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  •   Adel Elgammal

  •   Tagore Ramlal

Abstract

An adaptive approach for optimal tuning of a SMC for an automated voltage regulator system is displayed in this study. The approach is centered on hybrid of the GA and MOPSA. In addition, unique objective functions for the controller's parameter optimization are suggested. The performance of the resulting perfect sliding mode controller is confirmed by comparing it to controllers adjusted using various techniques that have been published in the literature. The simulation outcomes indicate that controllers tuned with the projected MOPSO and GA algorithms outperform controllers tuned with existing methods. In addition, a comparison study is performed to select the best controller for use in AVR systems. The suggested algorithm's major benefit is a considerable boost in convergence speed. With step changes and step load modifications in input wind power, the system model with built-in intelligent controller is generated in MATLAB/SIMULINK. The benefits of the recommended intelligent control algorithm are confirmed by comparing the outcomes of the sliding mode controller and the projected MOPSO self-tuned controller. The findings show that the hybrid Wind/PV system's reactive power adjustment capabilities. When used in conjunction with BES, it is extremely successful in optimising the voltage profile although providing active energy to local load.

Keywords: Automatic voltage regulation, Battery energy storage, DC link voltage, Distribution system, intelligent smoothing control, Reactive power, Sliding Mode controller, Solar photovoltaic (PV), Wind Energy, wind/PV hybrid power system

References

Miloud Rezkallah; Sanjeev Singh; Ambrish Chandra; Bhim Singh; Marco Tremblay; Maarouf Saad; Hua Geng “Comprehensive Controller Implementation for Wind-PV-Diesel Based Standalone Microgrid” IEEE Transactions on Industry Applications, Year: 2019 | Volume: 55, Issue: 5.

Ashu Verma; Ram Krishan; Sukumar Mishra “A Novel PV Inverter Control for Maximization of Wind Power Penetration” IEEE Transactions on Industry Applications, Year: 2018 | Volume: 54, Issue: 6.

Ujjwal Kumar Kalla; Bhim Singh; S. Sreenivasa Murthy; Chinmay Jain; Krishan Kant “Adaptive Sliding Mode Control of Standalone Single-Phase Microgrid Using Hydro, Wind, and Solar PV Array-Based Generation” IEEE Transactions on Smart Grid, Year: 2018 | Volume: 9, Issue: 6.

Farheen Chishti; Shadab Murshid; Bhim Singh “Robust Normalized Mixed-Norm Adaptive Control Scheme for PQ Improvement at PCC of a Remotely Located Wind–Solar PV-BES Microgrid” IEEE Transactions on Industrial Informatics, Year: 2020 | Volume: 16, Issue: 3.

Bhim Singh; Rohini Sharma; Seema Kewat “Robust Control Strategies for SyRG-PV and Wind-Based Islanded Microgrid” IEEE Transactions on Industrial Electronics, Year: 2021 | Volume: 68, Issue: 4.

Mohammad B. Shadmand; Robert S. Balog “Multi-Objective Optimization and Design of Photovoltaic-Wind Hybrid System for Community Smart DC Microgrid” IEEE Transactions on Smart Grid, Year: 2014 | Volume: 5, Issue: 5.

R. C. Bansal, “Automatic Reactive-Power Control of Isolated Wind–Diesel Hybrid Power Systems”, IEEE Transactions on Industrial Electronics, VOL. 53, NO. 4, August 2006.

Jinning Liu, Li Zhang, Man Cao, “Power management and synchronization control of renewable energy microgrid based on STATCOM”, IEEE Conference and Expo on Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014.

D. Menniti, A. Pinnarelli, N. Sorrentino, “An hybrid PV-wind supply system with DStatcom interface for a water-lift station”, International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM), June 2010.

G. Joos, B.T.Ooi, D. McGillis, F.D. Galiana and R. Marceau, “ The Potential of Distributed Generation to Provide Ancillary Services”, Power Engineering Society Summer Meeting, IEEE, July 2000.

I. Sefa; N. Altin; S. Ozdemir; O. Kaplan, “Fuzzy PI controlled inverter for grid interactive renewable energy systems r,” IET Renewable Power Generation, Volume: 9, Issue: 7, Pages: 729 - 738, 2015.

Faramarz Karbakhsh, G. B. Gharehpetian, Jafar Milimonfared, Armin Teymoori,“ Three Phase Photovoltaic Grid-Tied Inverter Based on Feed-Forward Decoupling Control Using Fuzzy-PI Controller ,”7th Power Electronics, Drive Systems &Technologies Conference , 16-18 Feb. 2016.

