Power grid single large disturbance online detection method based on WAMS

A detection method and large disturbance technology, applied in the direction of instruments, complex mathematical operations, character and pattern recognition, etc., can solve problems such as programming difficulties, high calculation intensity, misjudgment, etc., to achieve wrong judgment results, fast detection speed, algorithm easy effect

Active Publication Date: 2016-08-10
韩小学
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The research on the detection of large disturbances in the power grid started relatively late. Most of the existing research methods are difficult to program and computationally intensive.
At present,

Method used

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  • Power grid single large disturbance online detection method based on WAMS
  • Power grid single large disturbance online detection method based on WAMS
  • Power grid single large disturbance online detection method based on WAMS

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] Example 1: Short circuit simulation

[0066] Taking the disturbance calculation example of the 3-machine 9-node system, the 3-machine 9-node system is as follows: image 3 shown. Using MATLAB software to select several typical examples of disturbance of the 3-machine 9-node system as input data for simulation. In the algorithm based on the support vector machine, continue to select the voltage amplitude and phase angle of the BUS1 bus as the monitoring bus for disturbance detection.

[0067] When short-circuit disturbance occurs on line Line1, the main protection on the bus side of Bus5 operates, the protection on the side of bus Bus4 does not operate, the circuit breaker CB4 is not disconnected, the second backup protection of the adjacent line line2 operates, and the circuit breaker CB1 is disconnected. at the same time, Figure 4 , 5 The changes of voltage amplitude and phase angle uploaded by PMU, and the information uploaded by SCADA at this time are shown in T...

Embodiment 2

[0082] Example 2: PMU uploads wrong information

[0083] Assuming that the data uploaded from the PMU contains certain error information, the data uploaded from the PMU and SCADA such as Figure 6 , 7 , get Table 5, use the method of information fusion to judge whether there is a disturbance in the power grid.

[0084] Table 5 Information collected by SCADA

[0085]

[0086] The detection process based on electrical quantity is shown in Table 6.

[0087] Table 6 Disturbance detection process

[0088]

[0089] The detection result based on the electrical quantity is that the system has a disturbance alarm at 2.15, and the alarm display time is 2.15S.

[0090] The result of the detection method based on the switching value is: within 2.15 seconds, the protection element does not act, and there is no disturbance in the power grid.

[0091] For the results of the two disturbance detection methods, the results of information fusion using the multi-source information fusi...

Embodiment 3

[0095] Example 3: Detection of single large disturbance in oilfield power grid

[0096] The substation and transmission voltage levels in an oil field are relatively complicated. The voltage levels of an oil field power grid include several voltage levels such as 110kV, 66kV and 35kV. Due to the hugeness and complexity of the oilfield power grid, a dot-line circuit simplification is performed on a variable area of ​​an oilfield power grid before the simulation verification, as shown in Figure 8 The protection circuit diagram of an oilfield is given.

[0097] A certain torch substation supplies power to Fengyun and Xinghuo substations via double-circuit lines. Below Fengyun substation, there are North Five Substations, North Ten Substations, North Nineteen Substations, North III-2 Substations, North Twenty Substations, North Seven Substations, and Xinghuo Substations. The five transformations in the belt, the eleventh transformation in the north, the seventeenth transformatio...

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Abstract

The invention discloses a power grid single large disturbance online detection method based on a WAMS. The method comprises steps of 1), information acquisition; 2), disturbance detection; 3), information fusion; and 4), diagnosis and decision. According to the method, the algorithm is simple, the detection speed is relatively fast, accuracy is relatively high, the precise phase angle information is provided through utilizing a PMU, so whether disturbance occurs is detected, and a determination problem that whether single large disturbance occurs is solved, moreover, as the uploaded information is with a certain error probability, whether disturbance occurs is verified by utilizing the data fusion theory in combination with the data uploaded by the WAMS and a SCADA, and a problem of an error large disturbance occurrence determination result caused by the error uploaded information is solved.

Description

technical field [0001] The invention relates to the technical field of power grid fault detection, in particular to a WAMS-based online detection method for a single large disturbance in a power grid. Background technique [0002] The vigorous construction of the West-to-East Power Transmission and National Networking project has brought my country's power grid construction into a new stage of vigorous development. During the "Twelfth Five-Year Plan" period, the State Grid is preparing to invest 500 billion yuan in the initial construction of the smart grid. The power grid (smartpower grids) refers to the intelligentization of the power grid. It is built on the basis of a high-speed two-way communication network, and uses advanced equipment, measurement methods, sensing technology, control methods and decision-making systems to make the operation of the power grid Safer, more reliable, more economical and environmentally friendly, the smart grid also has the advantages of bein...

Claims

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Application Information

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IPC IPC(8): G06Q50/06G06K9/62G06F17/18
CPCG06F17/18G06Q50/06G06F18/2411
Inventor 高金兰李宏玉徐建军闫丽梅任爽刘超黄雨晴陈永康
Owner 韩小学
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