The dynamic nature of load and wind power could lead to reactive power imbalance, and hence the voltage deviations in a wind–diesel power system. These deviations, if not controlled, may drive the system to operate in an unstable manner. Therefore, in this paper, a static synchronous compensator (STATCOM) is interconnected to the system to achieve reactive power balancing and minimize voltage deviations. To improve the dynamic performance of STATCOM and achieve the effective operation of the system, an optimized sliding mode controller (SMC) is designed. With the help of the design of a first-order switching manifold, an SMC is designed, which generates a control law to control the converter firing angle, and hence the reactive power output of the STATCOM. To eliminate the chattering drawback of SMC and improve the convergence characteristics, a second-order super-twisting sliding mode controller (STSMC) is proposed. The asymptotic stability of the proposed controller is guaranteed through the Lyapunov stability analysis. Particle swarm optimization (PSO) is employed to fine-tune controller parameters and achieve optimal performance. Validation of the improved performance of the system through this proposed scheme has been carried out in the MATLAB/Simulink environment and presented in the simulation studies.
Al-DujailiAQFalahAHumaidiAJ, et al. (2020) Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study. International Journal of Advanced Robotic Systems17(6): 1–17.
2.
AmimeurHAouzellagDAbdessemedR, et al. (2012) Sliding mode control of a dual-stator induction generator for wind energy conversion systems. International Journal of Electrical Power & Energy Systems42(1): 60–70.
3.
Arabzadeh SaheliMFazelpourFSoltaniN, et al. (2019) Performance analysis of a photovoltaic/wind/diesel hybrid power generation system for domestic utilization in Winnipeg, Manitoba, Canada. Environmental Progress & Sustainable Energy38(2): 548–562.
4.
BalatM (2005) Usage of energy sources and environmental problems. Energy Exploration & Exploitation23(2): 141–167.
5.
BansalR (2008) Modelling and automatic reactive power control of isolated wind-diesel hybrid power systems using ANN. Energy Conversion and Management49(2): 357–364.
6.
BansalRC (2006) Automatic reactive-power control of isolated wind–diesel hybrid power systems. IEEE Transactions on Industrial Electronics53(4): 1116–1126.
7.
BansalRCBhattiTSKothariDP (2003) Automatic reactive power control of wind-diesel-micro-hydro autonomous hybrid power systems using ANN tuned static VAr compensator. In: Large engineering systems conference on power engineering, Montreal, QC, Canada, 7–9 May, pp. 182–188. New York: IEEE.
8.
BansalRCBhattiTSKothariDP (2004) Automatic reactive power control of isolated wind-diesel hybrid power systems for variable wind speed/slip. Electric Power Components and Systems32(9): 901–912.
9.
DongHYangXBasinM (2022) Practical tracking of permanent magnet linear motor via logarithmic sliding mode control. IEEE/ASME Transactions on Mechatronics27: 4112–4121.
10.
DongHYangXGaoH, et al. (2023) Practical terminal slidingmode control and its applications in servo systems. IEEE Transactions on Industrial Electronics70: 752–761.
11.
ElgerdO (1982) Electric Energy Systems Theory: An Introduction. New York: McGraw-Hill.
12.
ErramiYOuassaidMMaaroufiM (2015) A performance comparison of a nonlinear and a linear control for grid connected PMSG wind energy conversion system. International Journal of Electrical Power & Energy Systems68: 180–194.
13.
EvangelistaCPulestonPValenciagaF, et al. (2013) Lyapunov-designed super-twisting sliding mode control for wind energy conversion optimization. IEEE Transactions on Industrial Electronics60(2): 538–545.
14.
FengJZhaoDYanXG, et al. (2022) Dynamic output feedback sliding mode control for uncertain linear systems. Transactions of the Institute of Measurement and Control44(6): 1178–1193.
15.
FengZFeiJ (2018) Design and analysis of adaptive super-twisting sliding mode control for a microgyroscope. PLoS ONE13(1): e0189457.
16.
FesharakiJJAmnyiehZHDFatemiMJR, et al. (2021) Robust maximum power point tracking with a novel second order sliding mode controller. Transactions of the Institute of Measurement and Control43(5): 1168–1175.
17.
GuchhaitPBanerjeeA (2020) Stability enhancement of wind energy integrated hybrid system with the help of static synchronous compensator and symbiosis organisms search algorithm. Protection and Control of Modern Power Systems5: 11.
18.
GuchhaitPKBanerjeeAMukherjeeV (2020) Comparative study using soft computing techniques for the reactive power compensation of a hybrid power system model. Ain Shams Engineering Journal11(1): 87–98.
19.
GuoBSuMSunY, et al. (2019) A robust second-order sliding mode control for single-phase photovoltaic grid-connected voltage source inverter. IEEE Access7: 53202–53212.
20.
HumaidiAJHasanAF (2019) Particle swarm optimization–based adaptive super-twisting sliding mode control design for 2-degree-of-freedom helicopter. Measurement and Control52(9–10): 1403–1419.
21.
ItkisU (1976) Control Systems of Variable Structure. New York: Wiley.
22.
KassemAMAbdelazizAY (2014) Reactive power control for voltage stability of standalone hybrid wind–diesel power system based on functional model predictive control. IET Renewable Power Generation8(8): 887–899.
23.
KennedyJEberhartR (1995) Particle swarm optimization. In: Proceedings of ICNN’95—international conference on neural networks, vol. 4, Perth, WA, Australia, 27 November–1 December, pp. 1942–1948. New York: IEEE.
24.
KrimYAbbesDKrimS, et al. (2016) Nonlinear control strategy of a wind farm for participation in the system services without adding any storage organs. In: 2016 4th international conference on control engineering information technology (CEIT), Hammamet, Tunisia, 16–18 December, pp. 1–7. New York: IEEE.
25.
KrimYAbbesDKrimS, et al. (2018) Power management and second-order sliding mode control for standalone hybrid wind energy with battery energy storage system. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering232(10): 1389–1411.
26.
KumarAAnwarMNKumarS (2021) Sliding mode controller design for frequency regulation in an interconnected power system. Protection and Control of Modern Power Systems6: 6.
27.
KyesswaM (2020) Dynamic modelling and control for assessment of large-scale wind and solar integration in power systems. IET Renewable Power Generation14(8): 4010–4018.
28.
LascuCArgeseanuABlaabjergF (2020) Supertwisting sliding-mode direct torque and flux control of induction machine drives. IEEE Transactions on Power Electronics35(5): 5057–5065.
29.
MarwaJDhahriSSellamiA (2017) Design of robust supertwisting algorithm based second-order sliding mode controller for nonlinear systems with both matched and unmatched uncertainty. Complexity2017: 1972921.
30.
MiYMaCWangS, et al. (2016) Reactive power control of an isolated wind-diesel hybrid power system based on SVC by using sliding mode control. In: 2016 35th Chinese control conference (CCC), Chengdu, China, 27–29 July, pp. 9882–9887. New York: IEEE.
31.
MiYSongYFuY, et al. (2020) The adaptive sliding mode reactive power control strategy for wind–diesel power system based on sliding mode observer. IEEE Transactions on Sustainable Energy11(4): 2241–2251.
32.
SahuAPanigrahiSKPattnaikS (2012) Fast convergence particle swarm optimization for functions optimization. Procedia Technology4: 319–324.
33.
SaxenaNKKumarA (2016) Investigation of STATCOM performance with different participation of dynamic and static load in isolated hybrid power system. In: 2016 IEEE 1st international conference on power electronics, intelligent control and energy systems (ICPEICES), New Delhi, India, 4–6 July, pp. 1–6. New York: IEEE.
34.
ShahbazuddinSSridharG (2017) Automatic reactive power control of an isolated wind-diesel hybrid power system using firefly algorithm. In: 2017 international conference on recent trends in electrical, electronics and computing technologies (ICRTEECT), Warangal, India, 30–31 July, pp. 93–100. New York: IEEE.
35.
SharmaPBhattiTSRamakrishnaKSS (2012) Study of an isolated wind–diesel hybrid power system with STATCOM by incorporating a new mathematical model of PMIG. European Transactions on Electrical Power22(3): 351–363.
36.
SharmaPVNareshR (2019) Optimal sliding mode control for frequency regulation in deregulated power systems with DFIG-based wind turbine and TCSC–SMES. Neural Computing and Applications31: 1–18.
37.
ShiraliyanMSharmaPSharmaC (2018) Automatic reactive power control of isolated wind–diesel hybrid power system using artificial bee colony and gray wolf optimization. International Journal of Green Energy15(14–15): 889–904.
38.
SteinbergerMHornMFridmanL (2020) Variable-Structure Systems and Sliding-Mode Control: From Theory to Practice. Cham: Springer International Publishing.
39.
ThokerZALoneSA (2021) Voltage and frequency control of wind–diesel power system through adaptive sliding mode control of superconducting magnetic energy storage. Wind Engineering45(5): 1057–1071.
40.
UtkinVI (2008) Sliding mode control: Mathematical tools, design and applications. In: NistriPStefaniG (eds) Nonlinear and Optimal Control Theory Lecture Notes in Mathematics. Berlin: Springer, pp. 289–347.
41.
WaiRJLinCYWuWC, et al. (2013) Design of backstepping control for high-performance inverter with stand-alone and grid-connected power-supply modes. IET Power Electronics6(4): 752–762.
42.
YousufVAhmadA (2021) ADRC-based control strategies to alleviate SSR using STATCOM. Electrical Engineering103: 2303–2314.
43.
YunhaoHYuanyuanSHanZ, et al. (2018) Sliding mode reactive power control of isolated wind-diesel hybrid power system based on STATCOM. In: 2018 37th Chinese control conference (CCC), Wuhan, China, 25–27 July, pp. 8709–8714. New York: IEEE.
44.
ZhangXSunLZhaoK, et al. (2013) Nonlinear speed control for PMSM system using sliding-mode control and disturbance compensation techniques. IEEE Transactions on Power Electronics28(3): 1358–1365.
45.
ZholtayevDRubagottiMDoTD (2022) Adaptive super-twisting sliding mode control for maximum power point tracking of PMSG-based wind energy conversion systems. Renewable Energy183: 877–889.
