Electrical Engineering

Kiran Kumar B M This email address is being protected from spambots. You need JavaScript enabled to view it.1, Indira M S1, and S Nagaraja Rao1

1M S Ramaiah University of Applied Sciences, Bangalore, India

 

Received: May 16, 2021
Accepted: July 23, 2021
Publication Date: December 3, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202208_25(4).0014  


ABSTRACT

Solar Photovoltaic (SPV) and wind energy are two major sources of renewable energy that are intermittent in nature. A hybrid system consisting of SPV and Wind Energy Conversion System (WECS) can meet the energy needs as either of the source continues to generate energy, in the absence of the other that is reliable and cost effective. The paper presents detailed mathematical modelling, simulation and performance analysis of a single cell SPV and Permanent Magnet Synchronous Generator (PMSG) based WECS. These two sources are integrated to form a hybrid renewable energy system. The hybrid model is simulated and the overall performance is analyzed using MATLAB/Simulink for varying temperature/irradiation conditions and varying wind speeds for SPV and WECS respectively. Performance characteristics of the hybrid PV and WECS are presented. The paper also presents as a case study, the annual energy generation for a chosen location from individual SPV and WECS systems based on the real time data collected from Solacast website. This study evaluates the feasibility of implementation of a hybrid system at the site.


Keywords: Boost converter, Irradiation, Solar Photovoltaic, Temperature, Wind speed


REFERENCES

  1. [1] S. Lakshminarayanan, B. Kiran Kumar, S. N. Rao, and S. Pranupa, (2021) “Current mode control of single phase grid tie inverter with anti-islanding" Int J Pow Elec & Dri Syst 12(1): 241–248.
  2. [2] A. Mahesh and K. S. Sandhu, (2015) “Hybrid wind/photovoltaic energy system developments: Critical review and findings" Renewable and Sustainable Energy Reviews 52: 1135–1147. DOI: 10.1016/j.rser.2015.08.008.
  3. [3] M. S. Javed, A. Song, and T. Ma, (2019) “Technoeconomic assessment of a stand-alone hybrid solar-windbattery system for a remote island using genetic algorithm" Energy 176: 704–717. DOI: 10.1016/j.energy.2019.03.131.
  4. [4] T. Shilpashree, K. B. Kumar, and S. Pranupa, (2021) “A Comparative Study of Performance Analysis of Solar PV With Interleaved DC-DC Converters": 1–6. DOI: 10. 1109/RTEICT52294.2021.9573809.
  5. [5] B. K. Kumar, M. Indira, and S. N. Rao, (2021) “Performance Evaluation of Solar PV Using Multiple Level Voltage Gain Boost Converter with CLC Cell": 237–251. DOI: 10.1007/978-981-16-0749-3_18.
  6. [6] H. Patel, M. Gupta, and A. K. Bohre. “Mathematical modeling and performance analysis of MPPT based solar PV system”. In: 2016 International Conference on Electrical Power and Energy Systems (ICEPES). IEEE. 2016, 157–162. DOI: 10.1109/ICEPES.2016.7915923.
  7. [7] M. H. Ahmadi, M. Ghazvini, M. Sadeghzadeh, M. Alhuyi Nazari, R. Kumar, A. Naeimi, and T. Ming, (2018) “Solar power technology for electricity generation: A critical review" Energy Science& Engineering 6(5):340–361. DOI: 10.1002/ese3.239.
  8. [8] E. J. N. Menezes, A. M. Araújo, and N. S. B. da Silva, (2018) “A review on wind turbine control and its associated methods" Journal of cleaner production 174:945–953. DOI: 10.1016/j.jclepro.2017.10.297.
  9. [9] ¸S. E. C. ¸Sener, J. L. Sharp, and A. Anctil, (2018) “Factors impacting diverging paths of renewable energy: A review" Renewable and Sustainable Energy Reviews 81: 2335–2342. DOI: 10.1016/j.rser.2017.06.042.
  10. [10] R. Naveen, P. Revankar, and S. Rajanna, (2020) “Integration of Renewable Energy Systems for Optimal Energy Needs-a review" International Journal of Renewable Energy Research (IJRER) 10(2): 727–742.
  11. [11] E. Muh and F. Tabet, (2019) “Comparative analysis of hybrid renewable energy systems for off-grid applications in Southern Cameroons" Renewable energy 135: 41–54. DOI: 10.1016/j.renene.2018.11.105.
  12. [12] M. D. Al-Falahi, S. Jayasinghe, and H. Enshaei, (2017) “A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system" Energy conversion and management 143: 252–274. DOI: 10.1016/j.enconman.2017.04.019.
  13. [13] S.Wagh and P.Walke, (2017) “Review on wind-solar hybrid power system" International Journal of Research In Science & Engineering 3(2):
  14. [14] K. Kumar, N. R. Babu, and K. Prabhu, (2017) “Design and analysis of an integrated Cuk-SEPIC converter with MPPT for standalone wind/PV hybrid system" International Journal of Renewable Energy Research (IJRER) 7(1): 96–106.
  15. [15] M. Malinowski, J. I. Leon, and H. Abu-Rub, (2017) “Solar photovoltaic and thermal energy systems: Current technology and future trends" Proceedings of the IEEE 105(11): 2132–2146. DOI: 10.1109/JPROC.2017.2690343.
  16. [16] K. Yoshikawa, W. Yoshida, T. Irie, H. Kawasaki, K. Konishi, H. Ishibashi, T. Asatani, D. Adachi, M. Kanematsu, H. Uzu, et al., (2017) “Exceeding conversion efficiency of 26% by heterojunction interdigitated back contact solar cell with thin film Si technology" Solar Energy Materials and Solar Cells 173: 37–42. DOI:10.1016/j.solmat.2017.06.024.
  17. [17] A. K. Podder, N. K. Roy, and H. R. Pota, (2019) “MPPT methods for solar PV systems: a critical review based on tracking nature" IET Renewable Power Generation 13(10): 1615–1632. DOI: 10.1049/iet-rpg.2018.5946.
  18. [18] H. Abouobaida et al., (2017) “Practical performance evaluation of maximum power point tracking algorithms in a photovoltaic system" International Journal of Power Electronics and Drive Systems 8(4): 1744. DOI: 10.11591/ijpeds.v8i4.pp1744-1755.
  19. [19] Y. Mahmoud. “Toward a long-term evaluation of MPPT techniques in PV systems”. In: 2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA). IEEE. 2017, 1106–1113. DOI: 10.1109/DISTRA.2017.8191226.
  20. [20] B. Kiran Kumar, M. Indira, and S. Nagaraja Rao, (2021) “Performance analysis of multiple gain boost converter with hybrid maximum power point tracker for solar PV connected to grid" Clean Energy 5(4): 655–672. DOI: 10.1093/ce/zkab037.
  21. [21] N. R. Sulake, A. K. Devarasetty Venkata, and S. B. Choppavarapu, (2018) “FPGA implementation of a three-level boost converter-fed seven-level dc-link cascade H-bridge inverter for photovoltaic applications" Electronics 7(11): 282.
  22. [22] A. Bensalah, M. Benhamida, G. Barakat, and Y. Amara. “Large wind turbine generators: State-ofthe-art review”. In: 2018 XIII International Conference on Electrical Machines (ICEM). IEEE. 2018, 2205–2211. DOI: 10.1109/ICELMACH.2018.8507165.
  23. [23] A. AARIB, A. EL MOUDDEN, A. EL MOUDDEN, and A. HMIDAT, (2021) “Control and Investigation of Operational Characteristics of Variable Speed Wind Turbines with Doubly Fed Induction Generators"Walailak Journal of Science and Technology (WJST) 18(4): 10995–13. DOI: 10.48048/wjst.2021.10995.
  24. [24] V. Yaramasu, A. Dekka, M. J. Durán, S. Kouro, and B. Wu, (2017) “PMSG-based wind energy conversion systems: survey on power converters and controls" IET Electric Power Applications 11(6): 956–968. DOI: 10.1049/iet-epa.2016.0799.
  25. [25] T. M. Letcher. Wind energy engineering: A handbook for onshore and offshore wind turbines. Academic Press, 2017.
  26. [26] Y. El Mourabit, A. Derouich, A. El Ghzizal, N. El Ouanjli, and O. Zamzoum, (2017) “DTC-SVM Control for permanent magnet synchronous generator based variable speed wind turbine" International Journal of Power Electronics and Drive Systems 8(4): 1732. DOI: 10.11591/ijpeds.v8i4.pp1732-1743.
  27. [27] P. Joshi and K. Roy. “Implementation of Hybrid Wind–Solar Energy Conversion Systems”. In: Proceedings of International Conference on Data Science and Applications. Springer. 2021, 221–240. DOI: 10.1007/978-981-15-7561-7_18.

