Multi-source fusion of distribution network operation data containing new energy sources based on joint Kalman filtering

Liyuan Liu; Jinman Luo; Haobo Liang; Shanlong Zhao

doi:10.1117/12.3034319

16 October 2024 Multi-source fusion of distribution network operation data containing new energy sources based on joint Kalman filtering

Liyuan Liu, Jinman Luo, Haobo Liang, Shanlong Zhao

Author Affiliations +

Proceedings Volume 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024); 132912A (2024) https://doi.org/10.1117/12.3034319
Event: Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 2024, Changchun, China

Abstract

At present, the constraint mechanism of multi-source fusion of distribution network operation data containing new energy is generally set as a single form, and the data fusion efficiency is low, resulting in an increase in the average absolute percentage error. Therefore, the design and analysis of multi-source fusion method of distribution network operation data containing new energy based on joint Kalman filter is proposed. According to the current measurement, first collect the characteristics of distribution network operation data, set up multi-source data fusion levels, adopt a multi-level approach, improve the overall efficiency of data fusion, and build a multi-level constraint mechanism. On this basis, a multi-source fusion model of distribution network operation data with new energy based on joint Kalman filter is constructed, and multisource data fusion is realized by mapping auxiliary processing. The final test results show that the average absolute percentage errors of the four randomly selected test areas within the coverage of H distribution network are well controlled below 1.2 after three cycles of measurement, which indicates that the designed multi-source fusion method of new energy distribution network operation data is more reliable and efficient with the help of the joint Kalman filter technology, The degree of data fusion is high, targeted, and has practical application value.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Liyuan Liu, Jinman Luo, Haobo Liang, and Shanlong Zhao "Multi-source fusion of distribution network operation data containing new energy sources based on joint Kalman filtering", Proc. SPIE 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 132912A (16 October 2024); https://doi.org/10.1117/12.3034319

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data fusion

Fusion energy

Data modeling

Signal filtering

Data conversion

Data processing

Power grids

Show All Keywords

Keywords/Phrases

Search In:

Publication Years