Please wait a minute...
Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

Postal Subscription Code 80-972

2018 Impact Factor: 1.701

Front. Energy    2014, Vol. 8 Issue (4) : 464-479    https://doi.org/10.1007/s11708-014-0307-9
RESEARCH ARTICLE
THD reduction with reactive power compensation for fuzzy logic DVR based solar PV grid connected system
Akhil GUPTA1(), Saurabh CHANANA1, Tilak THAKUR2
1. Department of Electrical Engineering, National Institute of Technology, Kurukshetra 136119, India
2. Department of Electrical Engineering, PEC University of Technology, Chandigarh 160012, India
 Download: PDF(2575 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Dynamic voltage restorer (DVR) is used to protect sensitive loads from voltage disturbances of the distribution generation (DG) system. In this paper, a new control approach for the 200 kW solar photovoltaic grid connected system with perturb and observe maximum power point tracking (MPPT) technique is implemented. Power quality improvement with comparison is conducted during fault with proportional integral (PI) and artificial intelligence-based fuzzy logic controlled DVR. MPPT tracks the actual variable DC link voltage while deriving the maximum power from a photovoltaic array and maintains DC link voltage constant by changing modulation index of the converter. Simulation results during fault show that the fuzzy logic based DVR scheme demonstrates simultaneous exchange of active and reactive power with less total harmonic distortion (THD) present in voltage source converter (VSC) current and grid current with fast tracking of optimum operating point at unity power factor. Standards (IEEE-519/1547), stipulates that the current with THD greater than 5% cannot be injected into the grid by any distributed generation source. Simulation results and validations of MPPT technique and operation of fuzzy logic controlled DVR demonstrate the effectiveness of the proposed control schemes.

Keywords fuzzy logic      maximum power point tracking (MPPT)      proportional integral (PI)      control      voltage restorer     
Corresponding Author(s): Akhil GUPTA   
Online First Date: 04 July 2014    Issue Date: 09 January 2015
 Cite this article:   
Akhil GUPTA,Saurabh CHANANA,Tilak THAKUR. THD reduction with reactive power compensation for fuzzy logic DVR based solar PV grid connected system[J]. Front. Energy, 2014, 8(4): 464-479.
 URL:  
https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0307-9
https://academic.hep.com.cn/fie/EN/Y2014/V8/I4/464
Fig.1  Simulation model of the solar PV array connected to the grid through three-phase inverter
Fig.2  P-V and V-I curves obtained from simulations by using one of the two 100?kW solar PV arrays
Fig.3  Ramp up-down solar radiation intensity used, for 100?kW Sunpower SPR-305-WHT solar PV model under variable environmental conditions
System name (components) Rating values
No. of solar cells per module 96
No. of series connected modules per string 5
No. of parallel strings 66
Module specifications under STC [ Voc, Isc, Vmp, Imp] [64.2?V, 5.96?A, 54.7?V, 5.58?A]
Model parameters for one module [ Rs, Rp, Isat, Iph, Qd ] [0.038?Ω, 993.5?Ω, 1.1753e-008 A, 5.9602 A, 1.3]
Maximum power Pmp 66 × 5 × 54.7 × 5.58 = 100.7?kW
Tab.1  Specifications adopted for one solar PV array (SunPower SPR-305-WHT)
System name (components) Rating values
3-Ф Transformer nominal power and frequency [ 202?kVA, 50?Hz ]
Utility grid components Length of two 3-Ф transmission lines 4.5?km and 13.5?km
3-Ф series RLC load [Vn, P] [25?kV,2.20?MW]
3-Ф series RLC load [Vn, P, + Ql] [25?kV, 28?MW, + 2.2 MVAR]
3-Ф Transformer nominal power and frequency [47?MVA, 50?Hz ]
Grounding transformer nominal power and frequency [100?MVA, 50?Hz ]
A 3-Ф programmable voltage source 120?kV (phase to phase)
X/R ratio 7
Base voltage 120?kV
3-Ф short circuit level at base voltage 2500?MVA
Tab.2  Specifications adopted for transformer and utility grid
System name (components) Rating values
Nominal DC voltage 100?V
Nominal power and frequency [200?kW, 50?Hz ]
DC voltage regulator gains [ Kp, Ki ] [7, 800]
Current regulator gains [ Kp, Ki ] [0.3, 20]
CL filter [C, L] [1500?µF (with R = 1?mΩ), 1500?mH (with R = 1?Ω),]
Load [Vn, P, − Qc] [260?V, 20?kW, − 20?kVAR]
Tab.3  Specifications adopted for controller to average based VSC, CL, and connected load
Fig.4  General scheme of a 200?kW solar PV energy conversion system connected to utility grid distribution system
