收藏切换
Distributed Photovoltaic Data Compression Algorithm Based on Boundary Feature Identification and K-Dimensional Tree Optimization
收藏切换
PDF
Zhan SHI1, Jiajia FU1, Zhongmiao KANG1, Yutu LIANG1, Zhongyu ZHANG2, Lihui WANG2
Journal of Telemetry, Tracking and Command | 2025, 46(6) : 85 - 94
Less
收藏切换
Journal of Telemetry, Tracking and Command | 2025, 46(6): 85-94
TT & C Communication and Navigation
Distributed Photovoltaic Data Compression Algorithm Based on Boundary Feature Identification and K-Dimensional Tree Optimization
Full
Zhan SHI1, Jiajia FU1, Zhongmiao KANG1, Yutu LIANG1, Zhongyu ZHANG2, Lihui WANG2
Affiliations
  • 1. Guangdong Power Grid Co., Ltd., Guangzhou, 510600, China
  • 2. School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China
doi: 10.12347/j.ycyk.20250228001
Outline
收藏切换

A data compression collaborative algorithm that integrates transmission optimization and delay control was proposed to address the data dimension explosion and complexity increase caused by the large-scale grid connection of distributed photovoltaic systems. Firstly, based on the theory of decision boundary sensitivity, an optimization framework for minimizing total delay was constructed, and an enhanced inter-class boundary preservation algorithm (EIPB) was proposed to reduce the amount of transmitted data by dynamically maintaining key instances of decision boundaries. Secondly, the traditional distance instance selection method was improved by proposing an enhanced instance selection algorithm (EIS) based on K-dimensional tree (KD-Tree) spatial partitioning, which utilized nearest neighbor search acceleration technology to enhance instance selection efficiency. Then, a dynamic error allocation sector lossless compression algorithm (DEASC) was proposed, which achieved collaborative optimization of compression efficiency and fidelity through adaptive slope constraints and multi-stage entropy encoding. Experimental verification showed that the EIPB-EIS joint algorithm improved the average compression ratio to 7.8 compared to traditional methods, reduced the root mean square error of reconstruction percentage to 0.51%, and reduced transmission delay by 62.7%, effectively solving the problem of efficient transmission and accurate reconstruction of high-dimensional photovoltaic data.

Distributed photovoltaics  /  Data compression  /  Delay optimization  /  Preservation of inter class boundaries  /  Dynamic error allocation
Zhan SHI, Jiajia FU, Zhongmiao KANG, Yutu LIANG, Zhongyu ZHANG, Lihui WANG. Distributed Photovoltaic Data Compression Algorithm Based on Boundary Feature Identification and K-Dimensional Tree Optimization[J]. Journal of Telemetry, Tracking and Command, 2025 , 46 (6) : 85 -94 . DOI: 10.12347/j.ycyk.20250228001
Year 2025 volume 46 Issue 6
PDF
112
51
Cite this Article
BibTeX
Article Info
doi: 10.12347/j.ycyk.20250228001
  • Receive Date:2025-02-28
  • Online Date:2026-03-13
Article Data
Affiliations
History
  • Received:2025-02-28
  • Revised:2025-04-09
Funding
Affiliations
    1. Guangdong Power Grid Co., Ltd., Guangzhou, 510600, China
    2. School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China
References
Share
https://castjournals.cast.org.cn/joweb/ycyk/EN/10.12347/j.ycyk.20250228001
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT