Academic Papers: [1]Yong-LIANG LIANG, Ke-Jun Li, Chen-xian Guo, And ming-yang Li.Economic Scheduling of Compressed Natural Gas Main Station Critical Peak Pricing [J]. Applied Energy，2021, V292，15 june 2021, 116937. (SCI District, TOP) [2]Yongliangliang, zhongyi zhang, Ke-Jun Li, yu-chuan Li. New Correlation Features for Dga-Based Transformer Fault Diagnosis Based on Maximal Information Coefficient [J], High Voltage, 2022; 7: 302–313. (SCI District, TOP) [3]y. LIANG, k. Li, z. Ma and w. lee.Typical Fault Cause Recognition of Single-PHASE-TO-GROUD FAULT for Overhead Lines.IEEE Transactions on Industry Applications, 2020，56(6): 6298-6306. (SCI No. 2) [4]y. LIANG, k. -J. Li, z. Ma and w. -j. Lee.Multilabel Classification Model for Type ReCognition of Single-Phase-Cround Fault Based on Knn-Bayesian Method [J].IEEE Transactions on Industry Applications, 2021，57(2): 1294-1302. (SCI No. 2 District) [5]Liang Yongliang, Wu Yuebin, Ma Zhao*, et al.. The new generation of low -voltage DC power supply system in the "new infrastructure" application technical analysis and development outlook. China Electrical Engineering Journal, 2021, 41 (1): 13-24. [6]yongliang liang，xin Jin，Yongduan Xue，et al.Type Recognition of Single-PHASE-TO-GROUND FAULTS in Nonsolidly Earthed Distribution Networks-Marchitecture and Method[J]. Internetal Transactions on Electrical Energy Systems， 2019，29，E12071. (District 4，if: 1.692) [7]Liang Yongliang，Guo Hanzheng，Xue Yongduan.Diagnosis method of transformer -based transformer -based transformer -based features [J]. High voltage technology，2019，45(02)：386-392. [8]liang yl，Lin ZR，li kj，eT Al.Priority Assessment Model of on-Line Monitoring Devices Investment for Power Transformers [J]. Journal of intelligent & Fuzzy Systems，2018，35(01):589-599.(District 4, IF: 1.851) [9]Liang Yongliang，Li Kejun，Zhao Jianguo，et al. Transformer online monitoring device configuration priority evaluation model [J].，2016，40(08): 2562-2569. [10]Liang Yongliang，Li Kejun，Zhao Jianguo，et al. Research on dynamic adjustment strategies for transformer oil chromatography online monitoring cycle [J].，2014，34 (9): 1446-1453. [11]Liang Yongliang，Li Kejun，Niu Lin, etc..A optimization feature selection -Fast -related vector transformer fault diagnosis method[J]. Power grid technology，2013，37 (11): 3262-3267. [12]Liang Yongliang，Li Kejun，Niu Lin，et al. Transformer state evaluation Multi -level uncertain model [J].，2013，37 (22): 73-78. [13]Ma Zhao,Liang Yongliang*,Shang Yuwei,Zhang Zhongyi. Cigre SC6 2020 special report and active power distribution system development trend and outlook [J]. Power grid technology,2021,45 (04): 1471-1479. [14]Ma Chunyan，Duan Qing，Guo Yanxian，Liang Yongliang*，et al. The economic scheduling of the compressed natural gas plus the mother station of the peak and valley timely electricity price [J].，47 (02): 584-595. [15]Yang Fan，Jinxin，Shen Yu，Liang Yongliang*，et al. Multi -level classification and identification model of small current faults [J].，2018，42 (15): 186-191. Patent [1]A method of lurking a transformer -based transformer -based analysis method，ZL201710822442.8. 2020-11-24 Authorized。 [2]Transformer -based fault type recognition method based on the faulty characteristic gas association characteristics，ZL201810251648.4. 2020-07-28 Authorized。 [3]A multi -working conditions parameter recognizable transformer hotspot temperature prediction method，ZL 201610323832.6
Technology rewards [1]Data -based distribution network security controlled key technologies and applications, China Electric Power Enterprise Federation, Technical achievements, Provincial Ministry First Prize, 2021. [2]Safety and controllable key technologies and applications of power distribution network, National Power Grid Co., Ltd., Scientific and technological progress, Provincial Ministry Second Prize, 2022. [3]Single ground ground failure detection and identification key technologies and applications based on power distribution automation system, State Grid Hubei Electric Power Co., Ltd., Scientific and technological progressFirst Prize, 2020. [4]Single -phase grounding fault selection technology based on small data based on power grid -based big data; the first prize of science and technology progress in Texas，2022.
|