Fig.5  Flowchart of VSC control with feed-forward current controller
Fig.6  Block diagram of PI and fuzzy logic controlled dynamic voltage restorer
Fig.7  Block diagram of FLC
Fig.8  Membership function of error, change of error and output pulse to PWM (defuzzified value)

(a) Error E; (b) change of error dE; (c) output pulse to PWM (defuzzified value)

PI controlled DVR (DC current component in A) Fuzzy logic controlled DVR (DC current component in A)
VSC current 3.43 % (0.9858) 3.44 % (0.9673)
Load current 1.33 % (0.5343) 1.34 % (0.558)
Grid current 0.61 % (0.006872) 0.58 % (0.006267)
Tab.4  THD analysis of VSC current, load current and grid current (with DC current component)
Fig.9  Without DVR control from 3-Ф VSC, connected load and grid with P&O MPPT control during fault
Fig.10  Without DVR control uncompensated 3-Ф discrete output voltage from VSC and 3-Фgrid voltage with P&O MPPT control during fault
Fig.11  Without DVR control uncompensated 3-Ф discrete output current from VSC and 3-Ø current injected into grid with P&O MPPT control during fault
Fig.12  Active power output waveforms from 3-Ф VSC, connected load and grid for
Fig.13  Reactive power output waveforms from 3-Ф VSC, connected load and grid for
Fig.14  Compensated waveforms using fuzzy logic controlled DVR during fault
Fig.15  Compensated waveforms using fuzzy logic controlled DVR during fault
Fig.16  Comparison in actual dc link voltage to VSC and reference voltage during fault for
1 M G Villalva, T G de Siqueira, E Ruppert. Voltage regulation of photovoltaic arrays: small-signal analysis and control design. IET Power Electronics, 2010, 3(6): 869−880
https://doi.org/10.1049/iet-pel.2008.0344
2 M G Villalva, E Ruppert. Dynamic analysis of the input-controlled buck converter fed by a photovoltaic array. Brazilian Journal of Control and Automation, 2008, 19(4): 463−474
3 M E Ropp, S Gonzalez. Development of a MATLAB/Simulink model of a single-phase grid-connected photovoltaic system. IEEE Transactions on Energy Conversion, 2009, 24(1): 195−202
https://doi.org/10.1109/TEC.2008.2003206
4 G R Walker, P C Sernia. Cascaded dc-dc converter connection of photovoltaic modules. IEEE Transactions on Power Electronics, 2004, 19(4): 1130−1139
https://doi.org/10.1109/TPEL.2004.830090
5 T Y Kim, H G Ahn, S K Park, Y K Lee. A novel maximum power point tracking control for photovoltaic power system under rapidly changing solar radiation. In: Proceedings of IEEE International Symposium on Industrial Electronics. Pusan, Korea, 2001, 1011−1014
6 C Srisailam, A Sreenivas. Mitigation of voltage sags/swells by dynamic voltage restorer using PI and fuzzy logic controller. International Journal of Engineering Research and Applications, 2002, 2(4): 1733−1737
7 N G Hingorani. Introducing custom power. IEEE Spectrum, 1995, 32(6): 41−48
https://doi.org/10.1109/6.387140
8 A R Dash, B C Babu, K B Mohanty, R Dubey. Analysis of PI and PR controllers for distributed power generation system under unbalanced grid faults. In: Proceedings of 2011 International Conference on Power and Energy Systems. Chennai, India, 2011, 1−6
9 R Niemi, P D Lund. Alternative ways for voltage control in smart grids with distributed electricity generation. International Journal of Energy Research, 2011, 36(10): 1032−1043
https://doi.org/10.1002/er.1865
10 R G Wandhare, V Agarwa. A novel technique for THD control in grid connected photovoltaic systems using step variable inductor approach. In: Proceedings of 35th IEEE Photovoltaic Specialists Conference. Honolulu, USA, 2010, 844−848
11 R K Varma, V Khadkikar, R Seethapathy. Nighttime application of PV solar farm as STATCOM to regulate grid voltage. IEEE Transactions on Energy Conversion, 2009, 24(4): 983−985
https://doi.org/10.1109/TEC.2009.2031814
12 H Ezoji, A Sheikholeslami, M Rezanezhad, H Livani. A new control method for dynamic voltage restorer with asymmetrical inverter legs based on fuzzy logic controller. Simulation Modelling Practice and Theory, 2010, 18(6): 806−819
https://doi.org/10.1016/j.simpat.2010.01.017
13 C Nagarajan, M Madheswaran. Performance analysis of LCL-T resonant converter with fuzzy/PID controller using state space analysis. Electrical Engineering, 2011, 93(3): 167−178
https://doi.org/10.1007/s00202-011-0203-9
14 V Raj, M Sudhakaran, S S Kumar, S R Roy, T G Palanivelu. Multi level inverter based dynamic voltage restorer with PI and fuzzy logic controller. In: 32nd National Systems Conference. IIT Roorkee, India, 2008, 65−70.
