A Control Strategy with Improved Frequency Response Characteristics of Variable Speed DFIM Pumped Storage
Chuang Kaihsun1, Sun Jianjun1, Ding Lijie2, Luan Yihang1, Zhang Yuanzhi1
1. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China; 2. State Grid Sichuan Electric Power Research Institute Chengdu 610041 China
Abstract:With the gradual integration of renewable energy into the power grid, the demand for flexible regulation methods is increasing. To solve this problem, the variable speed pumped storage power station adopts a doubly fed induction machine (DFIM) and a variable speed pump turbine as its main components to achieve adjustable speed and open water diversion gates, thus realizing flexible power regulation under any conditions. However, research on the frequency response characteristics of DFIM in pumped storage is still in the preliminary stage. The commonly used frequency control methods focus on converting grid frequency deviation into active power correction, leading to suboptimal frequency response characteristics. Therefore, this paper proposes a method of frequency response strategy and dynamic adjustment of control parameters, aiming at enhancing the frequency response characteristics of DFIM, and making it more effective in integrating renewable energy into the power grid. Firstly, a topology of variable speed pumped storage unit is introduced. The speed priority control strategy and its advantages are further discussed to improve overall efficiency. Then, a frequency response module is proposed to convert frequency deviation and its rate of change into speed correction added to the speed controller. Meanwhile, a dynamic adjustment method of controller parameters, determined by the frequency characteristic during deviation, is proposed, resulting in a more reasonable release or obtainment of rotor kinetic energy. Subsequently, DFIM and synchronous machines with the same capacity are compared. The results show that DFIM can release or absorb more kinetic energy than synchronous machines, making it a crucial means to provide short-term power and inertia support to the grid. This paper conducts two simulations using Matlab/Simulink. The first one is about rotor speed and reactive power regulation, also known as the speed priority control of the DFIM. The second one is to verify the effectiveness of the proposed frequency response strategy. The first simulation results show that the machine can accurately adjust its rotor speed, torque, and reactive power when the reference values change. Due to the reference value being changed in the form of a step function, there is an overshoot in a short period, which must be avoided when used in an actual machine. Then, the proposed frequency response strategy is simulated. This strategy is compared to a commonly used frequency-active power control strategy and a constant-speed control strategy. At the beginning of the simulation, a load was added. The results show that DFIM can lower its speed to release kinetic energy, provide short-term active power, and provide inertia support. When the load is disconnected from the power grid, the power grid frequency increases, and DFIM accelerates, converting the extra active power into rotor kinetic energy. The proposed parameter dynamic adjustment method adjusts the parameters based on the rate of frequency change, shortening the frequency and speed recovery time. Based on theoretical analysis and simulation results, the following conclusions can be drawn: (1) When there is no frequency disturbance, the speed priority control can effectively control the motor speed, torque, and reactive power of DFIM. (2) The proposed frequency response module converts frequency deviation into speed correction, which can directly release or absorb the rotor kinetic energy. Compared with the frequency-active power control strategy, the strategy reduces frequency variation and steady-state error, and suppresses fluctuations during frequency variation. The frequency response characteristics in both generating and pumping modes are improved. (3) The parameter adjustment method allows the controller parameters to be dynamically adjusted, which can release or absorb the rotor kinetic energy more reasonably during the process. By setting the controller parameters appropriately, the inertia support capability of DFIM can be improved. This method requires little computing capability and can be handily promoted in practical engineering applications.
