Real-Time Generated Protection Settings Based Adaptive Current Protection for Transmission Line Considering High Proportion of New Energy Source

ZHANG Zhengwei, CHEN Qian, NIU Yinghao, FENG Yuan, ZHU Jiaao

Electric Power Construction ›› 2024, Vol. 45 ›› Issue (2) : 137-146.

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Electric Power Construction ›› 2024, Vol. 45 ›› Issue (2) : 137-146. DOI: 10.12204/j.issn.1000-7229.2024.02.012
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Real-Time Generated Protection Settings Based Adaptive Current Protection for Transmission Line Considering High Proportion of New Energy Source

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Abstract

The power sides of new power systems contain a large proportion of new energy sources. Owing to various types, distributed locations, and nonlinear outputs, the through-current level of the short circuit decreases, and its uncertainty increases when a fault occurs in the power grid, which makes it difficult for traditional current protection to preset and trip. Therefore, an adaptive current protection method based on real-time generated settings using local information is proposed, referring to traditional three-stage current protection. This method considers the actual fault characteristics of new energy sources to generate a preset. First, an equivalent source model is established that can distinguish the different outputs of new energy sources between generators and identify them online to obtain the unchanged parameters before and after the fault. Then, after a fault occurs, the local measured information is used to obtain the changeable parameters. Subsequently, preset values were generated in real-time based on the actual fault scenario and the actual output of new energy sources during the fault. Finally, the trip is decided based on the measured current and the preset value. Continuous identification before a fault occurs can effectively separate generators and new energy sources in the model. Online presetting based on actual fault scenarios and the output of new energy sources can effectively solve the problems of variety, distribution, and nonlinearity. The feasibility and correctness were verified by both analysis and comparison of various cases.

Key words

new power system / new energy source / current protection / real-time protection settings / equivalent source model

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Zhengwei ZHANG , Qian CHEN , Yinghao NIU , et al . Real-Time Generated Protection Settings Based Adaptive Current Protection for Transmission Line Considering High Proportion of New Energy Source[J]. Electric Power Construction. 2024, 45(2): 137-146 https://doi.org/10.12204/j.issn.1000-7229.2024.02.012

References

[1]
何廷一, 李胜男, 陈亦平, 等. 高比例新能源电网多源最优协同调频策略[J]. 电力建设, 2021, 42(10): 51-59.
Abstract
随着大规模可再生能源对电网渗透率的不断增加,大型风光电站也开始参与到电网的调频当中。首先,建立了功率响应总偏差、调频里程支出最小化的多目标互补控制模型,以解决不同调频资源的动态功率分配问题。为解决该非线性优化问题,采用多目标蝠鲼觅食优化算法(multi-objective manta ray foraging optimization, MMRFO)快速地获取高质量的Pareto前沿,以满足电网的实时在线调频需求,提高区域电网的动态响应能力。然后,基于熵权法,设计了灰靶决策法客观地选择不同功率扰动下兼顾运行经济性和电能质量的折中解。最后,基于扩展的两区域负荷频率控制(load frequency control,LFC)模型验证了所提方法的有效性。
HE Tingyi, LI Shengnan, CHEN Yiping, et al. Multi-source optimal coordinated frequency modulation strategy for high proportion new energy grid[J]. Electric Power Construction, 2021, 42(10): 51-59.

With the increasing penetration of large-scale renewable energy into the power grid, large-scale wind and solar power stations also begin to participate in the frequency regulation of the power grid. In order to solve the dynamic power allocation problem of different frequency-regulation resources, a multi-objective complementary control model with minimum total power deviation and regulation mileage payment is established. To solve the nonlinear optimization problem, the multi-objective manta ray foraging optimization algorithm (MMRFO) is adopted in this paper to quickly obtain high quality Pareto front to meet the real-time online frequency-regulation requirements of the power grid and improve the dynamic response capability of the regional power grid. Then, applying the entropy weight method, the grey target decision-making theory is designed to objectively select the compromise solution which takes into account both operation economy and power quality under different power perturbations. Finally, the validity of the proposed method is verified by an extended two-area load frequency control model.