15 The Mathworks. MATLAB/SIMULINK, Inc. 7.10.0.499 (R2010a). 2016-06
16 S W Lee, J H Kim, S R Lee, B K Lee, C Y Won. A transformer-less grid-connected photovoltaic system with active and reactive power control. In: Proceedings of the 6th IEEE International Power Electronics and Motion Control Conference. Wuhan, China, 2009, 2178−2181
17 A Gupta, S Chanana, T Thakur. Power quality improvement of solar pv transformer-less grid connected system with maximum power point tracking control. International Journal of Sustainable Energy, 2013, 33(4): 921−936
https://doi.org/10.1080/14786451.2013.790034
18 M G Molina, L E Juanicó, G F Rinalde, E Taglialavore, S Gortari. Design of improved controller for thermoelectric generator used in distributed generation. International Journal of Hydrogen Energy, 2010, 35(11): 5968−5973
https://doi.org/10.1016/j.ijhydene.2009.12.098
19 S Gomathy, S Saravanan, S Thangavel. Design and implementation of maximum power point tracking (MPPT) algorithm for a standalone PV system. International Journal of Scientific & Engineering Research, 2012, 3(3): 1−7
20 T Esram, P L Chapman. Comparison of PV array maximum power point tracking techniques. IEEE Transactions on Energy Conversion, 2007, 22(2): 439−449
https://doi.org/10.1109/TEC.2006.874230
21 N Mohan, T M Undeland. Power Electronics: Converters, Applications, and Design. New York: John Wiley & Sons, 1995
22 M F Ansari, S Chatterji, A Iqbal. A fuzzy logic control scheme for a solar photovoltaic system for a maximum power point tracker. International Journal of Sustainable Energy, 2010, 29(4): 245−255
https://doi.org/10.1080/14786461003802118
23 R F Coelho, F M Concer, D C Martins. A MPPT approach based on temperature measurements applied in PV systems. In: Proceedings of the 9th IEEE/IAS International Conference on Industry Applications. Sao Paulo, Brazil, 2010, 1−6
24 M G Molina, L E Juanico. Dynamic modeling and control design of advanced PV solar system for distributed generation applications. Journal of Electrical Engineering: Theory and Applications, 2010, 1(3): 141−150
25 H Moin. Investigation to improve the control and operation of a three-phase PV grid tie inverter. Dissertation for the Doctoral Degree. Dublin Institute of Technology, 2011
26 S V R Kumar, S S Nagaraju. Simulation of D-STATCOM and DVR in power systems. ARPN Journal of Engineering and Applied Sciences, 2007, 2(3): 7−13
27 M R Azim, M A Hoque. A fuzzy logic based dynamic voltage restorer for voltage sag and swell mitigation for industrial induction motor loads. International Journal of Computers and Applications, 2011, 30(8): 9−18
https://doi.org/10.5120/3672-5120
28 B Ferdi, C Benachaiba, B Berbaoui, R Dehini. STATCOM DC-link fuzzy controller for power factor correction. Journal of Acta Electrotechnica, 2011, 52(4): 173−178
29 I H Altas, A M Sharaf. A fuzzy logic power tracking controller for a photovoltaic energy conversion scheme. Electric Power Systems Research, 1992, 25(3): 227−238
https://doi.org/10.1016/0378-7796(92)90022-S
30 K M Tsang, W L Chan. Three-level grid-connected photovoltaic inverter with maximum power point tracking. Energy Conversion and Management, 2013, 65: 221−227
https://doi.org/10.1016/j.enconman.2012.08.008
31 A J Mahdi, W H Tang, Q H Wu. Improvement of a MPPT algorithm for PV systems and its experimental validation. In: Proceedings of International Conference on Renewable Energies and Power Quality (ICREPQ). Granada, Spain, 2010, 1−6
32 D Menniti, A Pinnarelli. A novel compensation approach for DC current component in a grid-connected photovoltaic generation system. In: Proceedings of IEEE International Conference on Power and Energy Society General Meeting. San Diego, USA, 2012
[1] Dorota RZETELSKA, Madeleine COMBRINCK. Fuel poverty and low carbon emissions: a comparative study of the feasibility of the hybrid renewable energy systems incorporating combined heat and power technology[J]. Front. Energy, 2022, 16(2): 336-356.
