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Active Power Control of Grid Tied SPV System with DSTATCOM Capabilities

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Published/Copyright: May 11, 2017

Abstract

This paper presents an active power control of SPV (Solar Photovoltaic) grid tied system with the DSTATCOM (Distribution Static Compensator) capabilities using recursive least square (RLS) control algorithm with IC (Incremental Conductance) maximum power point tracking. The system serves dual purpose of working as a SPV-DSTATCOM and DSTATCOM in presence and absence of solar power, respectively. The SPV-DSTACOM provides compensating currents along with active current component thus fulfilling active power demand of connected load and feeds active power to the grid along with improving the power quality. Moreover, when the solar power is not available during night or low solar irradiation conditions, the system works as a DSTATCOM providing compensating current which improves the power quality of the system during load unbalance, harmonics and reactive power. A RLS based adaptive algorithm is used to do these functions at good convergence than conventional LMS (Least Mean Square) algorithm. Thus, the proposed system is capable to meet peak power demand when the solar energy is available and it improves the system power quality during day and night. The system responses under varying conditions is demonstrated on s developed prototype.

Appendices

Experimental system parameters

SPV simulator OC voltage, VOCN = 230 V; SC current, ISCN = 16.6 A;power, PMPP = 3.12 kW; Vdc = 199.30 V;Interfacing inductor, Lf = 2.9 mH; DC Bus Capacitor, Cdc = 2350 μFPCC voltage, VLL = 129 V(rms) ;ripple filter, Cf = 10 µF and Rf = 5 Ω; sampling time, Ts = 30 µs; forgetting factor = 0.95; Kpd = 0.1 and Kid = 0.01; Nonlinear load= 0.716 kW.

References

1. Jager K, Isabella O, Smets AHM, Van Swaaij RACMM, Zeman M. Solar energy fundamentals, technology and systems. The Netherlands: Delft University of Technology, 2014.Search in Google Scholar

2. Vithayasrichareon P, MacGill IF. Valuing large-scale solar photovoltaics in future electricity generation portfolios and its implications for energy and climate policies. IET Renewable Power Generation. 2016;s(1):79–87.10.1049/iet-rpg.2015.0051Search in Google Scholar

3. Hussain I, Kandpal M, Singh B. Grid integration of single stage solar PV system using three-level voltage source converter. Int J Emerging Electric Power Syst. 2016;17(4):425–434.10.1515/ijeeps-2015-0222Search in Google Scholar

4. Agarwal R, Hussain I, Singh B. LMF based control algorithm for single-stage three-phase grid integrated solar PV system. IEEE Trans Sus Energy. 2016;7(4):1379–1387.10.1109/TSTE.2016.2553181Search in Google Scholar

5. Yang Y, Blaabjerg F, Wang H, Simões MG. Power control flexibilities for grid-connected multi-functional photovoltaic inverters. IET Renew Pow Gen. 2016;10(4):504–513.10.1049/iet-rpg.2015.0133Search in Google Scholar

6. Jain C, Singh B. Single-phase single-stage multifunctional grid interfaced solar photo-voltaic system under abnormal grid conditions. IET Gen Transm Distri. 2015;9(10):886–894.10.1049/iet-gtd.2014.0533Search in Google Scholar

7. Kumar Agarwal R, Hussain I, Singh B. Three-phase single-stage grid tied solar PV ECS using PLL-less fast CTF control technique. IET Power Electron. 2017;10(2):178–188 210.10.1049/iet-pel.2016.0067Search in Google Scholar

8. Wu TF, Chang CH, Lin LC, Kuo CL. Power loss comparison of single- and two-stage grid-connected photovoltaic systems. IEEE Trans Energy Convers. 2011;26(2):707–715.10.1109/TEC.2011.2123897Search in Google Scholar

9. Kish GJ, Lee JJ, Lehn PW. Modelling and control of photovoltaic panels utilising the incremental conductance method for maximum power point tracking. IET Renew Pow Gen. 2012;6(4):259–266.10.1049/iet-rpg.2011.0052Search in Google Scholar

10. Mohd Zainuri MAA, Mohd Radzi MA, Soh AC, Rahim NA. Development of adaptive perturb and observe-fuzzy control maximum power point tracking for photovoltaic boost dc-dc converter. IET Renew Pow Gen. 2014;8(2):183–194.10.1049/iet-rpg.2012.0362Search in Google Scholar

