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Neural Computing and Applications

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20.04.2019 | Original Article

A novel adaptive model predictive controller for load frequency control of power systems integrated with DFIG wind turbines

verfasst von: Mohamed A. Mohamed, Ahmed A. Zaki Diab, Hegazy Rezk, Tao Jin

Erschienen in: Neural Computing and Applications | Ausgabe 11/2020

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Abstract

With the rapid growth of renewable energy resources, wind energy system is getting more interest everywhere throughout the world. However, its extensive use in power systems prompts many power system dynamics and stability problems. Load variation and anomalous operating conditions prompt inconsistencies in frequency and planned power trades. These inconsistencies should be remedied by load frequency control. This paper introduces a novel frequency control system utilizing a mix of adaptive model predictive controller (AMPC) and recursive polynomial model estimator (RPME) integrated with double fed induction generator wind turbines. Inside each control duration, the RPME is identifying a discrete-time online autoregressive exogenous model. The latter is used through the AMPC to update the interior plant model in order to achieve a successful nonlinear control. The performance of the proposed system has been verified and contrasted with the conventional MPC system through a computer simulation-based MATLAB/SIMULINK. The simulation results demonstrated the superiority of the proposed system as for the conventional MPC system.

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Mohamed MA, Diab AAZ, Rezk H (2019) Partial shading mitigation of PV systems via different meta-heuristic techniques. Renew Energy 130:1159–1175CrossRef

Eltamaly AM, Mohamed MA, Al-Saud MS, Alolah AI (2017) Load management as a smart grid concept for sizing and designing of hybrid renewable energy systems. Eng Optim 49(10):1813–1828CrossRef

Eltamaly AM, Addoweesh KE, Bawah U, Mohamed MA (2013) New software for hybrid renewable energy assessment for ten locations in Saudi Arabia. J Renew Sustain Energy 5(3):033126CrossRef

Eltamaly AM, Mohamed MA, Alolah AI (2015) A smart technique for optimization and simulation of hybrid photovoltaic/wind/diesel/battery energy systems. In IEEE international conference on smart energy grid engineering (SEGE), pp 1–6

Ma J, Qiu Y, Li Y, Zhang W, Song Z, Thorp JS (2017) Research on the impact of DFIG virtual inertia control on power system small-signal stability considering the phase-locked loop. IEEE Trans Power Syst 32(3):2094–2105CrossRef

Ma M, Zhang C, Liu X, Chen H (2017) Distributed model predictive load frequency control of the multi-area power system after deregulation. IEEE Trans Ind Electron 64(6):5129–5139CrossRef

Khooban MH, Niknam T, Blaabjerg F, Dragičević T (2017) A new load frequency control strategy for micro-grids with considering electrical vehicles. Electr Power Syst Res 143:585–598CrossRef

Mallada E, Zhao C, Low S (2017) Optimal load-side control for frequency regulation in smart grids. IEEE Trans Autom Control 62(12):6294–6309MathSciNetCrossRef

Holdsworth L, Ekanayake JB, Jenkins N (2004) Power system frequency response from fixed speed and doubly fed induction generator-based wind turbines. Wind Energy Int J Prog Appl Wind Power Convers Technol 7(1):21–35

10.

Mullane A, O’Malley M (2005) The inertial response of induction-machine-based wind turbines. IEEE Trans Power Syst 20(3):1496–1503CrossRef

11.

Masiala M, Ghribi M, Kaddouri A (2004) An adaptive fuzzy controller gain scheduling for power system load-frequency control. In: IEEE international conference on industrial technology. IEEE ICIT’04, vol 3. IEEE, pp 1515–1520

12.

Lei W, Li C, Chen MZ (2018) Robust adaptive tracking control for quadrotors by combining PI and self-tuning regulator. IEEE Trans Control Syst Technol. https://doi.org/10.1109/TCST.2018.2872462 CrossRef

13.

Li J, Liu X, Su X (2018) Sliding mode observer-based load frequency control of multi-area power systems under delayed inputs attack. In: 2018 IEEE Chinese control and decision conference (CCDC), pp 3716–3720

14.

Hote YV, Jain S (2018) PID controller design for load frequency control: past, Present and future challenges. IFAC-PapersOnLine 51(4):604–609CrossRef

15.

Boroujeni SMS, Boroujeni BK, Delafkar H, Boroujeni AS (2011) A new IP type controller for load frequency control problem. J Basic Appl Sci Res 1(9):1078–1083

16.

Zhou F, Peng H, Zeng X, Tian X (2018) RBF-ARX model-based two-stage scheduling RPC for dynamic systems with bounded disturbance. Neural Comput Appl. https://doi.org/10.1007/s00521-018-3347-y CrossRef

17.

