Power big data oriented microgrid short-period load prediction method

A technology of short-term load forecasting and short-term load, which is applied in the direction of electrical digital data processing, forecasting, and data processing applications. The effect of improving execution efficiency

Inactive Publication Date: 2017-04-19
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

However, these methods still have the problem of insufficient prediction accuracy, and they all run on m

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  • Power big data oriented microgrid short-period load prediction method
  • Power big data oriented microgrid short-period load prediction method
  • Power big data oriented microgrid short-period load prediction method

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with accompanying drawing.

[0031] 1 Design of load forecasting model based on ISFLA_KELM

[0032] 1.1 Design idea of ​​ISFLA_KELM forecasting model

[0033] Compared with the traditional power load, the load base of the microgrid is small, the power consumption characteristics of each period are greatly different, and the random fluctuation of the load sequence is large. Because the short-term load forecasting method of the traditional power system usually cannot fully consider the external factors that affect the load change, it is applied to The short-term load forecasting of microgrid shows obvious deficiencies, and the forecasting effect is not good. The kernel function extreme learning machine has strong regression prediction ability, and has been applied to short-term load forecasting of microgrid, but the combination parameters of KELM still need to be further optimized, and the hybrid leapfr...

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Abstract

A power big data oriented microgrid short-period load prediction method is used for improving prediction precision for a microgrid short-period load. The power big data oriented microgrid short-period load prediction method is characterized by comprising the steps of firstly establishing a microgrid short-period load prediction model based on a kernelized extreme learning machine (KELM); then optimizing a combined parameter (C,sigma) of the kernelized extreme learning machine by means of an improved shuffled frog leaping algorithm (ISFLA), and obtaining an ISFLA-KELM prediction model; and finally predicating the microgrid short-period load by means of the ISFLA-KELM prediction model. According to the power big data oriented microgrid short-period load prediction method, the ISFLA-KELM prediction model is utilized for predicating the microgrid short-period load. An experiment represents a fact that the KELM has relatively high regression forcasting capability. Furthermroe the ISFLA algorithm has high optimization capability and the parameter of the KELM can be optimized, thereby greatly improving prediction precision for the microgrid short-period load.

Description

technical field [0001] The invention relates to a method capable of accurately predicting the short-term load of a microgrid, which belongs to the technical field of power generation. Background technique [0002] A microgrid is a small power generation and distribution system that organically integrates distributed power sources, loads, energy storage devices, converters, and monitoring and protection devices. Short-term load forecasting is an important part of microgrid economic dispatch. The size will directly affect the economy of grid operation. Compared with the large power grid environment, it is more difficult to implement short-term load forecasting for user-side microgrids. In order to improve the accuracy of load forecasting, many scholars have conducted a lot of research and proposed a series of forecasting methods, such as the load forecasting method based on sparse heteroscedastic Gaussian process; the method of using two-layer structure for microgrid load for...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/12G06Q10/04G06Q50/06
CPCG06F30/20G06N3/126G06Q10/04G06Q50/06Y02P80/14
Inventor 王保义牛锐张少敏
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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