Latest Articles

Multi-level Semantic Fusion Network for Few-shot Multimedia Image Recognition in Education Management
Multi-level Semantic Fusion Network for Few-shot Multimedia Image Recognition in Education ManagementVolume 28, Issue 2 (In Press)

Read more: ...

River bank erosion prediction using multivariable linear regression
River bank erosion prediction using multivariable linear regressionVolume 27, Issue 12 (In Press)

Read more: ...

Optimization of Ultrasound-Assisted Pectin Extraction from Durian Rind
Optimization of Ultrasound-Assisted Pectin Extraction from Durian RindVolume 28, Issue 2 (In Press)

Read more: ...

Short-time prediction model for cross-section passenger flow in urban transit trains using GCN-AM-BiLSTM
Short-time prediction model for cross-section passenger flow in urban transit trains using GCN-AM-BiLSTMVolume 28, Issue 2 (In Press)

Read more: ...

Response Prediction Analysis of RC Frame Structures Using Support Vector Machine Algorithm
Response Prediction Analysis of RC Frame Structures Using Support Vector Machine AlgorithmVolume 28, Issue 2 (In Press)

Read more: ...

Using the non-dominated sorting genetic algorithm II for multi-objective optimization of acoustic performance in sandwich panels with cellular honeycomb core
Using the non-dominated sorting genetic algorithm II for multi-objective optimization of acoustic performance in sandwich panels with cellular honeycomb coreVolume 28, Issue 2 (In Press)

Read more: ...

Analyzing Glass Configurations For Energy Efficiency In Building Envelopes: A Comparative
Analyzing Glass Configurations For Energy Efficiency In Building Envelopes: A ComparativeVolume 28, Issue 2 (In Press)

Read more: ...

Assessment of the optimal gold recovery rate through heap leach extraction process from hydrothermal alteration zone ore
Assessment of the optimal gold recovery rate through heap leach extraction process from hydrothermal alteration zone oreVolume 28, Issue 2 (In Press)

Read more: ...

Research on the Time-Varying Relationship between Macroeconomic Variables and the Stock Market Volatility Based on TVP-VAR Model
Research on the Time-Varying Relationship between Macroeconomic Variables and the Stock Market Volatility Based on TVP-VAR ModelVolume 28, Issue 2 (In Press)

Read more: ...