Ojaghi P, Rahmani M (2017) LMI-based robust predictive load frequency control for power systems with communication delays. IEEE Trans Power Syst 32(5):4091–4100CrossRef

18.

Lee HJ, Park JB, Joo YH (2006) Robust load-frequency control for uncertain nonlinear power systems: a fuzzy logic approach. Inf Sci 176(23):3520–3537MathSciNetCrossRef

19.

Çam E, Kocaarslan I (2005) Load frequency control in two area power systems using fuzzy logic controller. Energy Convers Manag 46(2):233–243CrossRef

20.

Sabahi K, Nekoui MA, Teshnehlab M, Aliyari M, Mansouri M (2007) Load frequency control in interconnected power system using modified dynamic neural networks. In: IEEE mediterranean conference on control and automation. MED’07, pp 1–5

21.

Al-Hamouz ZM, Al-Duwaish HN (2000) A new load frequency variable structure controller using genetic algorithms. Electr Power Syst Res 55(1):1–6CrossRef

22.

Mohamed TH, Diab AAZ, Hussein MM (2015) Application of linear quadratic gaussian and coefficient diagram techniques to distributed load frequency control of power systems. Appl Sci 5(4):1603–1615CrossRef

23.

Tan W (2010) Unified tuning of PID load frequency controller for power systems via IMC. IEEE Trans Power Syst 25(1):341–350CrossRef

24.

Kalamian N, Verij Kazemi M, Gholomian SA (2016) Direct power control of DFIG by using nonlinear model predictive controller. Asian J Control 18(3):985–999MathSciNetCrossRef

25.

Qudaih YS, Bernard M, Mitani Y, Mohamed TH (2011) Model predictive based load frequency control design in the presence of DFIG wind turbine. In: 2nd International conference on IEEE electric power and energy conversion systems (EPECS), pp 1–5

26.

Mohamed TH, Bevrani H, Hassan AA, Hiyama T (2010) Model predictive based load frequency control design. In: 16th International conference of electrical engineering, Busan, Korea

27.

Mohamed TH, Bevrani H, Hassan AA, Hiyama T (2011) Decentralized model predictive based load frequency control in an interconnected power system. Energy Convers Manag 52(2):1208–1214CrossRef

28.

Mohamed TH, Morel J, Bevrani H, Hiyama T (2012) Model predictive based load frequency control_design concerning wind turbines. Int J Electr Power Energy Syst 43(1):859–867CrossRef

29.

Sharma SK, Agarwal A, Kulshrestha A (2017) Proposed method to control load frequency in single area power system. Int Res J Eng Technol 04(10):1592–1595

30.

Thomas J, Dumur D, Buisson J, Guéguen H (2006) Model predictive control for hybrid systems under a state partition based MLD approach (SPMLD). In: Braz J, Araújo H, Vieira A, Encarnacao B (eds) Informatics in control, automation and robotics I. Springer, Dordrecht, pp 217–224. https://doi.org/10.1007/1-4020-4543-3_26 CrossRef

31.

Vazquez S, Rodriguez J, Rivera M, Franquelo LG, Norambuena M (2017) Model predictive control for power converters and drives: advances and trends. IEEE Trans Ind Electron 64(2):935–947CrossRef

32.

Nasiri MR, Farhangi S, Rodríguez J (2019) Model predictive control of multilevel CHB STATCOM in wind farm application using diophantine equations. IEEE Trans Ind Electron 66(2):1213–1223CrossRef

33.

Zhang S, Xiong R, Sun F (2017) Model predictive control for power management in a plug-in hybrid electric vehicle with a hybrid energy storage system. Appl Energy 185:1654–1662CrossRef

34.

Diab AAZ, Pankratov VV (2012) Model predictive control of vector controlled induction motor drive. In: IEEE 7th international forum on strategic technology (IFOST), pp 1–6

35.

Diab AZ, Vdovin VV, Kotin DA, Anosov VN, Pankratov VV (2014) Cascade model predictive vector control of induction motor drive. In: 12th IEEE international conference on actual problems of electronics instrument engineering (APEIE), pp 669–674

36.

Ichikawa S, Tomita M, Doki S, Okuma S (2006) Sensorless control of permanent-magnet synchronous motors using online parameter identification based on system identification theory. IEEE Trans Ind Electron 53(2):363–372CrossRef

37.

Kumar A, Daoutidis P (2002) Nonlinear dynamics and control of process systems with recycle. J Process Control 12(4):475–484CrossRef

Titel: A novel adaptive model predictive controller for load frequency control of power systems integrated with DFIG wind turbines
verfasst von: Mohamed A. Mohamed
Ahmed A. Zaki Diab
Hegazy Rezk
Tao Jin
Publikationsdatum: 20.04.2019
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 11/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-019-04205-w

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