Call for Paper - Upcoming Issues

Performance Analysis of OTC and Improved PSO MPPT Techniques for DFIG-Based Wind Energy Conversion Systems

International Journal of Electrical and Electronics Engineering
© 2023 by SSRG - IJEEE Journal
Volume 10 Issue 8
Year of Publication : 2023
Authors : Sreenivasulu Meda, Bishnu Prasad Muni, Kolli Ramesh Reddy
10.14445/23488379/IJEEE-V10I8P121
pdf
How to Cite?

Sreenivasulu Meda, Bishnu Prasad Muni, Kolli Ramesh Reddy, "Performance Analysis of OTC and Improved PSO MPPT Techniques for DFIG-Based Wind Energy Conversion Systems," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 8, pp. 215-223, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I8P121

Abstract:

With the increase in energy power requirement and reduction in the availability of conventional fuel resources, the practice of generating electrical energy using renewable energy resources has gained importance. Wind is considered a significant resource commercially used for electricity generation. Wind velocity varies continuously, and hence, the output of the wind generator varies. As a result, the electrical power a wind turbine develops is not at the corresponding maximum value. Hence, a Maximum Power Point Tracking (MPPT) controller is designed for a wind turbine, enabling it to derive the maximum possible power at all wind speeds. In this paper, a comparative analysis of Optimal Torque (OT) and improved Particle Swarm Optimization (PSO) MPPT techniques for a Doubly-Fed Induction Generator (DFIG) is obtained. The Simulink model for DFIG is first obtained, and the system’s output power without MPPT is examined. Conventional OT is then implemented. Secondly, an improved PSO MPPT technique is proposed, extracting a better quality of output power that exhibits better dynamics and gives more output power. The results of both methods are then compared and tabulated.

Keywords:

DFIG, MPPT, OTC, PSO, Wind energy.

References:

