Supplementary Frequency Control in a High-penetration Real Power System by Renewables Using SMES Application

被引:0
作者
Magdy, Gaber [1 ,2 ]
Nour, Morsy [1 ,3 ]
Shabib, G. [1 ,4 ]
Elbaset, Adel A. [5 ]
Mitani, Yasunori [2 ]
机构
[1] Aswan Univ, Fac Energy Engn, Elect Engn Dept, Aswan 81528, Egypt
[2] Kyushu Inst Technol, Dept Elect & Elect Engn, Tobata Ku, Kitakyushu, Fukuoka 8048550, Japan
[3] Comillas Pontifical Univ, Inst Res Technol, Madrid 28015, Spain
[4] Higher Inst Engn & Technol King Marriott, Alexandria 23713, Egypt
[5] Menia Univ, Fac Engn, Dept Elect Engn, Al Minya 61517, Egypt
基金
美国国家卫生研究院;
关键词
Renewable energy sources; Superconducting magnetic energy storage; Egyptian power system; Frequency control; Particle swarm optimization; SLIDING MODE CONTROL; OPTIMIZATION ALGORITHM; VIRTUAL INERTIA;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In modern power systems, the penetration level of Renewable Energy Sources (RESs) is strikingly increasing. Where, many synchronous generators are being replaced by the RESs-based the power electronic devices, this will reduce the overall system inertia. Moreover, the intermittent nature of the RESs causes several control problems such as frequency/voltage instability problem. Hence, these disturbances threaten preservation the power system stability and can lead to system collapse. In addition, the secondary frequency control action (i.e., Load Frequency Control (LEG)) will not be sufficient to maintain the system frequency close to its scheduled value. Therefore, this paper proposes an application of Superconducting Magnetic Energy Storage (SMES) system based on an optimal PID controller, which is optimally designed by the Particle Swarm Optimization (PSO) to enhance the frequency stability of modern power systems due to high RESs penetration. From the perspective of the LFC, the proposed controlled SMES can be used as a feedback controller with the aim of supporting the frequency control loops for frequency stability enhancement of the power systems. Moreover, the effectiveness of the proposed control strategy is tested and verified through a real hybrid power system in Egypt (i.e., Egyptian Power System (EPS)) that includes thermal, gas, hydraulic power plants, wind, and solar energy. The obtained simulation results by Matlab/Simulink software reveal that the proposed control strategy achieved superior dynamic responses satisfying the LFC requirements in all test scenarios. Consequently, the frequency stability is improved regarding peak undershoot, peak overshoot, and settling time.
引用
收藏
页码:526 / 538
页数:13
相关论文
共 32 条
[1]   Overview of energy storage in renewable energy systems [J].
Amrouche, S. Ould ;
Rekioua, D. ;
Rekioua, T. ;
Bacha, S. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2016, 41 (45) :20914-20927
[2]  
Bakeer A, 2017, PROC INT MID EAST P, P134, DOI 10.1109/MEPCON.2017.8301175
[3]  
Bevrani H, 2014, POWER ELECTRON POWER, P1, DOI 10.1007/978-3-319-07278-4
[4]  
Chen SY, 2018, SPR SER TRANSL STROK, P1, DOI 10.1007/978-3-319-90194-7_1
[5]   Efficient frequency controllers for autonomous two-area hybrid microgrid system using social-spider optimiser [J].
El-Fergany, Attia A. ;
El-Hameed, Mohammed A. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2017, 11 (03) :637-648
[6]   An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control [J].
Gheisarnejad, Meysam .
APPLIED SOFT COMPUTING, 2018, 65 :121-138
[7]   Whale optimisation algorithm for automatic generation control of interconnected modern power systems including renewable energy sources [J].
Hasanien, Hany M. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2018, 12 (03) :607-614
[8]   Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms [J].
Hasanien, Hany M. ;
El-Fergany, Attia A. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2017, 11 (07) :1692-1700
[9]   A new hybrid particle swarm and simulated annealing stochastic optimization method [J].
Javidrad, F. ;
Nazari, M. .
APPLIED SOFT COMPUTING, 2017, 60 :634-654
[10]  
Kennedy J., 1995, 1995 IEEE International Conference on Neural Networks Proceedings (Cat. No.95CH35828), P1942, DOI 10.1109/ICNN.1995.488968