[1] 李亚楼, 张星, 胡善华, 等. 含高比例电力电子装备电力系统安全稳定分析建模仿真技术[J]. 电力系统自动化, 2022, 46(10): 33-42. Li Yalou, Zhang Xing, Hu Shanhua, et al.Modeling and simulation technology for stability analysis of power system with high proportion of power electronics[J]. Automation of Electric Power Systems, 2022, 46(10): 33-42. [2] 姜树德, 梁国才, 王纯. 采用双馈电机的抽水蓄能机组技术概述[J]. 水电与抽水蓄能, 2021, 7(4): 20-25. Jiang Shude, Liang Guocai, Wang Chun.Technical overview of pumped storage unit with doubly-fed motor[J]. Hydropower and Pumped Storage, 2021, 7(4): 20-25. [3] 龚国仙, 李定林, 吕静亮, 等. 双馈式可变速抽水蓄能机组运行控制[J]. 大电机技术, 2022(3): 1-7, 20. Gong Guoxian, Li Dinglin, Lü Jingliang, et al.An overall control of doubly fed variable speed pumped storage unit[J]. Large Electric Machine and Hydraulic Turbine, 2022(3): 1-7, 20. [4] 赵冬梅, 王浩翔, 陶然. 计及风电-负荷不确定性的风-火-核-碳捕集多源协调优化调度[J]. 电工技术学报, 2022, 37(3): 707-718. Zhao Dongmei, Wang Haoxiang, Tao Ran.A multi-source coordinated optimal scheduling model considering wind-load uncertainty[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 707-718. [5] 何晨可, 朱继忠, 刘云, 等. 计及碳减排的电动汽车充换储一体站与主动配电网协调规划[J]. 电工技术学报, 2022, 37(1): 92-111. He Chenke, Zhu Jizhong, Liu Yun, et al.Coordinated planning of electric vehicle charging-swapping-storage integrated station and active distribution network considering carbon reduction[J]. Transactions of China Electrotechnical Society, 2022, 37(1): 92-111. [6] 姜云鹏, 任洲洋, 李秋燕, 等. 考虑多灵活性资源协调调度的配电网新能源消纳策略[J]. 电工技术学报, 2022, 37(7): 1820-1835. Jiang Yunpeng, Ren Zhouyang, Li Qiuyan, et al.An accommodation strategy for renewable energy in distribution network considering coordinated dispatching of multi-flexible resources[J]. Transactions of China Electrotechnical Society, 2022, 37(7): 1820-1835. [7] 孙凯, 舒琼, 薛峰. 定速抽水蓄能机组工况转换及控制流程综述[J]. 水电与抽水蓄能, 2020, 6(6): 49-57. Sun Kai, Shu Qiong, Xue Feng.Summary of working condition conversion and control flow of fixed-speed pumped storage unit[J]. Hydropower and Pumped Storage, 2020, 6(6): 49-57. [8] 李辉, 刘海涛, 宋二兵, 等. 双馈抽水蓄能机组参与电网调频的改进虚拟惯性控制策略[J]. 电力系统自动化, 2017, 41(10): 58-65. Li Hui, Liu Haitao, Song Erbing, et al.Improved virtual inertia control strategy of doubly fed pumped storage unit for power network frequency modulation[J]. Automation of Electric Power Systems, 2017, 41(10): 58-65. [9] 龚国仙, 吕静亮, 姜新建, 等. 参与一次调频的双馈式可变速抽水蓄能机组运行控制[J]. 储能科学与技术, 2020, 9(6): 1878-1884. Gong Guoxian, Lü Jingliang, Jiang Xinjian, et al.Operation control of doubly fed adjustable speed pumped storage unit for primary frequency modulation[J]. Energy Storage Science and Technology, 2020, 9(6): 1878-1884. [10] 刘开培, 朱蜀, 冯欣, 等. 双馈式变速抽水蓄能电厂的机电暂态建模及模型预测控制[J]. 高电压技术, 2020, 46(7): 2407-2418. Liu Kaipei, Zhu Shu, Feng Xin, et al.Electromechanical transient modeling and model predictive control of doubly-fed variable-speed pumped storage power plant[J]. High Voltage Engineering, 2020, 46(7): 2407-2418. [11] 朱珠, 潘文霞, 刘铜锤, 等. 变速抽蓄机组频率响应机理模型与性能研究[J]. 