[2]
董旭柱, 华祝虎, 尚磊, 等. 新型配电系统形态特征与技术展望[J]. 高电压技术, 2021, 47(9): 3021-3035.
DONG Xuzhu, HUA Zhuhu, SHANG Lei, et al. Morphological characteristics and technical prospect of new distribution system[J]. High Voltage Engineering, 2021, 47(9): 3021-3035.
[3]
贾科, 杨哲, 赵其娟, 等. 适用于新能源场站送出线路的高频突变量距离保护[J]. 电网技术, 2019, 43(9): 3271-3280.
JIA Ke, YANG Zhe, ZHAO Qijuan, et al. High-frequency catastrophe distance protection suitable for transmission lines of new energy stations[J]. Power System Technology, 2019, 43(9): 3271-3280.
[4]
钮厚敏, 贾科, 刘鑫, 等. 光伏直流升压场站并网整体协同低电压穿越控制策略[J]. 电力系统保护与控制, 2023, 51(8): 1-12.
NIU Houmin, JIA Ke, LIU Xin, et al. Low voltage ride-through control strategy for grid-connection of photovoltaic DC boost station[J]. Power System Protection and Control, 2023, 51(8): 1-12.
[5]
JAIN R, LUBKEMAN D L, LUKIC S M. Dynamic adaptive protection for distribution systems in grid-connected and islanded modes[J]. IEEE Transactions on Power Delivery, 2019, 34(1): 281-289.
[6]
向明旭, 杨高峰, 杨知方, 等. 电力现货市场出清中新能源随机波动特性表征方法及实例探讨[J]. 电力建设, 2023, 44(4): 8-17.
Abstract
新能源具有清洁低碳的“正外部性”,同时也具有随机波动的“负外部性”。当前电力现货市场主要基于运行经验调整出清边界以应对该随机波动特性,难以准确、解析反映新能源接入引起的源荷平衡特性变化,无法有效发挥电力现货市场在激发系统运行灵活性方面的调节作用。对此,文章分析了新能源随机波动特性对多重市场出清边界及成本特性的影响,并探讨了其在出清模型中的表征思路。随后,以调频里程服务为例,揭示了新能源特性对调频里程需求的影响,并提出计及机组调频里程响应模式的日内市场出清模型,可解析反映上述影响。仿真结果表明,所提方法能在提升系统频率性能的同时,保证系统运行经济性,验证了方法有效性。
XIANG Mingxu, YANG Gaofeng, YANG Zhifang, et al. Characterization method and case study of random fluctuation characteristics of new energy in spot market clearing of electricity[J]. Electric Power Construction, 2023, 44(4): 8-17.

Renewables have the “positive externalities” of clean and low-carbon. Meanwhile, they also have the “negative externalities” of uncertainties and fluctuations. To handle the aforementioned uncertainties and fluctuations, the current electricity spot market mainly adjusts the market clearing boundary according to the operating experiences, which cannot explicitly reflect the changes in the power balance characteristics caused by the integration of renewables. As a result, the regulation function of the electricity spot market on stimulating the flexibility of power system operation cannot be effectively performed. To solve this, the impact of uncertainties and fluctuations of renewables on multiple market clearing boundaries and cost characteristics is analyzed. The idea of characterizing the aforementioned impact in the market clearing model is explored. Then, taking the frequency-regulation mileage service as an example, the impact of renewables on the frequency-regulation mileage requirement is revealed. On the basis of these, the intra-day market clearing model considering the response mode of generators to the frequency-regulation mileage requirement is proposed, which can explicitly reflect the aforementioned impact. Simulation results demonstrate that the proposed method can improve the system frequency performance while guaranteeing the system economy performance, which validates the effectiveness of the proposed method.

