Substation Data Compression and Storage Method Based on Improved Revolving Door Algorithm

doi:10.11930/j.issn.1004-9649.202203116

Abstract

Abstract: In order to solve the data storage problem caused by the access of the substation supervisory control and data acquisition (SCADA) system to the data storage problem, a substation data compression and storage method based on the improved revolving door algorithm is proposed. Firstly, the lossy compression algorithm of the revolving gate is introduced, and in view of the shortcomings of fixed storage frequency, fixed threshold value and ignored abnormal points, the adaptive frequency conversion data storage strategy, the dynamic adjustment threshold value strategy and the abnormal point recording strategy are proposed to improve the accuracy of the algorithm. Secondly, the variable position storage method is adopted for the remote message, remote control and remote adjustment data of the SCADA system of the substation, and the improved revolving door algorithm is adopted for the telemetry data. Finally, the effectiveness of the proposed method was verified through numerical examples.

Key words: revolving door algorithm, data compression, algorithm improvement, SCADA system

YU Yang, ZHANG Hao, WANG Tongwen, WANG Wei, BIAN Ruien, LUO Nianhua. Substation Data Compression and Storage Method Based on Improved Revolving Door Algorithm[J]. Electric Power, 2023, 56(6): 202-208.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202203116

https://www.electricpower.com.cn/EN/Y2023/V56/I6/202

References

[1] 熊轲, 张锐晨, 王蕊, 等. 5G助力电力物联网: 网络架构与关键技术[J]. 中国电力, 2021, 54(3): 99–108
XIONG Ke, ZHANG Ruichen, WANG Rui, et al. 5G-enabled electricity Internet of Things: the network architecture and key technologies[J]. Electric Power, 2021, 54(3): 99–108
[2] 王立斌, 孙寻航, 杨迪, 等. 基于大数据的专变客户用能健康状态综合评价[J]. 智慧电力, 2021, 49(12): 96–103
WANG Libin, SUN Xunhang, YANG Di, et al. Comprehensive evaluation of energy utilization health status of specialized transformer customers based on big data[J]. Smart Power, 2021, 49(12): 96–103
[3] 谢清玉, 张耀坤, 李经纬. 面向智能电网的电力大数据关键技术应用[J]. 电网与清洁能源, 2021, 37(12): 39–46
XIE Qingyu, ZHANG Yaokun, LI Jingwei. Application of key technologies of power big data in smart grids[J]. Power System and Clean Energy, 2021, 37(12): 39–46
[4] 佘蕊, 张宁池, 王艳茹, 等. 面向电力物联网的5G通信认知无线电NOMA系统研究[J]. 中国电力, 2021, 54(5): 35–45
SHE Rui, ZHANG Ningchi, WANG Yanru, et al. Research on cognitive radio non-orthogonal multiple access system in 5G communications oriented to ubiquitous power Internet of Things[J]. Electric Power, 2021, 54(5): 35–45
[5] 赵鹏, 蒲天骄, 王新迎, 等. 面向能源互联网数字孪生的电力物联网关键技术及展望[J]. 中国电机工程学报, 2022, 42(2): 447–458
ZHAO Peng, PU Tianjiao, WANG Xinying, et al. Key technologies and perspectives of power Internet of Things facing with digital twins of the energy Internet[J]. Proceedings of the CSEE, 2022, 42(2): 447–458
[6] 许洪强, 蔡宇, 万雄, 等. 电网调控大数据平台体系架构及关键技术[J]. 电网技术, 2021, 45(12): 4798–4807
XU Hongqiang, CAI Yu, WAN Xiong, et al. Architecture and key technologies for big data platform in power grid[J]. Power System Technology, 2021, 45(12): 4798–4807
[7] 陈宏山, 徐舒, 李正红, 等. 计及5G通信异常工况的有源配电网快速综合保护方案[J]. 电力系统保护与控制, 2021, 49(15): 159–168
CHEN Hongshan, XU Shu, LI Zhenghong, et al. A new fast comprehensive protection scheme of an active distribution network considering the abnormal operating conditions of 5G communication[J]. Power System Protection and Control, 2021, 49(15): 159–168
[8] 王毅, 陈启鑫, 张宁, 等. 5G通信与泛在电力物联网的融合: 应用分析与研究展望[J]. 电网技术, 2019, 43(5): 1575–1585
WANG Yi, CHEN Qixin, ZHANG Ning, et al. Fusion of the 5G communication and the ubiquitous electric Internet of Things: application analysis and research prospects[J]. Power System Technology, 2019, 43(5): 1575–1585
[9] 高厚磊, 徐彬, 向珉江, 等. 5G通信自同步配网差动保护研究与应用[J]. 电力系统保护与控制, 2021, 49(7): 1–9
GAO Houlei, XU Bin, XIANG Minjiang, et al. Research and application of self-synchronized differential protection for distribution networks using 5G as the communication channel[J]. Power System Protection and Control, 2021, 49(7): 1–9
[10] 高维良, 高厚磊, 徐彬, 等. 5G用作配电网差动保护通道的可行性分析[J]. 电力系统保护与控制, 2021, 49(8): 1–7
