基于储能云架构的能源工业互联网平台研究与应用

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (4096 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Energy storage system has been playing an important part in implementation of energy interconnection. With the in-depth research on battery characteristics, mechanism model and predictive diagnosis, a more digital and intelligent energy storage cyber-physical system can be obtained through the integration of big data technology and artificial intelligence. Therefore, according to the concept of the industrial internet, a battery management system based on energy storage cloud architecture is proposed to achieve ubiquitous device access, big data analysis, energy management, intelligent evaluation and other functions. Furthermore, the functional framework and typical application scenarios of energy storage cloud-computing are represented. Finally, the energy industry internet platform is introduced. A flexible and interactive intelligent control system of energy storage, which can participate in the control of demanded quantities and peak shaving, is established to coordinate the operation of photovoltaic and electricity load. The verification results show that the energy industry internet platform can realize economical operation of comprehensive energy.

Key words： energy storage system cloud architecture the industry internet ubiquitous access optimal control

Received: 24 January 2022

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHANG Jiyuan
	SUN Jianyang
	WANG Weihong

Cite this article:

ZHANG Jiyuan,SUN Jianyang,WANG Weihong. Research and application of the energy industry internet platform based on energy storage cloud architecture[J]. Electrical Engineering, 2022, 23(8): 68-74.

URL:

http://dqjs.cesmedia.cn/EN/Y2022/V23/I8/68

[1] 陈国平, 李明节, 许涛, 等. 关于新能源发展的技术瓶颈研究[J]. 中国电机工程学报, 2017, 37(1): 20-26.
[2] 吴建中. 欧洲综合能源系统发展的驱动与现状[J]. 电力系统自动化, 2016, 40(5): 1-7.
[3] 蒲天骄, 陈盛, 赵琦, 等. 能源互联网数字孪生系统框架设计及应用展望[J]. 中国电机工程学报, 2021, 41(6): 2012-2028.
[4] 李欣然, 黄际元, 陈远扬, 等. 大规模储能电源参与电网调频研究综述[J]. 电力系统保护与控制, 2016, 44(7): 145-153.
[5] 叶小晖, 刘涛, 吴国旸, 等. 电池储能系统的多时间尺度仿真建模研究及大规模并网特性分析[J]. 中国电机工程学报, 2015, 35(11): 2635-2644.
[6] 马钊, 周孝信, 尚宇炜, 等. 能源互联网概念、关键技术及发展模式探索[J]. 电网技术, 2015, 39(11): 3014-3022.
[7] BOTTA A, DE DONATO W, PERSICO V, et al.Integration of cloud computing and internet of things: a survey[J]. Future Generation Computer Systems, 2016, 56: 684-700.
[8] GRIEVES M, VICKERS J.Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems[M]//Transdisciplinary Perspectives on Complex Systems. Cham: Springer, 2017: 85-113.
[9] ERDINC O, PATERAKIS N G, MENDES T D P, et al. Smart household operation considering bi-directional EV and ESS utilization by real-time pricing-based DR[J]. IEEE Transactions on Smart Grid, 2015, 6(3): 1281-1291.
[10] 张永旺, 赵伟, 肖勇, 等. 基于分层架构的大规模电动汽车有序充电仿真平台[J]. 电网技术, 2015, 39(1): 55-62.
[11] FRIANSA K, HAG I N, SANTI B M, et al.Development of battery monitoring system in smart microgrid based on internet of things (IoT)[J]. Procedia Engineering, 2017, 170: 482-487.
[12] KIM T, MAKWANA D, ADHIKAREE A, et al.Cloud-based battery condition monitoring and fault diagnosis platform for large-scale lithium-ion battery energy storage systems[J]. Energies, 2018, 11(1): 125.
[13] 康重庆, 刘静琨, 张宁, 等. 未来电力系统储能的新形态: 云储能[J]. 电力系统自动化, 2017, 41(21): 2-8.
[14] 李琳, 秦泽宇, 刘啸, 等. 电网侧储能电站监控信息接入验收管控方法研究[J]. 电气技术, 2021, 22(7): 7-12.
[15] 王昀, 谢海鹏, 孙啸天, 等. 计及激励型综合需求响应的电-热综合能源系统日前经济调度[J]. 电工技术学报, 2021, 36(9): 1926-1934.
[16] 周长城, 马溪原, 郭祚刚, 等. 面向工程应用的用户级综合能源系统规划[J]. 电工技术学报, 2020, 35(13): 2843-2854.
[17] 徐峰, 何宇俊, 李建标, 等. 考虑需求响应的虚拟电厂商业机制研究综述[J]. 电力需求侧管理, 2019, 21(3): 2-6.
[18] 傅晓梅, 温步瀛, 唐雨晨, 等. 考虑电池储能运行特性的微网优化运行[J]. 电气技术, 2021, 22(4): 12-19.