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Evaluation on Training Algorithms of Back Propagation Neural Network for a Solar Photovoltaic Based DSTATCOM System

  • Nor Hanisah BaharudinEmail author
  • Tunku Muhammad Nizar Tunku Mansur
  • Rosnazri Ali
  • Muhammad Irwanto Misrun
Chapter
Part of the Power Systems book series (POWSYS)

Abstract

This chapter discusses evaluation on the Back Propagation Neural Network (BPNN) control algorithm based on Fast Fourier Transform (FFT) control algorithm with different BPNN training algorithms for Distribution Static Compensator (DSTATCOM) with integrated solar photovoltaic system. Furthermore, the comparison is performed with different weight or bias training functions such as supervised and unsupervised. Each training algorithms have been utilized to investigate its performance in generating the target pattern for harmonic elimination in term of accuracy, learning epochs and training time. The performance of the BPNN training algorithms is determined by calculating the error between the target and output pattern using Mean Squared Error (MSE). The lower value of the MSE shows the higher accuracy of the output pattern according to the target pattern given. Number of iterations (epochs) and training time are evaluated to investigate the performance of different BPNN training algorithms on DSTATCOM for harmonic reduction under nonlinear load condition.

References

  1. 1.
    Xue Y, Chang L, Kjær SB, Bordonau J, Shimizu T (2004) Topologies of single-phase inverters for small distributed power generators: an overview. IEEE Trans Power Electron 19(5):1305–1314CrossRefGoogle Scholar
  2. 2.
    Shahnia F, Ghosh A, Ledwich G, Zare F (2014) Voltage unbalance improvement in low voltage residential feeders with rooftop PVs using custom power devices. Int J Electr Power Energy Syst 55:362–377CrossRefGoogle Scholar
  3. 3.
    Trichakis P, Taylor PC, Lyons PF, Hair R (2008) Predicting the technical impacts of high levels of small-scale embedded generators on low-voltage networks. IET Renew Power Gener 2(4):249–262CrossRefGoogle Scholar
  4. 4.
    Hussin MZ, Hasliza N, Yaacob A, Zain ZM, Omar AM, Shaari S (2012) A development and challenges of grid-connected photovoltaic system in Malaysia. In: 2012 IEEE control and system graduate research colloquium (ICSGRC 2012). pp 191–196Google Scholar
  5. 5.
    Papathanassiou SA (2007) A technical evaluation framework for the connection of DG to the distribution network. Electr Power Syst Res 77:24–34CrossRefGoogle Scholar
  6. 6.
    Eltawil MA, Zhao Z (2010) Grid-connected photovoltaic power systems: technical and potential problems a review. Renew Sustain Energy Rev 14:112–129CrossRefGoogle Scholar
  7. 7.
    Karimi M, Mokhlis H, Naidu K, Uddin S, Bakar AHA (2016) Photovoltaic penetration issues and impacts in distribution network a review. Renew Sustain Energy Rev 53:594–605CrossRefGoogle Scholar
  8. 8.
    Hernández JC, Ortega MJ, De Cruz J, Vera D (2011) Guidelines for the technical assessment of harmonic, flicker and unbalance emission limits for PV-distributed generation. Electr Power Syst Res 81:1247–1257CrossRefGoogle Scholar
  9. 9.
    IEEE recommended practice for utility interface of photovoltaic (PV) systems: IEEE Std 929-2000. Technical report (2000)Google Scholar
  10. 10.
    Kannan VK, Rengarajan N (2014) Investigating the performance of photovoltaic based DSTATCOM using I cos\(\it{\Phi} \) algorithm. Int J Electr Power Energy Syst 54:376–386CrossRefGoogle Scholar
  11. 11.
    Mahela OP, Shaik AG (2015) A review of distribution static compensator. Renew Sustain Energy Rev 50:531–546CrossRefGoogle Scholar
  12. 12.
    Kannan VK, Rengarajan N (2012) Photovoltaic based distribution static compensator for power quality improvement. Int J Electr Power Energy Syst 42(1):685–692CrossRefGoogle Scholar
  13. 13.
    Agarwal RK, Hussain I, Singh B (2017) Implementation of LLMF control algorithm for three-phase grid tied SPV- DSTATCOM system. IEEE Trans Ind Electron PP(99):1–10Google Scholar
  14. 14.
    Mahela OM, Shaik AG (2016) Power quality improvement in distribution network using DSTATCOM with battery energy storage system. Int J Electr Power Energy Syst 83:229–240CrossRefGoogle Scholar
  15. 15.
    Chidurala A, Saha TK, Mithulananthan N (2013) Power quality enhancement in unbalanced distribution network using Solar-DSTATCOM. In: Australasian universities power engineering conference, AUPEC 2013. Hobart, pp 1–6Google Scholar
  16. 16.
    Mallick RK, Sinha S, Mohanty S, Kumar S (2016) Design of optimal controller for DSTATCOM using differential evolution technique. In: International conference on electrical, electronics, and optimization techniques (ICEEOT). pp 1432–1437Google Scholar
  17. 17.
    Singh B, Jain C, Goel S (2014) ILST control algorithm of single-stage dual purpose grid connected solar PV system. IEEE Trans Power Electron 29(10):5347–5357CrossRefGoogle Scholar
  18. 18.
    Jain C, Singh B (2015) An offset reduction second order generalized integrator based control algorithm for single-phase S-DSTATCOM. In: 2015 39th National systems conference (NSC). pp 1–6Google Scholar
  19. 19.
    Ouchen S, Betka A, Abdeddaim S, Menadi A (2016) Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter. Energy Convers Manag 122:515–525CrossRefGoogle Scholar
  20. 20.
    Menniti D, Pinnarelli A, Sorrentino N (2010) An hybrid PV-wind supply system with D-Statcom interface for a water-lift station. In: 2010 international symposium on power electronics electrical drives automation and motion (SPEEDAM). pp 1387–1392Google Scholar
  21. 21.
    Samuel P, Gupta R, Chandra D (2009) Grid interface of photovoltaic-micro turbine hybrid based power for voltage support and control using VSI in rural applications. In: 2009 IEEE Power & energy society general meeting. pp 1–6Google Scholar
  22. 22.
    Senthilkumar A, Poongothai K, Selvakumar S, Silambarasan M (2015) Mitigation of harmonic distortion in microgrid system using adaptive neural learning algorithm based shunt active power filter. Procedia Technol 21:147–154CrossRefGoogle Scholar
  23. 23.
    Sangeetha B, Geetha K (2014) Performance of multilevel shunt active filter for smart grid applications. Int J Electr Power Energy Syst 63:927–932CrossRefGoogle Scholar
  24. 24.
    Kumar TP, Venkateshwarlu S (2017) Investigating the performance of PV interfaced PBT based DSTATCOM by adaptive fuzzy logic controller for reactive power management. In: 2017 11th international conference on intelligent systems and control (ISCO). Coimbatore, pp 160–165Google Scholar
  25. 25.
    Mishra S, Ray PK (2016) Power quality improvement using photovoltaic fed DSTATCOM based on JAYA optimization. IEEE Trans Sustain Energy 7(4):1672–1680CrossRefGoogle Scholar
  26. 26.
    Hussain I, Kandpal M, Singh B (2017) Grid integration of single stage SPV-STATCOM using cascaded 7-level VSC. Int J Electr Power Energy Syst 93:238–252CrossRefGoogle Scholar
  27. 27.
    Shivam S, Hussain I, Singh B (2016) Real-time implementation of SPV system with DSTATCOM capabilities in three-phase four-wire distribution system. IET Gener Transm Distrib 11(2):495–503CrossRefGoogle Scholar
  28. 28.
    Beniwal N, Hussain I, Singh B, Chandra A, Al-Haddad K (2016) Adaptive control scheme for three-phase four wire grid tied SPV system with DSTATCOM capabilities. In: 2016 National power systems conference (NPSC). Bhubaneswar, pp 1–6Google Scholar
  29. 29.
    Shivam S, Hussain I, Singh B (2016) Dual-sign error based adaptive control for three phase grid tied SECS with DSTATCOM capabilities. In: 2016 IEEE international conference on power electronics, drives and energy systems (PEDES). Trivandrum, pp 1–6Google Scholar
  30. 30.
    Ullah W, Mekhilef S, Seyedmahmoudian M, Horan B (2017) Active power filter (APF) for mitigation of power quality issues in grid integration of wind and photovoltaic energy conversion system. Renew Sustain Energy Rev 70:635–655CrossRefGoogle Scholar
  31. 31.
    Singh B, Arya SR, Dube SK, Chandra A, Al-Haddad K (2013) Implementation of DSTATCOM using neural network based radial basis function. In: 2013 IEEE industry applications society annual meeting. Lake Buena Vista, pp 1–8Google Scholar
  32. 32.
    Chang GW, Chen C-I, Teng Y-F (2010) Radial-basis-function-based neural network for harmonic detection. IEEE Trans Ind Electron 57(6):2171–2179CrossRefGoogle Scholar
  33. 33.
    Singh B, Arya SR (2014) Back-propagation control algorithm for power quality improvement using DSTATCOM. IEEE Trans Ind Electron 61(3):1204–1212CrossRefGoogle Scholar
  34. 34.
    Arya SR, Singh B (2013) Performance of DSTATCOM using leaky LMS control algorithm. IEEE J Emerg Sel Top Power Electron 1(2):104–113CrossRefGoogle Scholar
  35. 35.
    Emadi A, Nasiri A, Bekiarov SB (2005) Uninterruptible power supplies and active filters. CRC Press LLC, Boca RatonGoogle Scholar
  36. 36.
    Ewald FF, Mohammad ASM (2008) Power quality in power systems and electrical machines. Elsevier Academic Press, LondonGoogle Scholar
  37. 37.
    Singh B, Bhuvaneswari G, Arya SR (2012) Review on power quality solution technology. Asian Power Electron J 6(2):19–27Google Scholar
  38. 38.
    Singh B, Arya SR, Chandra A, Al-Haddad K (2012) Implementation of adaptive filter based control algorithm for distribution static compensator. In: 2012 IEEE industry applications society annual meeting. Las Vegas, pp 1–8Google Scholar
  39. 39.
    IEEE. IEEE Std 1531–2003 IEEE. Technical report (2003)Google Scholar
  40. 40.
    IEEE. IEC 61000-3-2:2018. Technical report (2018)Google Scholar
  41. 41.
    IEEE. IEEE Std 519–2014 (Revision of IEEE Std 519-1992). Technical report (2014)Google Scholar
  42. 42.
    Arya SR, Singh B (2014) Power quality improvement under nonideal AC mains in distribution system. Electr Power Syst Res 106:86–94CrossRefGoogle Scholar
  43. 43.
    Padiyar KR (2007) FACTS controllers in power transmission and distribution. New Age International (P) Limited, Publishers, New DelhiGoogle Scholar
  44. 44.
    Akagi H, Watanabe EH, Aredes M (2007) Instantaneous power theory and applications to power conditioning. Wiley, HobokenCrossRefGoogle Scholar
  45. 45.
    Rechka S, Ngandui E, Jianhong X, Sicard P (2003) Analysis of harmonic detection algorithms and their application to active power filters for harmonics compensation and resonance damping. Can J Electr Comput Eng 28(1):41–51CrossRefGoogle Scholar
  46. 46.
    Moreno-Munoz A (2007) Power quality mitigation technologies in a distributed environment. Springer, BerlinGoogle Scholar
  47. 47.
    Singh B, Jayaprakash P, Somayajulu TR, Kothari DP (2009) Reduced rating VSC with a zig-zag transformer for current compensation in a three-phase four-wire distribution system. IEEE Trans Power Deliv 24(1):249–259CrossRefGoogle Scholar
  48. 48.
    Singh B, Chandra A, Al-Haddad K (2015) Power quality: problems and mitigation techniques. Wiley, West SussexGoogle Scholar
  49. 49.
    Chen C-S, Lin C, Hsieh W-L, Hsu C-T, Te-tien K (2013) Enhancement of PV penetration with DSTATCOM in Taipower distribution system. IEEE Trans Power Syst 28(2):1560–1567CrossRefGoogle Scholar
  50. 50.
    Da Costa Teixeira C (2004) Power quality solutions for low and medium voltage critical loads. In: 2004 IEEE/PES transmision and distribution conference and exposition: Latin America (IEEE Cat. No. 04EX956). Sao Paulo, pp 326–331Google Scholar
  51. 51.
    Masand D, Jain S, Agnihotri G (2006) Control algorithms for distribution compensator. In: IEEE ISIE. Montreal, pp 1830–1834Google Scholar
  52. 52.
    El-Habrouk M, Darwish MK, Mehta P (2000) Active power filters: a review. IEE Proc Electr Power Appl 147(5):403–413CrossRefGoogle Scholar
  53. 53.
    Singh B, Al-Haddad K, Chandra A (1999) A review of active filters for power quality improvement. IEEE Trans Ind Electron 46(5):960–971CrossRefGoogle Scholar
  54. 54.
    Arya SR, Singh B, Chandra A, Al-Haddad K (2012). Control of shunt custom power device based on anti-hebbian learning algorithm. In: IECON proceedings (Industrial electronics conference). pp 1246–1251Google Scholar
  55. 55.
    Masand D, Jain S, Agnihotri G (2008) Control strategies for distribution static compensator for power quality improvement. IETE J Res 54(6):421–428CrossRefGoogle Scholar
  56. 56.
    Arya SR, Singh B (2014) Neural network based conductance estimation control algorithm for shunt compensation. IEEE Trans Ind Inform 10(1):569–577CrossRefGoogle Scholar
  57. 57.
    Bose BK (1994) Expert system, fuzzy logic, and neural network applications in power electronics and motion control. Proc IEEE 82(8):1303–1323CrossRefGoogle Scholar
  58. 58.
    Ahn H-S, Chen YQ, Moore KL (2007) Iterative learning control: brief survey and categorization. IEEE Trans Syst Man Cybern Part C: Appl Rev 37(6):1099–1121CrossRefGoogle Scholar
  59. 59.
    Baharudin NH, Mansur TMNT, Hassan SIS, Saad P, Ali R, Lada MY (2015) A comparison of distribution static synchronous compensator (DSTATCOM) control algorithms for harmonic elimination. ARPN J Eng Appl Sci 10(22)Google Scholar
  60. 60.
    Ying C, Qingsheng L (2009) New research on harmonic detection based on neural network for power system. In: 2009 Third international symposium on intelligent information technology application. Shanghai, pp 113–116Google Scholar
  61. 61.
    Jung I, Wang G (2007) Pattern classification of back-propagation algorithm using exclusive connecting network. World Acad Sci Eng Technol 1(12):180–184Google Scholar
  62. 62.
    Lu Y, Sundararajan N, Saratchandran P (1998) Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm. IEEE Trans Neural Netw 9(2):308–18CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Nor Hanisah Baharudin
    • 1
    Email author
  • Tunku Muhammad Nizar Tunku Mansur
    • 1
  • Rosnazri Ali
    • 1
  • Muhammad Irwanto Misrun
    • 1
  1. 1.School of Electrical System EngineeringUniversiti Malaysia Perlis (UniMAP)ArauMalaysia

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