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Design and analysis of the performance of multi-source interconnected electrical power system using resilience random variance reduction technique

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The increasing demand for electricity and global attention to the environment has led energy planners and developers to explore developing control techniques for energy stability. The primary objective function of this research in an interconnected electrical power system to increase the stability of the system with the proposed RRVR technique is evaluated in terms of the different constraints like THD (%), steady-state error (%), settling time (s), overshoot (%), efficiency (%) and to maintain the frequency at a predetermined value, and controlling the change of the power flow of control between the areas renewable energy generation (solar, wind, and fuel cell with battery management system) based intelligent grid system. To provide high-quality, reliable and stable electrical power, the designed controller should perform satisfactorily, that is, suppress the deviation of the load frequency. The performance of linear controllers on non-linear power systems has not yet been found to be effective in overcoming this problem. In this work, a fractional high-order differential feedback controller (FHODFC) is proposed for the LFC problems in a multi-area power system. The gains of FHODFC are best adjusted by resilience random variance reduction technique (RRVR) designed to minimize the overall weighted absolute error performance exponential time. Therefore, the controller circuit automatically adjusts the duty cycle value to obtain a desired constant output voltage value, despite all the grid system’s source voltage and load output changes. The proposed interconnected multi-generation energy generation topology is established in MATLAB 2017b software.
Rocznik
Strony
art. no. e137941
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
  • Department of Electrical and Electronics Engineering, V.S.B Engineering College, Karur and Research Scholar (Electrical), Anna University, Chennai, Tamilnadu, India
autor
  • Department of Electrical and Electronics Engineering, University College of Engineering, Anna University-BIT Campus, Tiruchirapalli, Tamilnadu, India
Bibliografia
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  • [11] H. Zhang, B. Zhang, A. Bose, and H. Sun, “A Distributed Multi-Control-Center Dynamic Power Flow Algorithm Based on Asynchronous Iteration Scheme,” IEEE Trans. Power Syst., vol. 33, no. 2, pp. 1716‒1724, March 2018, doi: 10.1109/TPWRS.2017.2721405.
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  • [14] A. Nassaj and S.M. Shahrtash, “An Accelerated Preventive Agent-Based Scheme for Postdisturbance Voltage Control and Loss Reduction,” IEEE Trans. Power Syst., vol. 33, no. 4, pp. 4508‒4518, July 2018, doi: 10.1109/TPWRS.2017.2778098.
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  • [17] C. Zhong, J. Zhang, and Y. Zhou, “Adaptive Virtual Capacitor Control for MTDC System With Deloaded Wind Power Plants,” IEEE Access, vol. 8, pp. 190582‒190595, 2020, doi: 10.1109/ACCESS.2020.3032284.
  • [18] M. Kahl, C. Freye, and T. Leibfried, “A Cooperative Multi-Area Optimization With Renewable Generation and Storage Devices,” IEEE Trans. Power Syst., vol. 30, no. 5, pp. 2386‒2395, Sept. 2015, doi: 10.1109/TPWRS.2014.2363762.
  • [19] J. Zhao et al., “A Multi-Source Coordinated Optimal Operation Model Considering the Risk of Nuclear Power Peak Shaving and Wind Power Consumption,” IEEE Access, vol. 8, pp. 189702‒189719, 2020, doi: 10.1109/ACCESS.2020.3027705.
  • [20] W. Wang, L. Jiang, Y. Cao, and Y. Li, “A Parameter Alternating VSG Controller of VSC-MTDC Systems for Low-Frequency Oscillation Damping,” IEEE Trans. Power Syst., vol. 35, no. 6, pp. 4609‒4621, Nov. 2020, doi: 10.1109/TPWRS.2020.2997859.
  • [21] T. Yang, S. Bozhko, J. Le-Peuvedic, G. Asher, and C.I. Hill, “Dynamic Phasor Modeling of Multi-Generator Variable Frequency Electrical Power Systems,” IEEE Trans. Power Syst., vol. 31, no. 1, pp. 563‒571, Jan. 2016, doi: 10.1109/TPWRS.2015.2399371.
  • [22] P.M. Dash, S.K. Mohapatra, and A.K. Baliarsingh, “Tuning of LFC in Multi-source Electrical Power Systems Implementing Novel Nature-Inspired MFO Algorithm Based Controller Parameter,” 2020 International Conference on Computational Intelligence for Smart Power System and Sustainable Energy (CISPSSE), Keonjhar, Odisha, India, 2020, pp. 1‒5, doi: 10.1109/CISPSSE49931.2020.9212199.
  • [23] F. Qi, M. Shahidehpour, F. Wen, Z. Li, Y. He, and M. Yan, “Decentralized Privacy-Preserving Operation of Multi-Area Integrated Electricity and Natural Gas Systems With Renewable Energy Resources,” IEEE Trans. Sustainable Energy, vol. 11, no. 3, pp. 1785‒1796, July 2020, doi: 10.1109/TSTE.2019.2940624.
  • [24] X.S. Zhang, T. Yu, Z.N. Pan, B. Yang, and T. Bao, “Lifelong Learning for Complementary Generation Control of Interconnected Power Grids With High-Penetration Renewables and EVs,” IEEE Trans. Power Syst., vol. 33, no. 4, pp. 4097‒4110, July 2018, doi: 10.1109/TPWRS.2017.2767318.
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  • [29] H. Rezk, M.A. Mohamed, A.A. Zaki Diab, and N. Kanagaraj, “Load Frequency control of Multi-interconnected Renewable Energy Plants using Multi-Verse Optimizer,” Comput. Syst. Sci. Eng., vol. 37, no. 2, pp. 219‒231, 2021, doi: 10.32604/csse.2021.015543.
  • [30] H. Sun, C. Peng, D. Yue, Y.L. Wang, and T. Zhang, “Resilient Load Frequency Control of Cyber-Physical Power Systems Under QoS-Dependent Event-Triggered Communication,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 51, no. 4, pp. 2113‒2122, doi: 10.1109/TSMC.2020.2979992.
  • [31] E. Canelas, T. Pinto-Varela, and B. Sawik, “Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study,” Energies, vol. 13, no. 9, p. 2249, 2020, doi: 10.3390/en13092249.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cf3e2318-9f82-41e4-835f-6095c67e4dfb
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