Active power distribution network dynamic virtual cluster division method based on model prediction control

A technology of model predictive control and active distribution network, applied in the direction of electrical components, circuit devices, photovoltaic power generation, etc., can solve the problem of continuous changes in the state of the power grid, the difficulty of cluster division results to meet the operation control of the active distribution network, and fluctuations in the output of distributed energy and other problems, to achieve the effect of moderate number of nodes, simplified dynamic cluster division process, and stable cluster division results

Active Publication Date: 2020-05-01
NANJING UNIV OF SCI & TECH
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the distributed energy output in the active distribution network is constantly fluctuating, and the state of the power grid is constantly c

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
  • Active power distribution network dynamic virtual cluster division method based on model prediction control
  • Active power distribution network dynamic virtual cluster division method based on model prediction control
  • Active power distribution network dynamic virtual cluster division method based on model prediction control

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0087] Example

[0088] In order to verify the effectiveness of the solution of the present invention, in figure 2 The simulation experiment is performed in the modified IEEE33 node power distribution system shown. In the experiment, the intraday cluster division rolling optimization link is set to 30min as the step size, ie ΔT=30, the starting period is 30min, and the solution time is 2h in the future, ie M=4; the real-time feedback correction link is set to 10min as the starting period.

[0089] 1) System parameter setting

[0090] Nodes 8 and 30 are installed with controllable distributed energy sources, with controllable active and reactive power output. Nodes 14 and 25 are installed with photovoltaics, and nodes 24 and 32 are installed with wind turbines. Photovoltaics and wind turbines have uncontrollable power and controllable reactive power.

[0091] The distributed energy installation nodes and installed capacity are shown in Table 1.

[0092] Table 1 DG installation capacit...

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 an active power distribution network dynamic virtual cluster division method based on model prediction control. The method comprises steps of performing cluster power supply rate constraint verification and rolling optimization by taking a rolling optimization time period as a time period division basis and combining the cluster power supply rate constraint and a rolling optimization objective function, and determining a cluster division scheme in the first rolling optimization time period in the future; utilizing a feedback correction time period as a time period division basis, in combination with a feedback correction objective function, performing feedback correction of a cluster division scheme obtained by rolling optimization once in each feedback correction time period in the first rolling optimization time period in the future, and determining a cluster division scheme of each feedback correction time period in the first rolling optimization time periodin the future. The method is advantaged in that dynamic closed-loop cluster division optimization is formed according to real-time information feedback, the actual working condition change of the system can be effectively tracked, and the adverse effect of prediction deviation and distributed energy fluctuation on active power distribution network partition control is eliminated.

Description

technical field [0001] The invention relates to a virtual cluster division technology of an active distribution network, in particular to a dynamic virtual cluster division method of an active distribution network based on model predictive control. Background technique [0002] The extensive use of renewable distributed energy (Distributed Generation, DG) is an important means to solve the energy crisis. The active distribution network technology has received extensive attention because it can accommodate a large number of DGs and improve the quality and reliability of power supply for users. However, the output of distributed energy is intermittent and uncertain, which brings great difficulties to the operation control of active distribution network. [0003] At present, the common distributed renewable power regulation methods mainly include micro-grid mode, centralized control and cluster control mode. Among them, the cluster-based control method can make full use of th...

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): H02J3/00H02J3/46
CPCH02J3/00H02J3/46Y04S10/50
Inventor 沈紫峰柳伟杨镇宁朱肖镕李娜游建斌
Owner NANJING UNIV OF SCI & TECH
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