[7]
刘慧媛, 肖繁, 张哲, 等. 新能源电源接入不平衡配电网的短路计算方法[J]. 电力系统自动化, 2019, 43(21): 177-186.
LIU Huiyuan, XIAO Fan, ZHANG Zhe, et al. Short circuit calculation method of new energy source connected to unbalanced distribution network[J]. Automation of Electric Power Systems, 2019, 43(21): 177-186.
[8]
李彦宾, 贾科, 毕天姝, 等. 电流差动保护在逆变型新能源场站送出线路中的适应性分析[J]. 电力系统自动化, 2017, 41(12): 100-105.
LI Yanbin, JIA Ke, BI Tianshu, et al. Adaptability analysis of current differential protection in transmission line of inverter new energy station[J]. Automation of Electric Power Systems, 2017, 41(12): 100-105.
[9]
梁营玉, 卢正杰. 基于补偿系数的有源配电网自适应电流差动保护[J]. 电网技术, 2022, 46(6): 2268-2275.
LIANG Yingyu, LU Zhengjie. Adaptive differential protection principle based on compensation coefficient for active distribution network[J]. Power System Technology, 2022, 46(6): 2268-2275.
[10]
黄景光, 李浙栋, 张宇鹏, 等. 计及后备保护优化级数的改进阻抗修正反时限过流保护整定方法[J]. 电网技术, 2022, 46(7): 2768-2777.
HUANG Jingguang, LI Zhedong, ZHANG Yupeng, et al. Setting optimization of improved impedance correction inverse time overcurrent protection considering backup protection optimization series[J]. Power System Technology, 2022, 46(7): 2768-2777.
[11]
JAMALI S, BORHANI-BAHABADI H. Protection method for radial distribution systems with DG using local voltage measurements[J]. IEEE Transactions on Power Delivery, 2019, 34(2): 651-660.
[12]
TELUKUNTA V, PRADHAN J, AGRAWAL A, et al. Protection challenges under bulk penetration of renewable energy resources in power systems: a review[J]. CSEE Journal of Power and Energy Systems, 2017, 3(4): 365-379.
[13]
王宁, 韩国栋, 高厚磊, 等. 有源配电网电流差动保护判据研究[J]. 电力系统保护与控制, 2023, 51(7): 14-23.
WANG Ning, HAN Guodong, GAO Houlei, et al. The current differential protection criterion of active distribution networks[J]. Power System Protection and Control, 2023, 51(7): 14-23.
[14]
高生凯, 曹炜, 张旭航, 等. 一种改进型配网自适应过流保护方法[J]. 电力系统保护与控制, 2021, 49(7): 110-119.
GAO Shengkai, CAO Wei, ZHANG Xuhang, et al. A novel adaptive overcurrent protection method for a distribution network[J]. Power System Protection and Control, 2021, 49(7): 110-119.
[15]
乔一达, 吴红斌, 吴通华, 等. 含逆变型分布式电源的配电网分区域电流保护[J]. 电工技术学报, 2022, 37(S1): 134-144.
QIAO Yida, WU Hongbin, WU Tonghua, et al. Regional current protection of distribution network with inverter distributed power supply[J]. Transactions of China Electrotechnical Society, 2022, 37(S1): 134-144.
[16]
翁汉琍, 樊荣, 饶丹青, 等. 分布式能源脱网和其本身特性改变对线路限时电流速断保护的影响及对策[J]. 电力系统及其自动化学报, 2023, 35(10): 33-40.
WENG Hanli, FAN Rong, RAO Danqing, et al. Influences of distributed energy resources off-grid and their attribute change on line time limited current protection and corresponding countermeasures[J]. Proceedings of the CSU-EPSA, 2023, 35(10): 33-40.
[17]
黄景光, 丁婧, 郑淑文, 等. 基于电流突变量的自适应过电流保护新原理[J]. 电力系统保护与控制, 2018, 46(7): 49-55.
HUANG Jingguang, DING Jing, ZHENG Shuwen, et al. A new adaptive over current protection principle based on current mutation[J]. Power System Protection and Control, 2018, 46(7): 49-55.
[18]
金甚达, 宋依群, 范春菊, 等. 考虑逆变电源控制策略的电流保护整定计算[J]. 电网技术, 2021, 45(9): 3690-3699.
JIN Shenda, SONG Yiqun, FAN Chunju, et al. Calculation of current protection setting based on inverter generation control strategy[J]. Power System Technology, 2021, 45(9): 3690-3699.
[19]
袁智勇, 徐全, 徐刚, 等. 含大容量分布式电源接入的配电网电流保护优化方案[J]. 电网技术, 2021, 45(5): 1862-1869.
YUAN Zhiyong, XU Quan, XU Gang, et al. Current protection optimization scheme in distribution network with large capacity distributed generators[J]. Power System Technology, 2021, 45(5): 1862-1869.
[20]
贾健飞, 李博通, 孔祥平, 等. 计及逆变型分布式电源输出特性的配电网自适应电流保护研究[J]. 高压电器, 2019, 55(2): 149-155.
