Construction of Power Supply Stability Control Model for Wind Connected Power Grid
DOI:
https://doi.org/10.13052/dgaej2156-3306.3767Keywords:
Wind power connected to power grid, power supply, stability, control model, mechanical torque, pv curve, nonlinear objective functionAbstract
There are many problems in the power supply stability control of wind power generation system, such as large fluctuations, poor control effect and so on. Therefore, a new stability control model of wind power grid connected is designed. Determine the DC grid connection mode when the wind farm is connected, convert the DC power into AC power through the converter station, and transmit it to the final AC system to realize the grid connection of wind power and power grid; According to the determined wind power access mode, calculate the mechanical operation power, mechanical torque and wind energy utilization coefficient collected by the wind turbine, complete the best collection of wind energy, and determine the shafting according to the mass block model of the wind turbine and generator, so as to realize the research on the mathematical model of wind power generation. By analyzing the power flow direction of the stator and rotor of the wind turbine generator set, the unstable state of the power supply voltage of the wind turbine generator set after grid connection is determined. The PV curve method is used to calculate the steady-state voltage stability of grid connected wind turbines, and a power supply stability control model based on the voltage stability of grid connected wind turbines is established. The nonlinear objective function method is used to optimize the critical point of power supply stability, calculate the maximum load and maximum power of the system, establish the static power supply and transient power supply stability model after wind power grid connection, and realize the power supply stability control research of grid connected wind power through the analysis of power supply characteristics. The experimental results show that the model is closer to the stability of the actual power supply in the test of improving the stability of the power supply, ensuring the quality of power supply, while the test results of the other two methods have large fluctuations. In the analysis of the change of power supply after grid connection, the experimental results obtained by the model are very close to the actual data values. Therefore, this method can effectively improve the performance of power system.
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References
Mahdy A, Hasanien H M, Helmy W, et al. Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy[J]. Energy, 2022, 24(5):147–151.
Yao X, Yi B, Yu Y, et al. Economic analysis of grid integration of variable solar and wind power with conventional power system[J]. Applied Energy, 2020, 26(4):1147–1152.
Santhoshi B K, Mohanasundaram K, Kumar L A. ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter[J]. Electrical Engineering, 2021, 17(8):1–17.
Ravada B R, Tummuru N R, Ande B. PV-Wind and Hybrid Energy Storage Integrated Multi-Source Converter Configuration based Grid-interactive Microgrid[J]. IEEE Transactions on Industrial Electronics, 2020, 32(19):15–21.
Zhangwenxia, liyanzhe, sunhuangjian, et al Study on systematic stability of DC microgrid with constant power load [J] Computer simulation, 2020, 37(3):6.
Xu Litong, Cheng Ming, Wei Xinchi, Ning Xinfu. Power Signal Feedback Control of Maximum Power Point Tracking Control for Brushless Doubly-Fed Wind Power Generation System Considering Loss[J]. Transactions of China Electrotechnical Society, 2020, 35(3):472–480.
Pan Ersheng, Wang Zhidong, Wang Dong, Liang Liang, Hou Yunhe. Stability Analysis of Phase-locked Loop Synchronized DFIGs in Weak Grids[J]. High Voltage Engineering, 2020, 46(1):170–177.
Yamashita K, Tsukamoto G, Nishikata S. Steady-state characteristics of a line-commutated converter-based high-voltage direct current transmission system for series-connected wind power plants[J]. IEEE Transactions on Industry Applications, 2020, 56(4): 3932–3939.
Kim G, J Hur. Probabilistic modeling of wind energy potential for power grid expansion planning[J]. Energy, 2021, 23(15):63–70.
G.Y.E.O.N.G.M.I.N. Kim, Hur J. Probabilistic modeling of wind energy potential for power grid expansion planning[J]. Energy, 2021, 23(02):120831.
Ranjan V, Arora A, Bhadu M. Stability Enhancement of Grid Connected AC Microgrid in Modern Power Systems[J]. 2022, 21(17):236–240.
Mahdy A, Hasanien H M, Helmy W, et al. Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy[J]. Energy, 2022, 245.
Pan L, Shao C. Wind energy conversion systems analysis of PMSG on offshore wind turbine using improved SMC and Extended State Observer[J]. Renewable Energy, 2020, 16(22):1463–1472.
Zhou W, Wang Y, Torres-Olguin R E, et al. Effect of Reactive Power Characteristic of Offshore Wind Power Plant on Low-Frequency Stability[J]. IEEE Transactions on Energy Conversion, 2020, 35(2):837–853.
Yan C, Yao W, Wen J, et al. Modelling and Comparison Analysis of Grid-Connected DFIG-based Wind Farm in Weak Grid[J]. IET Renewable Power Generation, 2020, 36(02):35–41.
Nagaraj R, Murthy D T, Rajput M M. Modeling Renewables Based Hybrid Power System with Desalination Plant Load Using Neural Networks[J]. Distrib. Gener. Altern. Energy J, 2019, 34:32–46.
Ghouari A, Hamouda C, Chaghi A, et al. An Experimental study on the smart home concept with PV and energy management and control strategy using an open source platform[J]. Distributed Generation & Alternative Energy Journal, 2019, 34(1):61–80.
Mahajan S, Vadhera S. Optimal location and sizing of distributed generation unit using human opinion dynamics optimization technique[J]. Distributed Generation & Alternative Energy Journal, 2018, 33(2):38–57.
