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Probabilistic Static Voltage Stability Margin Optimization Realization Method

A technology of static voltage stability and voltage stability margin, applied in the field of obtaining probabilistic static voltage stability margin based on quasi-Monte Carlo simulation and kernel density estimation, to achieve high calculation accuracy

Active Publication Date: 2020-02-14
SHANGHAI MUNICIPAL ELECTRIC POWER CO +2
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

However, most of the traditional methods are based on deterministic models, ignoring uncertain factors such as load fluctuations, generator failures and new energy generation fluctuations.

Method used

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  • Probabilistic Static Voltage Stability Margin Optimization Realization Method

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Embodiment Construction

[0021] Such as figure 1 As shown, this embodiment uses the IEEE 118 standard system as an example for illustration:

[0022] In this embodiment, the system is divided into four partitions A, B, C, and D. Zone A includes nodes 1-33, zone B includes nodes 34-59, zone C includes nodes 60-79, and zone D includes nodes 80-118. Set the active and reactive power of the node load to obey the normal distribution, and the expectation is equal to the active and reactive power of the load under the basic working condition. The coefficient of variation (standard deviation / expectation) is: 7% in area A, 4% in area B, and 9% in area C. D area 5%. Each generator is equivalent to 4 identical units, and the failure probability of each unit is 0.09. Set the sampling scale to 1000, use QMC (quasi-Monte Carlo) to obtain input variable samples, use the direct method to calculate the voltage stability critical point, and obtain the stability margin samples, then use DKDM to obtain the probability ...

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Abstract

A method of acquiring a probability static state voltage stabilization margin based on Quasi monte carlo simulation and kernel density estimation is disclosed. The method comprises the following steps of according to power grid data, carrying out pretreatment to acquire an input random variable matrix; and then using a diffusion-based kernel density method (DKDM) to acquire a probability density of a voltage stabilization margin and cumulative probability distribution. In the invention, through introducing the Quasi monte carlo simulation, an input random variable sample is acquired so as to increase calculating efficiency of a simulation method; the diffusion-based kernel density method is used to accurately acquire a probability distribution function of the stabilization margin; and only a small sampling scale is needed and high calculating precision can be acquired.

Description

technical field [0001] The invention relates to a technology in the field of power system control, in particular to a method for obtaining a probabilistic static voltage stability margin based on pseudo-Monte Carlo simulation and kernel density estimation. Background technique [0002] With the development of my country's power system, accelerating the development of hydropower in the southwest, large-scale development of wind power and solar power generation, and relying on UHV and smart grids to transport clean energy located in the central and western regions to the eastern load center are the main ways to fully implement the national new energy development plan. Under such a development model, the scale of DC power received by some power grids in eastern my country has increased significantly, and the output demand of internal units has decreased. , specifically as follows: 1) Strong feed-in: the power receiving ratio is greatly increased, 2) Weak start-up: the internal s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 李禹鹏崔勇冯楠杨增辉苏运郭强严正徐潇源马骏宇
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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