[1] I. K. Buehring, and L. L. Freris, “Control Policies for Wind-Energy Conversion Systems,” IEE Proceedings C (Generation, Transmission and Distribution), vol. 128, no. 5, pp. 253-261, 1981.
[CrossRef] [Google Scholar] [Publisher link]
[2] Geng Hua, and Yang Geng, “A Novel Control Strategy of MPPT Taking Dynamics of Wind Turbine into Account,” 37th IEEE Power Electronics Specialists Conference, pp. 1–6, 2006.
[CrossRef] [Google Scholar] [Publisher link]
[3] M. A. Abdullah et al., “A Review of Maximum Power Point Tracking Algorithms for Wind Energy Systems,” Renewable and Sustainable Energy Reviews, vol. 16, no. 5, pp. 3220–3227, 2012.
[CrossRef] [Google Scholar] [Publisher link]
[4] Sooraj Suresh Kumar, K. Jayanthi, and N. Senthil Kumar, “Maximum Power Point Tracking for a PMSG Based Variable Speed Wind Energy Conversion System using Optimal Torque Control,” International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), pp. 347-352, 2016.
[CrossRef] [Google Scholar] [Publisher link]
[5] Ameni Kadri, Hajer Marzougui, and Faouzi Bacha, “MPPT Control Methods in Wind Energy Conversion System using DFIG,” 4th International Conference on Control Engineering & Information Technology (CElT), pp. 1-6, 2016.
[CrossRef] [Google Scholar] [Publisher link]
[6] T. Nakamura et al., “Optimum Control of IPMSG for Wind Generation System,” Power Conversion Conference (PCC), vol. 3, pp. 1435-1440, 2002.
[CrossRef] [Google Scholar] [Publisher link]
[7] Hussain Jakeer, and Mahesh K. Mishra, “Adaptive MPPT Control Algorithm for Small-Scale Wind Energy Conversion Systems,” IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), IEEE International Conference, pp. 1-5, 2014.
[CrossRef] [Google Scholar] [Publisher link]
[8] N. Niassati et al., “A New Maximum Power Point Tracking Technique for Wind Power Conversion Systems,” 15th International Power Electronics and Motion Control Conference (EPE/PEMC), pp. DS2d.8-1-DS2d.8-6, 2012.
[CrossRef] [Google Scholar] [Publisher link]
[9] M. Nasiri, J. Milimonfared, and S. H. Fathi, “Modeling Analysis and Comparison of TSR and OTC Methods for MPPT and Power Smoothing in Permanent Magnet Synchronous Generator-Based Wind Turbines,” Energy Conversion and Management, vol. 86, pp. 892–900, 2014.
[CrossRef] [Google Scholar] [Publisher link]
[10] Karim Belmokhtar, Mamadou L. Doumbia, and Kodjo Agbossou, “Modelling and Fuzzy Logic Control of DFIG Based Wind Energy Conversion Systems,” IEEE International Symposium on Industrial Electronics, pp. 1888-1893, 2012.
[CrossRef] [Google Scholar] [Publisher link]
[11] M. Bezza et al., “Sensorless MPPT Fuzzy Controller for DFIG Wind Turbine,” Energy Procedia, vol. 18, pp. 339-348, 2012.
[CrossRef] [Google Scholar] [Publisher link]
[12] Youcef Djeriri et al., “Three-Level NPC Voltage Source Converter Based Direct Power Control of the Doubly Fed Induction Generator at Low Constant Switching Frequency,” Renewable Energies Review, vol. 16, no. 1, pp. 91-103, 2013.
[Google Scholar] [Publisher link]
[13] Syed Muhammad Raza Kazmi et al., “Review and Critical Analysis of the Research Papers Published Till Date on Maximum Power Point Tracking in Wind Energy Conversion System,” IEEE Energy Conversion Congress and Exposition, pp. 4075-4082, 2010.
[CrossRef] [Google Scholar] [Publisher link]
[14] Ayushi Sachan, Akhilesh Kumar Gupta, and Paulson Samuel, “A Review of MPPT Algorithms Employed in Wind Energy Conversion Systems,” Journal of Green Engineering, vol. 6, no. 4, pp. 385–402, 2017.
[CrossRef] [Google Scholar] [Publisher link]
[15] Chowdary V. Govinda et al., “A Review on Various MPPT Techniques for Wind Energy Conversion System,” International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC), pp. 310-326, 2018.
[CrossRef] [Google Scholar] [Publisher link]
[16] Hossam H. H. Mousa, Abdel-Raheem Youssef, and Essam E. M. Mohamed, “State of the Art Perturb and Observe MPPT Algorithms Based Wind Energy Conversion Systems: A Technology Review,” International Journal of Electrical Power and Energy Systems, vol. 126, 2021.
[CrossRef] [Google Scholar] [Publisher link]
[17] Ali Nouriani, and Hamed Moradi, “Variable Speed Wind Turbine Power Control: A Comparison between Multiple MPPT Based Methods,” International Journal of Dynamics and Control, vol. 10, pp. 654-667, 2021.
[CrossRef] [Google Scholar] [Publisher link]
[18] Hadadi Sudheendra, Tefera Mekonnen, and Melaku, “Recent Trends in the Hybrid HVDC with Wind Energy a Solution to the Problem and Challenges,” SSRG International Journal of VLSI & Signal Processing, vol. 2, no. 2, pp. 20-33, 2015.
[CrossRef] [Google Scholar] [Publisher link]
[19] Surabhi Chandra, Prerna Gaur, and Srishti, “Maximum Power Point Tracking Approaches for Wind–Solar Hybrid Renewable Energy System-A Review,” Advances in Energy and Power Systems, Lecture Notes in Electrical Engineering, pp. 3-12, 2018.
[CrossRef] [Google Scholar] [Publisher link]
[20] C. Swaminathan, and G. Nagarathinam, “A Perspective Observation of Power Generation using Wind Energy and its Benefits,” SSRG International Journal of Industrial Engineering, vol. 3, no. 3, pp. 7-11, 2016.
[CrossRef] [Publisher link]
[21] C. Srisailam, and M. Manjula, “Optimized FOPID Controller for Transient Stability Improvement in a Microgrid with Energy Storage,” SSRG International Journal of Electrical and Electronics Engineering, vol. 10, no. 2, pp. 19-34, 2023.
[CrossRef] [Publisher link]
[22] Mekalathur B. Hemanth Kumar et al., “Review on Control Techniques and Methodologies for Maximum Power Extraction from Wind Energy Systems,” IET Renewable Power Generation, vol. 12, no. 14, pp. 1609-1622, 2018.
[CrossRef] [Google Scholar] [Publisher link]
[23] B. Srikanth Goud et al., “Cuckoo Search Optimization Based MPPT for Integrated DFIG-Wind Energy System,” International Conference on Decision Aid Sciences and Application, pp. 636-639, 2020.
[CrossRef] [Google Scholar] [Publisher link]
[24] Youssef Ait Ali, and Mohammed Ouassaid, “Advanced Control Strategy of DFIG Based Wind Turbine using Combined Artificial Neural Network and PSO Algorithm,” International Conference on Electrical and Information Technologies, pp. 1-7, 2020.
[CrossRef] [Google Scholar] [Publisher link]
[25] Abdelhalim Borni et al., “Comparative Study of P&O and Fuzzy MPPT Controllers and Their Optimization using PSO and GA to Improve Wind Energy System,” International Journal for Engineering Modelling, vol. 34, no. 2, pp. 55-76, 2021.
[CrossRef] [Google Scholar] [Publisher link]
[26] Youssef Ait Ali, and Mohammed Ouassaid, “Sensorless MPPT Controller using Particle Swarm and Grey Wolf Optimization for Wind Turbines,” 7 th International Renewable and Sustainable Energy Conference, pp. 1-7, 2019.
[CrossRef] [Google Scholar] [Publisher link]
[27] M. A. Abdullah et al., “Particle Swarm Optimization-Based Maximum Power Point Tracking Algorithm for Wind Energy Conversion System,” IEEE Conference on Power and Energy, pp. 65-70, 2012.
[CrossRef] [Google Scholar] [Publisher link]
[28] Majid Abdullateef Abdullah et al., “Towards Green Energy for Smart Cities: Particle Swarm Optimization Based MPPT Approach,” IEEE Access, vol. 6, pp. 58427-58438, 2018.
[CrossRef] [Google Scholar] [Publisher link]
[29] J. Prasanth Ram, N. Rajasekara, and Masafumi Miyatake, “Design and Overview of Maximum Power Point Tracking Techniques in Wind and Solar Photovoltaic Systems: A Review,” Renewable and Sustainable Energy Reviews, vol. 73, pp. 1138–1159, 2017.
[CrossRef] [Google Scholar] [Publisher link]