基于随机网络演算的分布式能源调控系统时延上界计算

doi:10.19595/j.cnki.1000-6753.tces.191802

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Abstract As a large number of distributed energy resources are connected to the grid for operation, the determinability of communication delay and network control become the keys to ensure the stable operation of the system. This paper studied the distributed energy system based on Ethernet communication and proposed a calculation method of transmission delay boundary using stochastic network calculus theory. With the establishment of self-similar traffic model, we use delay guarantee services and weighted fair queuing mechanism scheduling algorithms at the network nodes to concretize the random service curve and derive the end-to-end transmission delay boundary of distributed energy communication network, which could effectively overcome traditional queuing theory that can cause the problem of network control failure due to calculating the average delay only and omitting the long delay. Finally, the accuracy of the numerical calculation results of the delay boundary of the stochastic network algorithm proposed in this paper is verified by experiments that take into account the tightly coupled analysis model of distributed energy physical equipment and communication networks constructed by OPNET simulation software. The research provides an accurate analysis of the transmission characteristics of different communication architectures and provides theoretical support at the communication level for distributed energy networked control.

Key words： Distributed energy resource stochastic network calculus service curve end-to-end transmission delay bound

Received: 23 December 2019

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TM734

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	Meng Guangyu
	Yu Jiexiao
	Yang Ting

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Meng Guangyu,Yu Jiexiao,Yang Ting. Upper Bound Calculation of Delay of Distributed Energy Resource Coordinated-Control System Based on Stochastic Network Calculus[J]. Transactions of China Electrotechnical Society, 2020, 35(11): 2360-2371.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.191802 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I11/2360

