costs

Method used

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  • Short-period load prediction method for microgrid based on SPSS and RKELM
  • Short-period load prediction method for microgrid based on SPSS and RKELM
  • Short-period load prediction method for microgrid based on SPSS and RKELM

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Embodiment Construction

[0051] The implementation of the present invention will be further described below in conjunction with the accompanying drawings and examples, but the implementation and protection of the present invention are not limited thereto.

[0052] figure 1 It is a short-term load forecasting method of a microgrid based on SPSS and RKELM in the present invention. Such as figure 1 Shown, the inventive method comprises the steps:

[0053] Step A: Collect online data periodically and update the historical database, specifically including:

[0054] The data is collected online through the data collection device, and the historical database is updated every day, and the database saves the data of the previous 30 days.

[0055] Step B: Preprocessing historical data and extracting load sample features, which specifically includes the following steps:

[0056] Step B1: Normalize the historical data and scale it to the [0,1] interval, the formula is as follows:

[0057]

[0058] where x...

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Abstract

The invention proposes a short-period load prediction method for a microgrid based on SPSS and RKELM, and the method comprises the steps: (1), carrying out the online data collection, and periodicallyupdating a historical database; (2), carrying out the preprocessing of historical data, and extracting load sample features; (3), constructing an offline load prediction model; (4), screening a historical sample similar to a to-be-predicted point precursor load as an online training sample through SRC (Spearman Rank Correlation); (5), calculating a load prediction value at a future moment according to the online training sample and the offline load prediction model. The method employs a rapid RKELM (Reduced Kernel Extreme Learning Machine), a chaos particle swarm optimization algorithm and the SRC, and achieves the building of a prediction model comprising offline parameter optimization and an online load. Through the periodic updating of model parameters, the method guarantees the timeliness of an algorithm, reduces the complexity of online prediction and calculation, reduces the storage quantity of historical data, reduces the calculation cost, and can achieve the more accurate prediction of the short-period and super-short-period loads of the microgrid.

Description

technical field [0001] The invention belongs to the technical field of microgrid load forecasting, in particular to a short-term load forecasting method for microgrids based on SPSS and RKELM technical background [0002] Microgrid refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. Through the controllability of power supply and load in the microgrid, the grid-connected operation or independent operation of the microgrid is realized. The microgrid appears as an overall unit externally, and at the same time, it can be smoothly merged into the main grid for operation, meeting the user's requirements for power quality and power supply security. With the rapid development of new energy and new technologies, distributed power generation is gradually popularized and applied. The microgrid can promote the access of distributed clean ener...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62
CPCG06Q10/04G06Q50/06G06F18/2113
Inventor 杨荣照杨苹陈夏沈志钧余伟洲张云飞陈亦平张勇候君莫维科高琴
Owner SOUTH CHINA UNIV OF TECH
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