Multi-phase state estimation method of power distribution network

A State Estimation, Distribution Network Technology

Inactive Publication Date: 2017-01-18
ZHUHAI XUJIZHI ELECTRIFIED WIRE NETING AUTOMATIONCO +1
View PDF2 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of these methods is that the measurement model is closer to the real situation. The disadvantages include that the covariance matrix changes from a diagonal matrix to a matrix with more off-diagonal elements, which reduces the solution efficiency of the state estimation. The direct correlation

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
  • Multi-phase state estimation method of power distribution network
  • Multi-phase state estimation method of power distribution network
  • Multi-phase state estimation method of power distribution network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] refer to figure 1 , the present invention provides a distribution network multi-phase state estimation method, comprising the following steps:

[0046] S1. Establishing the error model and measurement equation of the state estimation measurement model;

[0047] S2. Establishing multi-phase network constraints for state estimation;

[0048] S3. Establish a state estimation model according to the multiphase network constraints and the state estimation measurement model;

[0049] S4. Based on the established state estimation model, iterative optimization is performed to realize multi-phase state estimation of the distribution network.

[0050] Further as a preferred embodiment, the step S1 includes:

[0051] S11. According to the following formula, an error model of the state estimation measurement model is established:

[0052] e U ~ N ( 0 ...

Embodiment 2

[0078] This embodiment is the theoretical basis of Embodiment 1. The derivation process of the state estimation algorithm of Embodiment 1 is described in detail below:

[0079] 1) Establishment of SE measurement model

[0080] The measurement model in state estimation mainly includes two parts: the error model and the measurement equation.

[0081] 1.1 Error model

[0082] The three-phase direct measurement of distribution network includes two parts: voltage transformer (PT) and current transformer (CT). These two parts provide voltage amplitude measurement, current amplitude measurement, voltage phase angle measurement and current phase measurement. Angle measures satisfy the assumption of independent normal distributions. The measurement of active power and reactive power is an indirect measurement, which is calculated from PT and CT measurements through the calculation unit. The error link from the sensor to the control center of the power grid quantity measurement inclu...

Embodiment 3

[0136] This embodiment is an example of applying Embodiment 1 to perform multiphase state estimation, specifically as follows:

[0137] (1) Case analysis

[0138] Taking the IEEE4 node system as an example, the effectiveness of this method is illustrated. It is assumed that there are nodal voltage amplitude, branch current amplitude and power factor angle measurements in all branches. The initial power flow result of the system corresponding to each measured value is x 0 , each quantity measurement satisfies (μ=x 0 ,σ=0.01*u) normal distribution.

[0139] After 100 simulation calculations using this estimation method, the distribution of state estimation results is counted. On average, each state estimation iteration is 10 times, and the average calculation time is 0.018s. The comparison between the estimated results and the actual situation is as follows figure 2 , image 3 ,and Figure 4 as shown, figure 2 Indicates the load phase A current, image 3 Indicates th...

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 multi-phase state estimation method of a power distribution network. The method comprises the following steps that S1) an error mode and a measurement equation of a state estimation and measurement model are established; S2) multi-phase network constraints of state estimation are established; S3) according to the multi-phase network constraints and the state estimation and measurement model, a state estimation model is established; and S4) on the basis of the established state estimation model, iteration optimization is carried out, and multi-phase state estimation of the power distribution network is realized. The method can be used to avoid conversion error caused by indirect measurement, the calculating efficiency is high, an estimation result is relatively accurate, and the method can be widely applied to state estimation industries of the power distribution network.

Description

technical field [0001] The invention relates to the field of power system operation and control, in particular to a multi-phase state estimation method of a distribution network. Background technique [0002] State estimation (StateEstimation, SE) provides reliable basic operation data for distribution network analysis and optimization, and is the core function of distribution management system. The traditional distribution network state estimation method considers that the branch and node power measurements are independent and uncorrelated random variables that satisfy the normal distribution. Excellent state quantity. Research results in recent years have shown that many power measurements in distribution networks are based on indirect measurements derived from direct measurements, and voltage, current, and active and reactive power measurements have a strong correlation. In order to describe the correlation between indirect measurement and direct measurement, it is nece...

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
IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 李长春李杰孙宝来秦卫东王华飞杜鹏田新成
Owner ZHUHAI XUJIZHI ELECTRIFIED WIRE NETING AUTOMATIONCO
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products