Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Power flow model linearization error minimization method based on variable space optimal selection

A technology of variable space and power flow model, which is applied in the direction of AC networks with the same frequency from different sources, can solve the problems of lack of power flow calculation and optimal power flow verification, reduce linearization errors, reduce linear errors, and improve computational efficiency. sticky effect

Pending Publication Date: 2020-06-19
STATE GRID CHONGQING ELECTRIC POWER +2
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0016] 2) The existing linear power flow model analysis lacks the verification of power flow calculation and optimal power flow

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Power flow model linearization error minimization method based on variable space optimal selection
  • Power flow model linearization error minimization method based on variable space optimal selection
  • Power flow model linearization error minimization method based on variable space optimal selection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0058] The method of minimizing the linearization error of the power flow model based on the optimal selection of the variable space mainly includes the following steps:

[0059] 1) Using the finite-order Taylor expansion method to establish a linear power flow model based on the node space of the power system.

[0060] The main steps of establishing a linear power flow model based on the node space of the power system using the finite-order Taylor expansion method are as follows:

[0061] 1.1) Establish the power flow equation in the form of node injection, namely:

[0062]

[0063]

[0064] In the formula, P i and Q i are active power injection and reactive power injection of node i, respectively. j∈i represents the node set j connected to node i. the y ii =g ii +jb ii is the parallel admittance at node i. v i is the voltage amplitude of node i. P ij and Q ij are the active power and reactive power on the branch from node i to node j, respectively. θ ij i...

Embodiment 2

[0093] The experiment to verify the method of minimizing the linearization error of the power flow model with the optimal selection of the variable space mainly includes the following steps:

[0094] a) Historical scenarios of power flow calculation and optimal power flow

[0095] The present invention selects IEEE 30 and IEEE 118 and system power flow calculation and optimal power flow situation to verify and compare the error situation of this method and the traditional linear power flow model listed in Table 1. All cases contain different load fluctuations. These scenarios are divided into two categories, which are explained below:

[0096] 1) Sample scenarios: These scenarios are input into the optimal variable space selection model to obtain a linear power flow model with minimum linearization error.

[0097] 2) Test scenarios: These scenarios are used to test the accuracy of the linear power flow model in power flow calculation and OPF.

[0098] The input data informa...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a power flow model linearization error minimization method based on variable space optimal selection. The method mainly comprises the following steps: 1) establishing a linearpower flow model based on a power system node space by utilizing an finite-order Taylor expansion method, (2) establishing an optimal variable space selection model on the basis of the linear power flow model, and (3) inputting real-time power system parameters into the optimal variable space selection model to obtain an optimal variable space. The optimal variable space of the method proposed bythe present invention can effectively reduce the linear error when the operating state of the system fluctuates in a large range.

Description

technical field [0001] The invention relates to the field of power system and its automation, in particular to a method for minimizing the linearization error of a power flow model based on the optimal selection of variable space. Background technique [0002] The power flow equation is a nonlinear equation system that expresses the relationship between active power (P), reactive power (Q), voltage amplitude (v), and phase angle (θ). The basic constraints that need to be satisfied for the optimal power flow problem. The expression of the power flow equation is as follows: [0003] [0004] [0005] In the formula: the subscripts i and j are the start and end nodes of the branch respectively, and g ij , b ij are the conductance and susceptance on the branch from node i to node j, respectively. [0006] However, the nonlinear characteristics of power flow models lead to computational difficulties in some application scenarios, such as market clearing (safety-constrai...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/06
CPCH02J3/06
Inventor 古济铭张同尊张林史成钢朱小军杨知方樊哲新余娟冯楠董育霖刘本元
Owner STATE GRID CHONGQING ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com