Method for dynamic state estimation of natural gas network considering dynamic characteristics of natural gas pipelines

Patent metadata

Field	Value
Publication number	US-11972182-B2
Application number	US-202117322912-A
Country	US
Kind code	B2
Filing date	May 18, 2021
Priority date	May 25, 2020
Publication date	Apr 30, 2024
Grant date	Apr 30, 2024

Abstract

Provided is a method for a dynamic state estimation of a natural gas network considering dynamic characteristics of natural gas pipelines. The method can obtain a result of the dynamic state estimation of the natural gas network by establishing an objective function of the dynamic state estimation of the natural gas network, a state quantity constraint of a compressor, a state quantity constraint of the natural gas pipeline and a topological constraint of the natural gas network, and using a Lagrange method or an interior point method to solve a state estimation model of the natural gas network. The method takes the topological constraint of the natural gas network into consideration, and employs a pipeline pressure constraint in a frequency domain to implement linearization of the pipeline pressure constraint, thereby obtain a real-time, reliable, consistent and complete dynamic operating state of the natural gas network.

First claim

What is claimed is:

1. A method for a dynamic state estimation of a natural gas network considering dynamic characteristics of natural gas pipelines to obtain a real-time, reliable and complete operating state of the natural gas network, the method comprising:
step 1 of establishing a time-domain window and a frequency-domain window for the dynamic state estimation of the natural gas network, the step 1 comprising:
sub-step 1-1 of defining a time-domain window width as I t , where I t is a positive integer, and a value of I t is determined by a dispatcher of the natural gas network; defining a u-th sampling time point in the time-domain window as τ u =τ−uΔt, u=0, 1, . . . , I t −1, where τ represents a current time point of the natural gas network, and Δt represents a sampling interval of the natural gas network; defining a current time-domain window width as I t,e , where I t,e is a positive integer, and a value of I t,e is determined by the dispatcher of the natural gas network; and defining a historical time-domain window width as I t,h where I t,h is a positive integer, and a value of I t,h is determined by the dispatcher of the natural gas network, wherein I t , I t,e and I t,h satisfy the following relational expression:
I t =I t,e +I t,h ; and

sub-step 1-2 of defining a frequency-domain window width as I f , where a value of I f is determined by the dispatcher of the natural gas network; and defining a d-th frequency component in the frequency-domain window as ω d , d=0, 1, . . . , I f −1, where ω d is calculated by the following formula:

ω
d

=

d

I
t

·
Δ

⁢

⁢
t

.

step 2 of constructing a measurement vector for the dynamic state estimation of the natural gas network, the step 2 comprising:
sub-step 2-1 of acquiring, from a data acquisition and monitoring control system of the natural gas network, all operation data of the natural gas network at a sampling time point τ u in the time-domain window where the current time point τ of the natural gas network belongs, wherein the all operation data of the natural gas network comprises: a measurement value z G + ,u i p of a natural gas flow at a head end of each pipeline in the natural gas network, and a measurement value z G − ,u i p of a natural gas flow at a tail end of each pipeline in the natural gas network, where i p represents a serial number of a pipeline in the natural gas network; a measurement value z G + ,u i c of a natural gas flow at a head end of each compressor, and a measurement value z G − ,u i c of a natural gas flow at a tail end of each compressor, where i c represents a serial number of a compressor; a pressure measurement value z pr,u i n of each node of the natural gas network, where i n represents a serial number of a node of the natural gas network; a measurement value z gs,u i s of a natural gas flow of each natural gas source, where i s represents a serial number of a natural gas source; and a measurement value z gl,u i l of a natural gas flow of each natural gas load, where i l represents a serial number of a natural gas load; and
sub-step 2-2 of constructing a measurement vector z u for the dynamic state estimation of the natural gas network at the sampling time point τ u :

z
u

=

[

Z

G
+

,
u

Z

G
-

,
u

Z

pr
,
u

Z

gs
,
u

Z

gl
,
u

]

,

where z G + ,u represents a column vector consisting of all the measurement values z G + ,u i p of natural gas flows at head ends of respective pipelines in the natural gas network and all the measurement values z G + ,u i c of natural gas flows at head ends of respective compressors at the sampling time point τ u ; z G − ,u represents a column vector consisting of all the measurement values z G − ,u i p of natural gas flows at tail ends of respective pipelines in the natural gas network and all the measurement values z G − ,u i c of natural gas flows at tail ends of respective compressors at the sampling time point τ u ; z pr,u represents a column vector consisting of all the pressure measurement values z pr,u i n of respective nodes of the natural gas network at the sampling time point τ u ; z gs,u represents a column vector consisting of all the measurement values z gs,u i s of natural gas flows of respective natural gas sources in the natural gas network at the sampling time point τ u ; and z gl,u represents a column vector consisting of all the measurement values z gl,u i l of natural gas flows of respective natural gas loads in the natural gas network at the sampling time point τ u ;
step 3 of constructing a state vector x u for the dynamic state estimation of the natural gas network at the sampling time point τ u :

x
u

=

[

Assignees

• Univ Tsinghua

Inventors

• Sun Hongbin
• Guo Qinglai
• Wang Bin
• Yin Guanxiong
• Pan Zhaoguang
• Chen Binbin

Classifications

• G06F30/28 Primary

  using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD] · CPC title

• G06F17/16

  Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

• G06F2111/10

  Numerical modelling · CPC title

• G06F30/18 Primary

  Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling (circuit design at the physical level G06F30/39; network planning tools for wireless communication networks H04W16/18) · CPC title

• F17D5/005

  of gas pipelines, e.g. alarm · CPC title