[2] Meng SONG, Wei SUN. Applications of thermostatically controlled loads for demand response with the proliferation of variable renewable energy[J]. Front. Energy, 2022, 16(1): 64-73.
[3] Hao LUO, Mancang LI, Shanfang HUANG, Minyun LIU, Kan WANG. Optimization of spatial structure designs of control rod using Monte Carlo code RMC[J]. Front. Energy, 2021, 15(4): 974-983.
[4] Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI. MPC-based interval number optimization for electric water heater scheduling in uncertain environments[J]. Front. Energy, 2021, 15(1): 186-200.
[5] Abdelkarim AMMAR, Amor BOUREK, Abdelhamid BENAKCHA. Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer[J]. Front. Energy, 2020, 14(4): 836-849.
[6] Xiaojing LV, Weilun ZENG, Xiaoyi DING, Yiwu WENG, Shilie WENG. Experimental investigation of a novel micro gas turbine with flexible switching function for distributed power system[J]. Front. Energy, 2020, 14(4): 790-800.
[7] Mujahid TABASSUM, Manas K. HALDAR, Duaa Fatima S. KHAN. Implementation and performance evaluation of advance metering infrastructure for Borneo-Wide Power Grid[J]. Front. Energy, 2020, 14(1): 192-211.
[8] Ridha CHEIKH, Arezki MENACER, L. CHRIFI-ALAOUI, Said DRID. Robust nonlinear control via feedback linearization and Lyapunov theory for permanent magnet synchronous generator-based wind energy conversion system[J]. Front. Energy, 2020, 14(1): 180-191.
[9] Ali EL YAAKOUBI, Kamal ATTARI, Adel ASSELMAN, Abdelouahed DJEBLI. Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG[J]. Front. Energy, 2019, 13(4): 742-756.
[10] P. PADMAGIRISAN, V. SANKARANARAYANAN. Powertrain control of a solar photovoltaic-battery powered hybrid electric vehicle[J]. Front. Energy, 2019, 13(2): 296-306.
[11] Weiliang WANG, Bo LI, Xuan YAO, Junfu LYU, Weidou NI. Air pollutant control and strategy in coal-fired power industry for promotion of China’s emission reduction[J]. Front. Energy, 2019, 13(2): 307-316.
[12] Alireza REZVANI, Ali ESMAEILY, Hasan ETAATI, Mohammad MOHAMMADINODOUSHAN. Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode[J]. Front. Energy, 2019, 13(1): 131-148.
[13] Yufei YUE, Qianming XU, Peng GUO, An LUO. Constant temperature control of tundish induction heating power supply for metallurgical manufacturing[J]. Front. Energy, 2019, 13(1): 16-26.
[14] Qiaowan CHANG, Yuan XU, Shangqian ZHU, Fei XIAO, Minhua SHAO. Pt-Ni nanourchins as electrocatalysts for oxygen reduction reaction[J]. Front. Energy, 2017, 11(3): 254-259.
[15] T A BINSHAD,K VIJAYAKUMAR,M KALEESWARI. PV based water pumping system for agricultural irrigation[J]. Front. Energy, 2016, 10(3): 319-328.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed