Skip to main content
SpringerLink
Log in

Maximum Power Extraction Using Random Binary Searching Algorithm Under Non-uniform Insolation

  • Conference paper
  • First Online:
Advances in Communication and Computational Technology (ICACCT 2019)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 668))

  • 1764 Accesses

Abstract

Maximum power point tracker (MPPT) controls the DC/DC converter for extracting maximum power from solar photovoltaic (SPV) array connected with power generation system. MPPT operates at its maximum power point (MPP) (Vmp, Imp) irrespective to load conditions and input weather conditions. Use of by-pass diodes in series-connected SPV modules under non-uniform insolation is a key cause for many power peaks in the power–voltage characteristics of SPV array. Henceforth the problem of MPPT under partial shading becomes a nonlinear optimization problem. A new quick and reliable MPPT technique is proposed in this paper to identify the global MPP under partial shadow conditions. The computation time and correctness in tracking global MPP are compared with standard soft computing techniques: modified binary (MB) search, differential evolution (DE) techniques, and particle swarm optimization (PSO). The results show correctness of the presented random binary search technique in tracking the global MPP in very less time than the conventional soft computing techniques. The technique is quick, simple, and oscillation-free for tracking global MPP in least iterations; hence, the computation (hardware) requirements are less than that using PSO and DE MPPT techniques.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Subudhi B, Pradhan R (2013) A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Trans Sustain Energy 4(1):89–98

    Article  Google Scholar 

  2. Aureliano M, Galotto L, Poiltronieri L (2013) Evaluation of the main MPPT techniques for photovoltaic applications. IEEE Trans Ind Electron 60(3):1156–1167

    Article  Google Scholar 

  3. Esram T, Chapman P (2007) Comparison of photovoltaic array maximum power point tracking techniques. IEEE Trans Energy Convers 22(2):439–449

    Article  Google Scholar 

  4. Qiang M, Mingwei S, Liying L, Guerrero JM (2011) A novel improved variable step-size incremental-resistance MPPT method for PV systems. IEEE Trans Ind Electron 58(6):2427–2434

    Article  Google Scholar 

  5. Elgendy MA, Bashar Z, Atkinson DJ (2013) Assessment of the incremental conductance maximum power point tracking algorithm. IEEE Trans Sustain Energy 4(1):108–117

    Article  Google Scholar 

  6. Bader NA, Khaled HA, Finney SJ, Williams BW (2013) A maximum power point tracking technique for partially shaded photovoltaic systems in micro grids. IEEE Trans Ind Electron 60(4):1–4

    Google Scholar 

  7. Koutroulis E, Blaabjerg F (2012) A new technique for tracking the global maximum power point of PV arrays operating under partial-shading conditions. IEEE J Photovolt 2(2):642–649

    Article  Google Scholar 

  8. Ahmad Al N, Rached D (2012) Efficiency optimization of a DSP-based standalone PV system using fuzzy logic and dual-MPPT control. IEEE Trans Ind Inf 8(3):573–580

    Article  Google Scholar 

  9. Xiao L, Yaoyu L, John ES (2014) Maximum power point tracking for photovoltaic system using adaptive extreme seeking control. IEEE Trans Control Syst Technol 25(3):352–359

    Google Scholar 

  10. Peter PK, Agarwal V (2012) The input resistance of a reconfigurable switched capacitor DC–DC converter-based maximum power point tracker of a photovoltaic source. IEEE Trans Power Electron 27(12):574–581

    Article  Google Scholar 

  11. Liu YH, Huang SC, Huang JW, Liang WC (2012) A particle swarm optimization -based maximum power point tracking algorithm for PV systems operating under partially shaded conditions. IEEE Trans Energy Convers 27(4):1027–1030

    Article  Google Scholar 

  12. Ishaque K, Salam Z, Amjad M, Mekhilef S (2012) An improved particle swarm optimization (PSO)–based MPPT for PV with reduced steady-state oscillation. IEEE Trans Power Electron 27(8):3627–3634

    Article  Google Scholar 

  13. Azab M (2012) Optimal power point tracking for stand-alone PV system using particle swarm optimization. IEEE Trans Power Syst 27(4):1978–1985

    Google Scholar 

  14. Latham AM, Pilawa RP, Odame K, Sullivan CR (2013) Analysis and optimization of maximum power point tracking algorithms in the presence of noise. IEEE Trans Power Electron 28(7):3479–3486

    Article  Google Scholar 

  15. Hartmann LV (2013) Combining model-based and heuristic techniques for fast tracking the maximum-power point of photovoltaic systems. IEEE Trans Power Electron 28(6):2875–2881

    Article  Google Scholar 

  16. Kjer BS (2012) Evaluation of the hill climbing and the incremental conductance, maximum power point trackers for photovoltaic power systems. IEEE Trans Energy Convers 27(4):316–324

    Google Scholar 

  17. Young HJ, Jung DY, Kim JG, Kim JH, Lee TW, Won CY (2011) A real maximum power point tracking method for mismatching compensation in PV array under partially shaded conditions. IEEE Trans Power Electron 26(4):1001–1007

    Article  Google Scholar 

  18. Dhimish M (2019) Assessing MPPT techniques on hot-spotted and partially shaded photovoltaic modules: comprehensive review based on experimental data. IEEE Trans Electron Devices 66(3):1132–1144

    Article  Google Scholar 

  19. Al-Soeidat M, Lu DD-C, Zhu J (2018) An analog BJT-tuned maximum power point tracking technique for PV systems. IEEE Trans Circuits Syst II 66:637–641

    Article  Google Scholar 

  20. Başoğlu ME (2018) An improved 0.8VOC model based GMPPT technique for module level photovoltaic power optimizers. IEEE Trans Ind Appl 55:1913–1921

    Article  Google Scholar 

  21. Saikrishna Goud J, Kalpana R, Singh B (2018) A hybrid global maximum power point tracking technique with fast convergence speed for partial shaded PV systems. IEEE Trans Ind Appl 54:5367–5376

    Article  Google Scholar 

  22. Saikrishna Goud J, Kalpana R, Singh B, Kumar S (2018) Maximum power point tracking technique using artificial bee colony and hill climbing algorithms during mismatch insolation conditions on PV array. IET Renew Power Gener 12:1915–1922 ISSN 1752-1416

    Article  Google Scholar 

  23. Lin WM, Hong CM, Chen CH (2011) Neural-network-based MPPT control of a stand-alone hybrid power generation system. IEEE Trans Power Electron 26(12):3571–3578

    Article  Google Scholar 

  24. Shi Y, Eberhart RC (2001) Fuzzy adaptive particle swarm optimization. In: Proceedings of the congress on evolutionary computation 2001, Seoul, Korea. IEEE Service Center, pp 101–106

    Google Scholar 

  25. Thomas CH, Leiserson CE, Clifford S, Rivest RL (2009) Introduction to algorithms, 3rd edn. MIT Press and McGraw-Hill, Cambridge. ISBN 0-262-03384-4

    MATH  Google Scholar 

  26. Lata Agarwal K (2017) A performance maximization of small scale grid connected solar photovoltaic power plants. Ph.D. thesis, J.N.V.U., Jodhpur, Rajasthan, India

    Google Scholar 

Download references

Acknowledgement

Authors are thankful to TEQIP-III at RTU-ATU for providing grant under the competitive research scheme (CRS) with project sanction id TEQIP-III/RTU(ATU)/CRS/2019-20/30.

Author information

Authors and Affiliations

  1. Department of EE, JIET, Jodhpur, India

    Kusum Lata Agarwal

  2. Department of EE, M.B.M. Engineering College, JNVU, Jodhpur, India

    Avdhesh Sharma

Authors
  1. Kusum Lata Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Avdhesh Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kusum Lata Agarwal .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Maryland Eastern Shore, Princess Anne, MD, USA

    Gurdeep Singh Hura

  2. Department of Master of Computer Applications, National Institute of Technology Kurukshetra, Kurukshetra, Haryana, India

    Ashutosh Kumar Singh

  3. Department of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia

    Lau Siong Hoe

Appendix

Appendix

See Tables 2 and 3

Table 2 Specifications of system investigated
Full size table
Table 3 Various insolation patterns for SPV array of [3 * 3]
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Agarwal, K.L., Sharma, A. (2021). Maximum Power Extraction Using Random Binary Searching Algorithm Under Non-uniform Insolation. In: Hura, G.S., Singh, A.K., Siong Hoe, L. (eds) Advances in Communication and Computational Technology. ICACCT 2019. Lecture Notes in Electrical Engineering, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-15-5341-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-5341-7_7

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5340-0

  • Online ISBN: 978-981-15-5341-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation