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A Short-Term Load Forecasting Method for Microgrid Based on Spearman Rank and Rkelm

A short-term load forecasting and load forecasting technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as not very suitable for computing costs, and achieve the effect of improving accuracy and taking into account computing efficiency

Active Publication Date: 2021-11-23
SOUTH CHINA UNIV OF TECH
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  • Claims
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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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  • A Short-Term Load Forecasting Method for Microgrid Based on Spearman Rank and Rkelm
  • A Short-Term Load Forecasting Method for Microgrid Based on Spearman Rank and Rkelm
  • A Short-Term Load Forecasting Method for Microgrid Based on Spearman Rank and Rkelm

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Embodiment Construction

[0052] 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.

[0053] figure 1 It is a short-term load forecasting method of a microgrid based on Spearman rank and RKELM in the present invention. like figure 1 Shown, the inventive method comprises the steps:

[0054] Step A: Collect online data periodically and update the historical database, specifically including:

[0055] 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.

[0056] Step B: Preprocessing historical data and extracting load sample features, which specifically includes the following steps:

[0057] Step B1: Normalize the historical data and scale it to the [0,1] interval, the formula is as follows:

[0058]

[0059] w...

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Abstract

The present invention proposes a short-term load forecasting method for microgrids based on SPSS and RKELM, including steps: (1) collecting online data and periodically updating the historical database (2) preprocessing historical data and extracting load sample characteristics; (3) constructing Offline load forecasting model; (4) Use the Spearman rank correlation method to select historical samples similar to the precursor load of the point to be predicted as online training samples; (5) Calculate the load in the future according to the online training samples and the offline load forecasting model Predictive value. This method uses the rapid simplified kernel function extreme learning machine (RKELM), chaotic particle swarm algorithm and Spearman rank correlation screening (RKELM), and establishes a prediction model including offline parameter optimization and online load; through periodic update of model parameters to Ensure the timeliness of the algorithm, reduce the complexity of online prediction calculations, reduce the amount of historical data storage, reduce computing costs, and can more accurately predict short-term and ultra-short-term loads of microgrids.

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 Spearman rank and RKELM [0002] technical background [0003] 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 distr...

Claims

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Application Information

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Patent Type & Authority Patents(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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