11. Sekhar PC, Mishra S. Takagi–Sugeno fuzzy-based incremental conductance algorithm for maximum power point tracking of a photovoltaic generating system. IET Renew Pow Gen. 2014;8(8):900–914.10.1049/iet-rpg.2013.0219Search in Google Scholar

12. Elobaid LM, Abdelsalam AK, Zakzouk EE. Artificial neural network-based photovoltaic maximum power point tracking techniques: A survey. IET Renew Pow Gen. 2015;9(8):1043–1063.10.1049/iet-rpg.2014.0359Search in Google Scholar

13. Hua CC, Fang YH, Chen WT. Hybrid maximum power point tracking method with variable step size for photovoltaic systems. IET Renew Pow Gen. 2016;10(2):127–132.10.1049/iet-rpg.2014.0403Search in Google Scholar

14. Singh B, Chandra A, Al-Haddad K. Power quality: Problems and mitigation techniques. United Kingdom: John Wiley & Sons Ltd., 2015 .10.1002/9781118922064Search in Google Scholar

15. Chidurala A, Kumar Saha T, Mithulananthan N. Harmonic impact of high penetration photovoltaic system on unbalanced distribution networks – learning from an urban photovoltaic network. IET Renew Pow Gen. 2016;10(4):485–494.10.1049/iet-rpg.2015.0188Search in Google Scholar

16. Pompodakis EE, Drougakis IA, Lelis IS, Alexiadis MC. Photovoltaic systems in low-voltage networks and overvoltage correction with reactive power control. IET Renew Pow Gen. 2016;10(3):410–417.10.1049/iet-rpg.2014.0282Search in Google Scholar

17. Badoni M, Singh A, Singh B. Variable forgetting factor recursive least square control algorithm for DSTATCOM. IEEE Trans Pow Deli. 2015;30(5):2353–2361.10.1109/TPWRD.2015.2422139Search in Google Scholar

18. Singh B, Arya SR. Adaptive control of four-leg VSC based DSTATCOM in distribution system. Int J Emerging Electric Power Syst. 2014;15(1):93–99.10.1515/ijeeps-2013-0145Search in Google Scholar

19. Panigrahi R, Subudhi B, Panda PC. A robust LQG servo control strategy of shunt-active power filter for power quality enhancement. IEEE Trans Pow Electron. 2016;31(4):2860–2869.10.1109/TPEL.2015.2456155Search in Google Scholar

20. Srinivas M, Hussain I, Singh B. Combined LMS–LMF-based control algorithm of DSTATCOM for power quality enhancement in distribution system. IEEE Trans Ind Electron. 2016;63(7):4160–4168.10.1109/TIE.2016.2532278Search in Google Scholar

21. Kumar S, Verma AK, Hussain I, Singh B, Jain C. Better control for a solar energy system: using improved enhanced phase-locked loop-based control under variable solar intensity. IEEE Ind Appl Magazine. 2017;23(2):24–36.10.1109/MIAS.2016.2600730Search in Google Scholar

22. Sahoo PK, Ray PK, Das P. Power quality improvement of single phase grid connected photovoltaic system. Int J Emerging Electric Power Syst. 2017;18(1):1–9.10.1515/ijeeps-2016-0097Search in Google Scholar

23. Agarwal RK, Hussain I, Singh B. Three-phase grid-tied single-stage solar energy conversion system using LLMS control algorithm. IET Renewable Power Generation. 2016;10(10):1638–1646.10.1049/iet-rpg.2016.0061Search in Google Scholar

24. IEEE recommended practices and requirement for harmonic control on electric power system. IEEE Std.519. 1992.Search in Google Scholar

25. IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Std. 1547. 2003.Search in Google Scholar

26. Haykin S. Neural networks and learning machines, 3rd ed. New Jersey: Pearson Education, 2009.Search in Google Scholar

27. Villalva MG, Gazoli JR, Filho ER. Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Trans Pow Elec. 2009;24(5):1198–1208.10.1109/TPEL.2009.2013862Search in Google Scholar

28. Akagi H, Watanabe E. H, Aredes M. Instantaneous power theory and applications to power conditioning 2007 Wiley-IEEE Press.10.1002/0470118938Search in Google Scholar

Received: 2016-9-27
Revised: 2017-4-11
Accepted: 2017-4-25
Published Online: 2017-5-11

© 2017 Walter de Gruyter GmbH, Berlin/Boston

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