电网技术, 2023, 47(2): 463-474. Zhu Zhu, Pan Wenxia, Liu Tongchui, et al.Study on frequency response mechanism model and performance of variable speed pumping unit[J]. Power System Technology, 2023, 47(2): 463-474. [12] 蔡国伟, 钟超, 吴刚, 等. 考虑风电机组超速减载与惯量控制的电力系统机组组合策略[J]. 电力系统自动化, 2021, 45(16): 134-142. Cai Guowei, Zhong Chao, Wu Gang, et al.Unit commitment strategy of power system considering overspeed load reduction and inertia control of wind turbine[J]. Automation of Electric Power Systems, 2021, 45(16): 134-142. [13] 颜湘武, 崔森, 宋子君, 等. 基于超级电容储能控制的双馈风电机组惯量与一次调频策略[J]. 电力系统自动化, 2020, 44(14): 111-120. Yan Xiangwu, Cui Sen, Song Zijun, et al.Inertia and primary frequency regulation strategy of doubly-fed wind turbine based on super-capacitor energy storage control[J]. Automation of Electric Power Systems, 2020, 44(14): 111-120. [14] Lao Huanjing, Zhang Li, Zhao Tong, et al.Innovated inertia control of DFIG with dynamic rotor speed recovery[J]. CSEE Journal of Power and Energy Systems, 2020, 8(5): 1417-1427. [15] Dreidy M, Mokhlis H, Mekhilef S.Inertia response and frequency control techniques for renewable energy sources: a review[J]. Renewable and Sustainable Energy Reviews, 2017, 69: 144-155. [16] 蔡福霖, 胡泽春, 曹敏健, 等. 提升新能源消纳能力的集中式与分布式电池储能协同规划[J]. 电力系统自动化, 2022, 46(20): 23-32. Cai Fulin, Hu Zechun, Cao Minjian, et al.Collaborative planning of centralized and distributed battery energy storage to improve new energy consumption capacity[J]. Automation of Electric Power Systems, 2022, 46(20): 23-32. [17] 单煜, 汪震, 周昌平, 等. 基于分段频率变化率的风电机组一次调频控制策略[J]. 电力系统自动化, 2022, 46(11): 19-26. Shan Yu, Wang Zhen, Zhou Changping, et al.Control strategy of primary frequency regulation for wind turbine based on segmented rate of change of frequency[J]. Automation of Electric Power Systems, 2022, 46(11): 19-26. [18] 李柏慷, 张峰, 丁磊. 双馈风机参与调频的速度控制器模糊协同控制及参数校正策略[J]. 电网技术, 2022, 46(2): 596-605. Li Baikang, Zhang Feng, Ding Lei.Fuzzy cooperative control and parameter correction strategy of speed controller in frequency modulation stage of doubly-fed induction generator[J]. Power System Technology, 2022, 46(2): 596-605. [19] Verma P, Seethalekshmi K, Dwivedi B.A cooperative approach of frequency regulation through virtual inertia control and enhancement of low voltage ride-through in DFIG-based wind farm[J]. Journal of Modern Power Systems and Clean Energy, 2022, 10(6): 1519-1530. [20] 王彤, 邢其鹏, 李鸿恩, 等. 计及虚拟惯量控制的DFIG等效惯量在线评估与响应特性分析[J]. 电力系统保护与控制, 2022, 50(11): 52-60. Wang Tong, Xing Qipeng, Li Hongen, et al.Online evaluation and response characteristics analysis of equivalent inertia of a doubly-fed induction generator incorporating virtual inertia control[J]. Power System Protection and Control, 2022, 50(11): 52-60. [21] Valavi M, Nysveen A.Variable-speed operation of hydropower plants: a look at the past, present, and future[J]. IEEE Industry Applications Magazine, 2018, 24(5): 18-27. [22] Zhang Xiaoxi, Cheng Yongguang, Yang Zhiyan, et al.Water column separation in pump-turbine after load rejection: 1D-3D coupled simulation of a model pumped-storage system[J]. Renewable Energy, 2021, 163: 685-697.