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Power system probabilistic state estimation method based on adaptive sparse pseudo-spectral method

A state estimation and power system technology, applied in computing, electrical components, circuit devices, etc., can solve the problems that the approximation function cannot guarantee the expected accuracy, the calculation efficiency of sampling results is low, and the accuracy of the approximation function cannot be accurately estimated.

Active Publication Date: 2017-09-26
TONGJI UNIV
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Problems solved by technology

However, this method also has the following disadvantages: 1) The termination criterion cannot accurately estimate the accuracy of the approximation function, resulting in that the obtained approximation function cannot guarantee the expected accuracy; In multi-output quantization problems, it is difficult to make full use of the sampling results and thus the computational efficiency is low

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  • Power system probabilistic state estimation method based on adaptive sparse pseudo-spectral method
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  • Power system probabilistic state estimation method based on adaptive sparse pseudo-spectral method

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Embodiment Construction

[0070] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0071] Such as figure 1 As shown, this embodiment provides a method for estimating a random state of a power system based on an adaptive sparse pseudospectrum method, including steps:

[0072] S1. Establish a stochastic state estimation model of the power system

[0073] The mathematical model of stochastic state estimation of power system based on weighted least square method is as follows:

[0074]

[0075] In the formula: i is the serial number; d is the total number of random measurements; N z is the total number of measurements, all N z measurement vector where Z i is a...

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Abstract

The invention relates to a power system probabilistic state estimation method based on an adaptive sparse pseudo-spectral method, comprising the following steps: (1) building a power system probabilistic state estimation model; and (2) using an adaptive sparse pseudo-spectral method to solve the power system probabilistic state estimation model. The calculation efficiency of power system probabilistic state estimation is improved while it is ensured that various types of measurement uncertainty can be handled and a credible state estimation result can be obtained. The amount of calculation can be determined automatically according to the accuracy requirement. The power system probabilistic state estimation method has the advantages of a wide range of application, high calculation efficiency, high flexibility, and the like.

Description

technical field [0001] The invention relates to a method for estimating a random state of a power system, in particular to a method for estimating a random state of a power system based on an adaptive sparse pseudospectral method. Background technique [0002] Power system state estimation is one of the most basic software in energy management system (EMS), the accuracy of its calculation results is of great significance to the analysis and control of power system. Most current state estimation methods aim at a certain type of objective function to achieve the maximum or minimum value, and calculate a set of estimated values ​​of the system state from a set of determined measured values. However, this type of deterministic state estimation method cannot determine the relationship between the calculated state estimation value and the state true value because it does not quantify the possible range of error between the measured value and the true value (ie measurement uncertai...

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Application Information

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IPC IPC(8): H02J3/00G06F17/50
CPCG06F30/20H02J3/00H02J2203/20Y02E60/00
Inventor 林济铿申丹枫刘阳升
Owner TONGJI UNIV
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