Daugherity W C, Rathakrishnan B & Yen J, “Performance evaluation of a self-tuning fuzzy controller,” Proc. IEEE International Conference on Fuzzy Systems, 389-397, 8-12 March 1992.

Hasanien HM. Design optimization of PID controller in automatic voltage regulator system using taguchi combined genetic algorithm method. IEEE Syst J 2013;7:825–31.

Kim DH. Hybrid GA–BF based intelligent PID controller tuning for AVR system. Appl Soft Comput 2011;11:11–22.

Ortiz-Quisbert ME, Duarte-Mermoud MA, Milla F, Castro-Linares R, Lefranc G. Optimal fractional order adaptive controllers for AVR applications. Electr Eng 2018;100:267–83.

Pan I, Das S. Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization. Int J Electr Power Energy Syst 2013;51:106–18.

Pan I, Das S. Chaotic multi-objective optimization based design of fractional order PI kD l controller in AVR system. Int J Electr Power Energy Syst 2012;43:393–407.

Gaing ZL. A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans Energy Convers 2004;19:384–91.

Sahib MA, Ahmed BS. A new multiobjective performance criterion used in PID tuning optimization algorithms. J Adv Res 2016;7:125–34.

Zamani M, Karimi-Ghartemani M, Sadati N, Parniani M. Design of a fractional order PID controller for an AVR using particle swarm optimization. Control Eng Pract 2009;17:1380–7.

Ekinci S, Hekimoglu B. Improved kidney-inspired algorithm approach for tuning of PID controller in AVR system. IEEE Access 2019;7:39935–47.

Mosaad AM, Attia MA, Abdelaziz AY. Whale optimization algorithm to tune PID and PIDA controllers on AVR system. Ain Shams Eng J 2019;10:755–67.

Bingul Z, Karahan O. A novel performance criterion approach to optimum design of PID controller using cuckoo search algorithm for AVR system. J Franklin Inst 2018;355:5534–59.

Sikander A, Thakur P, Bansal RC, Rajasekar S. A novel technique to design cuckoo search based FOPID controller for AVR in power systems. Comput Electr Eng 2018;70:261–74.

Blondin MJ, Sicard P, Pardalos PM. Controller Tuning Approach with robustness, stability and dynamic criteria for the original AVR System. Math Comput Simul 2019;163:168–82.

Blondin MJ, Sanchis J, Sicard P, Herrero JM. New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Appl Soft Comput 2018;62:216–29.

Chatterjee S, Mukherjee V. PID controller for automatic voltage regulator using teaching-learning based optimization technique. Int J Electr Power Energy Syst 2016;77:418–29.

Panda S, Sahu BK, Mohanty PK. Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization. J Franklin Inst 2012;349:2609–25.

Dos Santos Coelho L. Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach. Chaos, Solitons Fractals 2009;39:1504–14.

Çelik E, Durgut R. Performance enhancement of automatic voltage regulator by modified cost function and symbiotic organisms search algorithm. Eng Sci Technol Int J 2018;21:1104–11.

Gozde H, Taplamacioglu MC. Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system. J Franklin Inst 2011;348:1927–46.

Zhang D-L, Tang Y-G, Guan X-P. Optimum design of fractional order PID controller for an AVR system using an improved artificial bee colony algorithm. Acta Autom Sin 2014;40:973–9.

Mosaad AM, Attia MA, Abdelaziz AY. Comparative performance analysis of AVR controllers using modern optimization techniques. Electr Power Compon Syst 2018;46:2117–30.

Chatterjee A, Mukherjee V, Ghoshal SP. Velocity relaxed and craziness-based swarm optimized intelligent PID and PSS controlled AVR system. Int J Electr Power Energy Syst 2009;31:323–33.

Tang Y, Cui M, Hua C, Li L, Yang Y. Optimum design of fractional order PI kD l controller for AVR system using chaotic ant swarm. Expert Syst Appl 2012;39:6887–96.

Zhu H, Li L, Zhao Y, Guo Y, Yang Y. CAS algorithm-based optimum design of PID controller in AVR system. Chaos, Solitons Fractals 2009;42:792–800.

Zeng GQ, Chen J, Dai YX, Li LM, Zheng CW, Chen MR. Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization. Neurocomputing 2015;160:173–84.

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How to Cite
[1]
Elgammal, A. and Ramlal, T. 2021. Adaptive Voltage Regulation Control Strategy in a Stand-Alone Islanded DC Microgrid based on distributed Wind / Photovoltaic / Diesel / Energy Storage Hybrid Energy Conversion System. European Journal of Electrical Engineering and Computer Science. 5, 4 (Jul. 2021), 26-33. DOI:https://doi.org/10.24018/ejece.2021.5.4.343.