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New energy microgrid residual power prediction method, computer equipment and storage medium

A technology of surplus power and prediction method, which is applied in the field of electric power dispatching, can solve problems such as electric power prediction that does not include power generation, achieve multiple economic and social benefits, improve optimized management, and ensure safe and stable operation

Pending Publication Date: 2022-05-13
NANYANG POWER SUPPLY COMPANY OF STATE GRID HENAN ELECTRIC POWER
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The invention does not include the prediction of power generation

Method used

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  • New energy microgrid residual power prediction method, computer equipment and storage medium
  • New energy microgrid residual power prediction method, computer equipment and storage medium
  • New energy microgrid residual power prediction method, computer equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] The purpose of this embodiment 1 is to provide a new energy microgrid residual power prediction method, such as figure 1 As shown, the predictive assessment includes:

[0042] 1. In step S1, training is performed based on sample data to obtain a residual power prediction model.

[0043] This step S1 is mainly to use sample data to train a residual power prediction model. Specifically, such as figure 2 As shown, step S1 includes:

[0044] (1) Step S11, acquiring sample data.

[0045] The sample data includes historical surplus power and historical meteorological data; the surplus power is the difference between the power generated by the microgrid as a whole and the electricity load.

[0046]Most of the microgrids are equipped with new energy sources such as photovoltaic power stations or wind farms. However, photovoltaic and wind power are affected by natural conditions, and their output power has large fluctuations and randomness. Therefore, it is necessary to con...

Embodiment 2

[0089] The purpose of this embodiment 2 is to provide a kind of computer equipment, and described computer equipment can be computer, also can be server, and its internal structure diagram can be as follows Figure 4 shown. The computer device includes a processor, a memory and a network interface connected through a system bus, wherein the processor of the computer device is used to provide computing and control capabilities. The memory of the computer equipment includes a non-volatile storage medium and an internal memory; the non-volatile storage medium stores an operating system, a computer program and a database; the internal memory is the operating system in the non-volatile storage medium and provide an environment for the operation of computer programs. The database of the computer equipment is used to store historical data, calculation models and the like. The network interface of the computer device is used to communicate with external devices through a network con...

Embodiment 3

[0092] The purpose of Embodiment 3 is to provide a computer device, including a memory and a processor, the memory is used for computer programs and data, and the processor invokes the computer program stored in the memory to execute the remaining power prediction method.

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Abstract

The invention provides a new energy microgrid residual power prediction method, computer equipment and a storage medium, and belongs to the technical field of power dispatching. The prediction method comprises the following steps: S1, training based on sample data to obtain a residual power prediction model; s2, performing residual power prediction by using the residual power prediction model; the step S1 comprises the following steps: S11, acquiring sample data, wherein the sample data comprises historical residual power data and historical meteorological data; s12, performing normalization processing on the sample data; s13, establishing an LSSVM (least square support vector machine) prediction model; s14, optimizing kernel parameters of the LSSVM model by using a particle swarm algorithm; and S15, constructing a residual power prediction model. According to the method, the short-term residual power of the new energy micro-grid is predicted, so that the optimization management of the micro-grid can be improved; according to the method, a large power grid dispatching center can be helped to predict the size and change condition of the residual power of the micro-grid, normalized and refined management of the micro-grid can be enhanced, and safe and stable operation of the large power grid is guaranteed.

Description

technical field [0001] The invention belongs to the technical field of electric power dispatching, and in particular relates to a method for predicting surplus power of a new energy microgrid, computer equipment and a storage medium. Background technique [0002] Microgrid is a small power system that integrates distributed power supply, power distribution system, monitoring system and power consumption system. It is an autonomous system with self-control and self-energy management. The microgrid can be operated in parallel with the large power grid or independently, which can improve the reliability of power supply and economic benefits, and bring various benefits to users. When the microgrid and the large grid are connected to the grid, when the electric energy in the microgrid cannot meet all the load demands, the external large grid plays the role of supplementing the electric energy to provide enough power for the electric load in the microgrid. When the power generati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N20/10G06N3/00H02J3/00
CPCG06Q10/04G06Q50/06H02J3/003G06N3/006G06N20/10
Inventor 张朋飞张庶王延平王鑫袁昉周林邵丽李宜珂
Owner NANYANG POWER SUPPLY COMPANY OF STATE GRID HENAN ELECTRIC POWER
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