Research on security and stability verification technology for power grid planning based on multi-source data fusion

doi:10.3969/j.issn.2097-0706.2023.06.006

Abstract

Abstract:

A safety and stability system plays an important role in preventing the power system from large cascading failure blackouts under extreme disasters. Since the single-source data can hardly reflect the volatile weather conditions，multi-source data including the meteorological data for power grid planning are fused by spatio-temporal griding. The influence of multi-source data fusion on the security and stability verification system for power grid planning is studied， and the improvement of the proposed system on power grid's early warning is analyzed. Validated by a provincial power grid，the system extends its data collection range from the internal system to the natural environment，so as to extend early-warning objectives from single-fault risk to clustered fault risk caused by disasters. The results show that the fusion of multi-source data can effectively optimize the power network security and stability check based on single-source data，complete the unification and integration of multi-source data， improve the reliability of calculation data，and facilitate the application of power grid security and stability check.

Key words: multi-source data, security and stability, analysis and early warning, control decision, extreme disaster, power system, grid security

CLC Number:

TK01：TM73

NI Jie, LI Chen, QIN Tian, WU Xiaoxiao, ZHOU Xia, MA Daoguang. Research on security and stability verification technology for power grid planning based on multi-source data fusion[J]. Integrated Intelligent Energy, 2023, 45(6): 42-48.