GAO Weiliang, GAO Houlei, XU Bin, et al. Feasibility analysis of adopting 5G in differential protection of distribution networks[J]. Power System Protection and Control, 2021, 49(8): 1–7
[11] 向珉江, 袁通, 苏善诚, 等. 基于5G授时的配网差动保护数据同步方案[J]. 电力系统保护与控制, 2021, 49(8): 8–15
XIANG Minjiang, YUAN Tong, SU Shancheng, et al. 5G timing base data synchronization scheme for differential protection of distribution networks[J]. Power System Protection and Control, 2021, 49(8): 8–15
[12] 张建雨, 姜睿智, 李俊刚, 等. 基于5G通信的配电网差动保护技术研究[J]. 电力系统保护与控制, 2021, 49(7): 17–23
ZHANG Jianyu, JIANG Ruizhi, LI Jungang, et al. Research on differential protection of a distribution network based on 5G communication[J]. Power System Protection and Control, 2021, 49(7): 17–23
[13] 赵伟博, 董玉明, 莫娟, 等. 电力与通信共享铁塔的关键技术与商业模式[J]. 中国电力, 2021, 54(11): 171–180
ZHAO Weibo, DONG Yuming, MO Juan, et al. Key technologies and business model of shared towers for power and communication[J]. Electric Power, 2021, 54(11): 171–180
[14] 窦健, 郑国权, 郄爽, 等. 用电信息采集系统的相关性数据压缩方案研究[J]. 电测与仪表, 2021, 58(10): 80–86
DOU Jian, ZHENG Guoquan, QIE Shuang, et al. Research on correlation data compression scheme of power information acquisition system[J]. Electrical Measurement & Instrumentation, 2021, 58(10): 80–86
[15] 马发勇, 厉启鹏, 马志斌, 等. 电力调度SCADA系统中历史数据压缩及存储策略[J]. 电网技术, 2014, 38(4): 1109–1114
MA Fayong, LI Qipeng, MA Zhibin, et al. The research of historical data compression and storage strategy in power dispatch SCADA system[J]. Power System Technology, 2014, 38(4): 1109–1114
[16] 郑宗强, 翟明玉, 彭晖, 等. 电网调控分布式SCADA系统体系架构与关键技术[J]. 电力系统自动化, 2017, 41(5): 71–77
ZHENG Zongqiang, ZHAI Mingyu, PENG Hui, et al. Architecture and key technologies of distributed SCADA system for power dispatching and control[J]. Automation of Electric Power Systems, 2017, 41(5): 71–77
[17] 胡春潮, 侯艾君, 马凯, 等. 基于OPNET的电网SCADA系统通信建模与仿真[J]. 电力系统保护与控制, 2016, 44(10): 54–59
HU Chunchao, HOU Aijun, MA Kai, et al. Communication modeling and simulation of SCADA system of power grid based on OPNET[J]. Power System Protection and Control, 2016, 44(10): 54–59
[18] 赵洪山, 马利波. 基于张量Tucker分解的智能配电网大数据压缩[J]. 中国电机工程学报, 2019, 39(16): 4744–4752, 4976
ZHAO Hongshan, MA Libo. Big data compression of smart distribution systems based on tensor tucker decomposition[J]. Proceedings of the CSEE, 2019, 39(16): 4744–4752, 4976
[19] 徐旭东, 付艳萍. SCADA中历史数据的SDT算法研究与改进[J]. 计算机工程与科学, 2018, 40(6): 999–1004
XU Xudong, FU Yanping. SDT algorithm and its improvement for historical data in SCADA[J]. Computer Engineering & Science, 2018, 40(6): 999–1004
[20] 曾文序, 库少平, 郑浩. 基于旋转门算法的自适应变频数据采集策略[J]. 计算机应用研究, 2018, 35(3): 769–772
ZENG Wenxu, KU Shaoping, ZHENG Hao. Strategy of self-adaptive frequency conversion data acquisition based on swing door trending algorithm[J]. Application Research of Computers, 2018, 35(3): 769–772
[21] 王爽, 陆月明. 基于旋转门算法的安全网关控制信息采集策略[J]. 网络与信息安全学报, 2018, 4(10): 59–67
WANG Shuang, LU Yueming. Information acquisition strategy for security gate-ways based on swing door trending algorithm[J]. Chinese Journal of Network and Information Security, 2018, 4(10): 59–67
[22] 孙浩飞, 吕新良, 琚泽立, 等. 基于小波变换和嵌入式零树编码的电力录波有损压缩应用[J]. 电网与清洁能源, 2020, 36(6): 31–38, 44
SUN Haofei, LÜ Xinliang, JU Zeli, et al. Application of power disturbance data compression based on wavelet transform and EZW coding[J]. Power System and Clean Energy, 2020, 36(6): 31–38, 44
[23] 李添正, 王春桃. 基于马尔可夫随机场的加密二值图像有损压缩算法[J]. 计算机应用, 2020, 40(5): 1354–1363
LI Tianzheng, WANG Chuntao. Lossy compression algorithm for encrypted binary images using Markov random field[J]. Journal of Computer Applications, 2020, 40(5): 1354–1363
[24] 王鹤, 李石强, 于华楠, 等. 基于分布式压缩感知和边缘计算的配电网电能质量数据压缩存储方法[J]. 电工技术学报, 2020, 35(21): 4553–4564
WANG He, LI Shiqiang, YU Huanan, et al. Compression acquisition method for power quality data of distribution network based on distributed compressed sensing and edge computing[J]. Transactions of China Electrotechnical Society, 2020, 35(21): 4553–4564
[25] 袁莉芬, 刘韬, 何怡刚, 等. 基于LSA-MP改进原子分解的电能质量数据压缩方法[J]. 电子测量与仪器学报, 2022, 36(1): 98–108
YUAN Lifen, LIU Tao, HE Yigang, et al. Power quality data compression method based on lightning search algorithm and atomic decomposition[J]. Journal of Electronic Measurement and Instrumentation, 2022, 36(1): 98–108