[1] 范士雄, 蒲天骄, 刘广一, 等. 主动配电网中分布式发电系统接入技术及其进展[J]. 电工技术学报, 2016, 31(增刊2): 92-101.
Fan Shixiong, Pu Tianjiao, Liu Guangyi, et al.Technologies and its trends of grid integration of distributed generation in active distribution network[J]. Transactions of China Electrotechnical Society, 2016, 31(S2): 92-101.
[2] 丛鹏伟, 唐巍, 娄铖伟, 等. 含高渗透率可再生能源的主动配电网两阶段柔性软开关与联络开关协调优化控制[J]. 电工技术学报, 2019, 34(6): 1263-1272.
Cong Pengwei, Tang Wei, Lou Chengwei, et al.Two-stage coordination optimization control of soft open point and tie switch in active distribution network with high penetration renewable energy generation[J]. Transactions of China Electrotechnical Society, 2019, 34(6): 1263-1272.
[3] 李宇泽, 周念成, 侯健生, 等. 计及光伏发电低电压穿越不确定性的主动配电网短路电流概率评估[J]. 电工技术学报, 2020, 35(3): 564-576.
Li Yuze, Zhou Niancheng, Hou Jiansheng, et al.Probabilistic evaluation of short-circuit currents in active distribution grids considering low voltage ride-through uncertainty of photovoltaic[J]. Transactions of China Electrotechnical Society, 2020, 35(3): 564-576.
[4] 易文飞, 张艺伟, 曾博, 等. 多形态激励型需求侧响应协同平衡可再生能源波动的鲁棒优化配置[J]. 电工技术学报, 2018, 33(23): 5541-5554.
Yi Wenfei, Zhang Yiwei, Zeng Bo, et al.Robust optimization allocation for multi-type incentive-based demand response collaboration to balance renewable energy fluctuations[J]. Transactions of China Electrotechnical Society, 2018, 33(23): 5541-5554.
[5] Lai Jingang, Lu Xiaoqing, Tang Ruoli, et al.Delay-tolerant distributed voltage control for multiple smart loads in AC microgrids[J]. ISA Transactions, 2019, 86: 181-191.
[6] Chen Gang, Zhao Zhongyuan.Delay effects on consensus-based distributed economic dispatch algorithm in microgrid[J]. IEEE Transactions on Power Systems, 2018, 33(1): 602-612.
[7] Xiong Linyun, Li Hao, Wang Jie.LMI based robust load frequency control for time delayed power system via delay margin estimation[J]. International Journal of Electrical Power & Energy Systems, 2018, 100: 91-103.
[8] Singh V P, Kishor N, Samuel P.Load frequency control with communication topology changes in smart grid[J]. IEEE Transactions on Industrial Informatics, 2016, 12(5): 1943-1952.
[9] Ghasempour A.Optimum packet service and arrival rates in advanced metering infrastructure architecture of smart grid[C]//IEEE Green Technologies Conference (Green Tech), Kansas City, MO, USA, 2016:1-5.
[10] Ghasempour A, Moon T K.Optimizing the number of collectors in machine-to-machine advanced metering infrastructure architecture for internet of things-based smart grid[C]//IEEE Green Technologies Conference (Green Tech), Kansas City, MO, USA, 2016: 51-55.
[11] Fidler M.A survey of deterministic and stochastic service curve models in the network calculus[J]. IEEE Communications Surveys & Tutorials, 2010, 12(1): 59-86.
[12] Muller C, Putzke M, Wietfeld C.Traffic engineering analysis of smart grid services in cellular networks[C]//IEEE Third International Conference on Smart Grid Communications, National Cheng Kung University, Taiwan, China, 2012: 252-257.
[13] 高昆仑, 王宇飞, 赵婷. 电网信息物理系统运行中信息-物理交互机理探索[J]. 电网技术, 2018, 42(10): 3101-3109.
Gao Kunlun, Wang Yufei, Zhao Ting.Exploration of cyber-physical interaction mechanism in power grid cyber-physical systems operation[J]. Power System Technology, 2018, 42(10): 3101-3109.
[14] 杨挺, 翟峰, 赵英杰, 等. 泛在电力物联网释义与研究展望[J]. 电力系统自动化, 2019, 43(13): 9-20, 53.
Yang Ting, Zhai Feng, Zhao Yingjie, et al.Explanation and prospect of ubiquitous electric power internet of things[J]. Automation of Electric Power Systems, 2019, 43(13): 9-20, 53.
[15] IEC 61850—90—7 Communication networks and systems for power utility automation-object models for power converters in distributed energy resources (DER) system[S].
[16] Yang Ting, Zhao Rui, Zhang Weixin, et al.On the modeling and analysis of communication traffic in intelligent electric power substations[J]. IEEE Transactions on Power Delivery, 2017, 32(3): 1329-1338.
[17] 李昌超, 康忠健, 于洪国, 等. 考虑电力业务重要性的电力通信网关键节点识别[J]. 电工技术学报, 2019, 34(11): 2384-2394.
Li Changchao, Kang Zhongjian, Yu Hongguo, et al.Identification of key nodes in power communication network[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2384-2394.
[18] Budka K C, Deshpande J G, Doumi T L, et al.Communication network architecture and design principles for smart grids[J]. Bell Labs Technical Journal, 2010, 15(2): 205-227.
[19] Wang P, Akyildiz I F.Improving network connectivity in the presence of heavy-tailed interference[J]. IEEE Transactions on Wireless Communications, 2014, 13(10): 5427-5439.
[20] Iftikhar M, Mathkour H, Imran M, et al.A novel framework for G/M/1 queuing system based on scheduling-cum-polling mechanism to analyze multiple classes of self-similar and LRD traffic[J]. Wireless Networks, 2016, 22(4): 1269-1284.
[21] 郝唯杰, 杨强, 李炜. 基于FARIMA模型的智能变电站通信流量异常分析[J]. 电力系统自动化, 2019, 43(1): 158-169.
Hao Weijie, Yang Qiang, Li Wei.FARIMA model based analysis of communication traffic anomaly in smart substation[J]. Automation of Electric Power Systems, 2019, 43(1): 158-169.
[22] Karasaridis A, Hatzinakos D.Network heavy traffic modeling using α-stable self-similar processes[J]. IEEE Transactions on Communications, 2001, 49(7): 1203-1214.
[23] Jiang Yuming, Liu Yong.Stochastic network calculus[M]. London U K: Springer-Verlag, 2008.
[24] Jiang Yuming, Yin Qinghe, Liu Yong, et al.Fundamental calculus on generalized stochastically bounded bursty traffic for communication networks[J]. Computer Networks, 2009, 53(12): 2011-2021.
[25] Jensen Tue V, de Sevin Hugo, Greiner Martin, et al. The RE-Europe data set[DB/OL]. Zenodo, 2017, http://doi.org/10.5281/zenodo.999150
[26] Peng Chen, Li Jicai, Fei Minrui.Resilient event-triggered H-infinity load frequency control for networked power systems with energy-limited DoS attacks[J]. IEEE Transactions on Power Systems, 2017, 32(5): 4110-4118.