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References 17

[1]	王伟胜, 林伟芳, 何国庆, 等. 美国得州2021年大停电事故对我国新能源发展的启示[J]. 中国电机工程学报, 2021, 41(12):4033-4043.
	WANG Weisheng, LIN Weifang, HE Guoqing, et al. Enlightenment of 2021 Texas blackout to the renewable energy development in China[J]. Proceedings of the CSEE, 2021, 41(12):4033-4043.
[2]	吴勇军, 薛禹胜, 陆佳政, 等. 山火灾害对电网故障率的时空影响[J]. 电力系统自动化, 2016, 40(3):14-20.
	WU Yongjun, XUE Yusheng, LU Jiazheng, et al. Space-time impact of forest fire on power grid fault probability[J]. Automation of Electric Power Systems, 2016, 40(3):14-20.
[3]	罗剑波, 董希建, 崔晓丹, 等. 关于大型安全稳定控制系统可靠性研究的探讨[J]. 电力系统保护与控制, 2018, 46(8):65-72.
	LUO Jianbo, DONG Xijian, CUI Xiaodan, et al. Discussion on reliability of large scale security and stability control system[J]. Power System Protection and Control, 2018, 46(8):65-72.
[4]	范士雄, 刘幸蔚, 於益军, 等. 基于多源数据和模型融合的超短期母线负荷预测方法[J]. 电网技术, 2021, 45(1):243-250.
	FAN Shixiong, LIU Xingwei, YU Yijun, et al. Multi-source data and hybrid neural network based ultra-short-term bus load forecasting[J]. Power System Technology, 2021, 45(1):243-250.
[5]	郭志民, 张永浩, 周兴华, 等. 基于多源数据融合策略的配电网停电故障分析[J]. 电网与清洁能源, 2018, 34(1):84-88.
	GUO Zhimin, ZHANG Yonghao, ZHOU Xinghua, et al. Analysis on the outage caused by the failure in distribution networks based on the multi-source data fusion strategy[J]. Power System and Clean Energy, 2018, 34(1):84-88.
[6]	陈彬, 倪明, 周霞, 等. 极端灾害下基于时空网格的配电网多源数据融合方法[J]. 中国电力, 2019, 52(11):77-84.
	CHEN Bin, NI Ming, ZHOU Xia, et al. Multi-source data fusion method for distribution network based on spatiotemporal grid under extreme disasters[J]. Electric Power, 2019, 52(11):77-84.
[7]	王卓容, 石庆鑫. 基于拓扑重构与分布式电源调度的配电网灾后恢复策略[J]. 综合智慧能源, 2022, 44(2):29-34. doi: 10.3969/j.issn.2097-0706.2022.02.005
	WANG Zhuorong, SHI Qingxin. Post-disaster restoration strategy of power distribution systems based on topology reconfiguration and distributed generation scheduling[J]. Integrated Intelligent Energy, 2022, 44(2):29-34. doi: 10.3969/j.issn.2097-0706.2022.02.005
[8]	赵丽莉, 李雪明, 倪明, 等. 继电保护与安全稳定控制系统隐性故障研究综述及展望[J]. 电力系统自动化, 2014, 38(22):128-135.
	ZHAO Lili, LI Xueming, NI Ming, et al. Review and prospect of research on hidden failures of protection system and security and stability control system[J]. Automation of Electric Power Systems, 2014, 38(22):128-135.
[9]	常东旭, 郭琦, 朱益华, 等. 多端混合直流与稳控系统的接口设计与仿真研究[J]. 电网技术, 2021, 45(9):3772-3780.
	CHANG Dongxu, GUO Qi, ZHU Yihua, et al. Interface design and simulation of multi-terminal hybrid HVDC and security and stability control system[J]. Power System Technology, 2021, 45(9):3772-3780.
[10]	谢云云, 薛禹胜, 王昊昊, 等. 电网雷击故障概率的时空在线预警[J]. 电力系统自动化, 2013, 37(17):44-51.
	XIE Yunyun, XUE Yusheng, WANG Haohao, et al. Space-time early-warning of power grid fault probability by lighting[J]. Automation of Electric Power Systems, 2013, 37(17):44-51.
[11]	陈彬, 于继来. 强台风环境下配电线路故障概率评估方法[J]. 中国电力, 2019, 52(5): 89-95.
	CHEN Bin, YU Jilai. Outage probability evaluation of the distribution corridors under strong typhoon environment[J]. Electric Power, 2019, 52(5): 89-95.
[12]	ESKANDARPOUR R, KHODAEI A. Machine learning based power grid outage prediction in response to extreme events[J]. IEEE Transactions on Power Systems, 2017, 32(4): 3315-3316. doi: 10.1109/TPWRS.2016.2631895
[13]	齐郑, 张首魁, 李志, 等. 考虑时间尺度的含DG配电网故障动态恢复策略[J]. 电力系统保护与控制, 2017, 45(16): 31-38.
	QI Zheng, ZHANG Shoukui, LI Zhi, et al. Dynamic service restoration strategy considering time scale for distribution network with DGs[J]. Power System Protection and Control, 2017, 45(16):31-38.
[14]	倪新宇, 茅大钧. 基于数据融合的超临界机组设备故障诊断研究[J]. 华电技术, 2018, 40(7): 5-9,77.
	NI Xinyu, MAO Dajun. Research on fault diagnosis technology of supercritical unit based on data fusion[J]. Huadian Technology, 2018, 40(7): 5-9,77.
[15]	YAN R, SAHA T K, BAI F, et al. The anatomy of the 2016 South Australia blackout: A catastrophic event in a high renewable network[J]. IEEE Transactions on Power Systems, 2018, 33(5): 5374-5388. doi: 10.1109/TPWRS.59
[16]	韩世旺, 赵颖, 张兴宇, 等. 面向碳中和的新型电力系统氢储能调峰技术研究[J]. 综合智慧能源, 2022, 44(9):20-26. doi: 10.3969/j.issn.2097-0706.2022.09.003
	HAN Shiwang, ZHAO Ying, ZHANG Xingyu, et al. Researches on hydrogen storage peak-shaving technology for new power systems to achieve carbon neutrality[J]. Integrated Intelligent Energy, 2022, 44(9):20-26. doi: 10.3969/j.issn.2097-0706.2022.09.003
[17]	罗丽琦, 王月, 钟海军, 等. 固体氧化物燃料电池热电联供系统设计[J]. 综合智慧能源, 2022, 44(8):25-32. doi: 10.3969/j.issn.2097-0706.2022.08.002
	LUO Liqi, WANG Yue, ZHONG Haijun, et al. Design of the CHP system integrated with SOFC[J]. Integrated Intelligent Energy, 2022, 44(8):25-32. doi: 10.3969/j.issn.2097-0706.2022.08.002

时间	经度/(°)	纬度/(°)	10级风圈/km	最大风速/(m·s^-1)	中心气压/kPa
01：00	117.1	19.6	50	31	94
03：00	116.8	19.8	50	32	94
05：00	116.2	20.2	50	30	94
07：00	115.8	20.4	50	30	94
09：00	115.3	20.7	48	35	95

故障描述	负载率	过载元件
鹏济甲线2500三永欢西乙线2873三相开断	105.55	鹏济乙线2501
鹏济甲线2500三永妈贤乙线2724三相开断	105.55	鹏济乙线2501
鹏济甲线2500三永	105.54	鹏济乙线2501

发电机名称	有功出力调整量	无功出力调整量
昭阳A厂 ^#1发电机	减少3.20	保持不变
昭阳A厂 ^#2发电机	减少39.30	保持不变
昭阳A厂 ^#3发电机	减少60.00	保持不变

变压器名称	有功负荷调整量	无功负荷调整量
济海站220 kV ^#1变压器	减少24.33	减少5.13
济海站220 kV ^#2变压器	减少24.27	减少5.45
济海站220 kV ^#3变压器	减少24.22	减少5.30
济海站220 kV ^#4变压器	减少24.58	减少5.58