JIA Jianfei, LI Botong, KONG Xiangping, et al. Research on adaptive current protection for distribution network considering the output characteristics of inverter-interfaced distributed generator[J]. High Voltage Apparatus, 2019, 55(2): 149-155.
[21]
徐玉韬, 吴恒, 谈竹奎, 等. 适用于微电网的变频式继电保护方案[J]. 电工技术学报, 2019, 34(S1): 360-367.
XU Yutao, WU Heng, TAN Zhukui, et al. Frequency conversion relay protection scheme suitable for microgrid[J]. Transactions of China Electrotechnical Society, 2019, 34(S1): 360-367.
[22]
贾科, 侯来运, 毕天姝, 等. 基于故障区域局部迭代的工程实用化新能源短路电流计算[J]. 电力系统自动化, 2021, 45(13): 151-158.
JIA Ke, HOU Laiyun, BI Tianshu, et al. Practical engineering calculation of short-circuit current for renewable energy based on local iteration of fault area[J]. Automation of Electric Power Systems, 2021, 45(13): 151-158.
[23]
谈竹奎, 文贤馗, 杨涛, 等. 面向新型电力系统的双馈风力发电机并网控制策略研究[J]. 电力系统保护与控制, 2023, 51(3): 181-187.
TAN Zhukui, WEN Xiankui, YANG Tao, et al. A grid-connected control strategy for doubly-fed wind turbines for new power systems[J]. Power System Protection and Control, 2023, 51(3): 181-187.
[24]
分布式电源并网技术要求: GB/T 33593—2017[S]. 北京: 中国标准出版社, 2017.
Technical requirements for grid connection of distributed resources: GB/T 33593—2017[S]. Beijing: Standards Press of China, 2017.
[25]
李红, 粟时平, 唐铭泽, 等. 不对称故障下考虑电压跌落程度的新能源逆变器控制策略[J]. 电力系统保护与控制, 2023, 51(1): 21-32.
LI Hong, SU Shiping, TANG Mingze, et al. Control strategy of renewable energy inverter considering voltage sag degree under asymmetric faults[J]. Power System Protection and Control, 2023, 51(1): 21-32.
[26]
郑涛, 郭勇帆, 吕文轩, 等. 基于电力电子变压器故障穿越策略的低压直流配电网保护[J]. 电力系统自动化, 2023, 47(16): 152-161.
ZHENG Tao, GUO Yongfan, Wenxuan, et al. Protection for low-voltage DC distribution network based on fault ride-through strategy of power electronic transformer[J]. Automation of Electric Power Systems, 2023, 47(16): 152-161.
[27]
王新宝, 葛景, 韩连山, 等. 构网型储能支撑新型电力系统建设的思考与实践[J]. 电力系统保护与控制, 2023, 51(5): 172-179.
WANG Xinbao, GE Jing, HAN Lianshan, et al. Theory and practice of grid-forming BESS supporting the construction of a new type of power system[J]. Power System Protection and Control, 2023, 51(5): 172-179.
[28]
詹长江, 吴恒, 王雄飞, 等. 构网型变流器稳定性研究综述[J]. 中国电机工程学报, 2023, 43(6): 2339-2359.
ZHAN Changjiang, WU Heng, WANG Xiongfei, et al. An overview of stability studies of grid-forming voltage source converters[J]. Proceedings of the CSEE, 2023, 43(6): 2339-2359.
[29]
潘学萍, 王卫康, 黄桦, 等. 考虑机网动态交互作用的光伏场群等值建模[J]. 电力自动化设备, 2023, 43(3): 80-85, 109.
PAN Xueping, WANG Weikang, HUANG Hua, et al. Equivalent modeling of PV station groups considering dynamic interaction between PV and power grid[J]. Electric Power Automation Equipment, 2023, 43(3): 80-85, 109.
[30]
刁涵彬, 李培强, 郭思源, 等. PMU小扰动信号下的综合负荷模型参数辨识方法[J]. 电力系统保护与控制, 2023, 51(13): 37-49.
DIAO Hanbin, LI Peiqiang, GUO Siyuan, et al. Parameter identification method of composite load model using small disturbance signal of PMU[J]. Power System Protection and Control, 2023, 51(13): 37-49.
[31]
陈谦, 张政伟, 钱倍奇, 等. 面向高比例新能源电网短路计算的机电-电磁融合电源模型[J/OL]. 电力自动化设备, 2023: 1-12 (2023-07-10)[2023-08-03]. https://doi.org/10.16081/j.epae.202307009.
CHEN Qian, ZHANG Zhengwei, QIAN Beiqi, et al. Electromechanical-electromagnetic characteristics combined power source model for short-circuit calculation with high proportion of new energy[J/OL]. Electric Power Automation Equipment, 2023: 1-12 (2023-07-10)[2023-08-03]. https://doi.org/10.16081/j.epae.202307009.

Funding

National Natural Science Foundation of China(51837004)
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