Contenu connexe
Similaire à Anfis controller for solar powered cascade multilevel inverter 2
Similaire à Anfis controller for solar powered cascade multilevel inverter 2 (20)
Plus de IAEME Publication
Plus de IAEME Publication (20)
Anfis controller for solar powered cascade multilevel inverter 2
- 1. INTERNATIONAL Issue 3, October – December (2012), © IAEME 0976 – 6545(Print), ISSN
International Journal of Electrical Engineering and Technology (IJEET), ISSN
0976 – 6553(Online) Volume 3,
JOURNAL OF ELECTRICAL ENGINEERING
& TECHNOLOGY (IJEET)
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
Volume 3, Issue 3, October - December (2012), pp. 234-240
© IAEME: www.iaeme.com/ijeet.asp IJEET
Journal Impact Factor (2012): 3.2031 (Calculated by GISI)
www.jifactor.com ©IAEME
ANFIS CONTROLLER FOR SOLAR POWERED
CASCADE MULTILEVEL INVERTER
Shimi S.L. #1 , Dr. Thilak Thakur #2, Dr. Jagdish Kumar#3 ,
Dr. S Chatterji#4, Dnyaneshwar Karanjkar #5
#1, #3
Assistant Professor, #2Associate Professor, , #4Professor & Head,#5 Research scholar,
#1, #4, #5
Electrical Engineering Department, NITTTR, Chandigarh
#2, #3
Electrical Engineering Department ,PEC University of Technology, Chandigarh
E-mail: #1shimi.reji@gmail.com, #2 tilak20042005@yahoo.co.in, #3 jk_bishnoi@yahoo.com,
#4
chatterjis@yahoo.com,#5dskaranjkar@rediffmail.com
ABSTRACT
This paper deals with the design and simulation of solar powered cascaded H-bridge
multilevel inverter. ANFIS based controller switching scheme is used to improve the power
quality thus to reduce the Total Harmonic Distortion (THD)of the system . The system
performance using ANFIS based controller are evaluated by means of MATLAB/SIMULINK
simulations and the results in terms of THD are simulate and compared with the conventional
controller.
Index Terms: Adaptive Neuro Fuzzy Inference System (ANFIS), Solar Powered Multilevel
Inverter ,Total Harmonic Distortion (THD).
I. INTRODUCTION
Power quality is the major issue in the energy sector. The nonlinear electronic
equipments connected in the network produce undesired harmonics components and results
in poor power quality thus deteriorating the efficiency and performance of the system. To
overcome these snag many different solutions have been proposed in literature. The
multilevel converters are gaining high reputation because of their better efficiency and output
waveforms over other standard two level pulse width modulated (PWM) converters [1], [2],
[4], [5]. One of the major advantage of multilevel inverter is that even in high power
application it is flexible to interface the renewable energy sources such as PV arrays,
wind, and fuel cells in the dc input portion of the multilevel inverter [3, 4]. Multilevel
converters have received more and more attention because of their capability of high voltage
operation, high efficiency, and low electromagnetic interference (EMI) [5][3].
234
- 2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
The multilevel inverters use large number of power semiconductor devices for their
switching thus results in more switching losses and is less reliable. But the industrial
applications such as industrial manufacturing are more dependent on induction motors and
their inverter systems for process control. The IEEE 519 standard limits of THD of the
output voltage of the converter circuit should be maintained for such applications [6]. In
industries the harmonics mitigation of multilevel inverter circuit is a very important issue. In
[7-9] the investigators have proposed the elimination theory to determine the switching
patterns to eliminate the specific harmonics, such as 5th, 7th, 11th, and the 13th. In case of 3
phase 11 level multilevel inverter there are 15 dc sources, as the number of dc sources
increases the degrees of the polynomials in these equations increases and thus it becomes
difficult to solve such a problem. The methods to solve such polynomial equations using
elimination theory are discussed in [10]. The solar powered multilevel inverter introduces a
lot of harmonics. In this paper an ANFIS based switching scheme is used for harmonic
elimination. The knowledge of harmonic elimination for multilevel inverter is very necessary
as it gives an idea about the switching pattern for harmonic elimination in case of 11 level
cascade multilevel inverter [11].
II. MULTILEVEL INVERTER DRIVES (MLIDS)
In industrial drives the conventional inverter drives are most commonly used. They
consist of six power switches with pulse width modulation (PWM) switching. By using such
conventional converters the output voltage and current waveform qualities has deteriorated.
To overcome this problem and improve the waveform quality the switching frequency
should be increased, but this result in higher switching losses. As the number of levels of
multilevel inverter is increased the output staircase waveform is more close to a sine wave
thus very low distortion is produced in the output.
Fig. 1 Single-phase structure of a mulitlevel cascaded inverter
The investigator of [3] has mainly discussed the cascade MLID and back-to-back diode-
clamped converter topologies of multilevel inverters for electric drive application. The
235
- 3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
cascaded multilevel inverter drive is the main focus of this paper. The Fig. 1 shows the
single-phase structure of a multilevel cascaded inverter.
4ܸ
∞
ܸ ሺݐݓሻ ൌ ሺ ሺcosሺ݊ߠଵ ሻ cosሺ݊ߠଶ ሻ cosሺ݊ߠଷ ሻ cosሺ݊ߠସ ሻ
ߨ݊
ୀଵ,ହ,,ଵଵ,ଵଷ
cosሺ݊ߠହ ሻሻ … … ሺ1ሻ
III. PV MODELING
Modeling of a solar cell is done by connecting a current source in parallel with an
inverted diode along with a series and a parallel resistance as shown in Fig.2. The series
resistance is due to hindrance in the path of flow of electrons from n to p junction and parallel
resistance is due to the leakage current. The single diode model shown in Fig. 2 [13] was
adopted for simulating the PV module under different irradiance and temperature levels. The
modeling of the PV cell was done in MATLAB/SIMULINK by writing the code in the
embedded block. The PV cell subsystems were modeled and connected to the 11 level
cascade multilevel inverter.
Rs I
+
Rs V
_
Fig. 2 Single diode model of a PV cell
In literature a number of approaches and models were found to analyze the behavior of PVs
[14-16].
The PV cell model used in this work is based on the single diode cell. The VI characteristics
( in green) of a typical solar cell are as shown in the Fig. 3.
3. 1.
PMPP
3 1.
IMPP
Cell current in A
2. MPP 1
Cell power in
2 0.
1. 0.
1 0.
0. 0.
Vo
0 0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Cell voltage in V
Fig. 3 V-I and P-V characteristics curve of photovoltaic cell
236
- 4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
When the voltage and the current characteristics are multiplied we get the P-V characteristics
(in blue) as shown in Fig. 4. The point highlighted as MPP is the point at which the panel
power output is maximum [17]. The equation (2) is the basic equation for the photovoltaic
current.
ೇశೃೞ
ାோೞ ூ
ܫൌ ܫ௩ െ ܫ ݁ ೇ ೌ െ1െ ோು
…………………(2)
Where,
Ipv : photovoltaic current
I0 : saturation current
Vt : thermal voltage
Rs : equivalent series resistance
Rp : equivalent parallel resistance
a : diode ideality constant
IV. ANFIS (ADAPTIVE NEURO FUZZY INFERENCE SYSTEM)
Intelligent control is the viable alternative to conventional control schemes. The
uncertain or unknown variations in plant parameters can be dealt more effectively by using
artificial intelligent techniques such as fuzzy logic and neural network. Hence the robustness
of the control system can be improved. The multilayer feed forward network has nodes which
performs a particular function on incoming signals. Each node has different formula. The
links in the adaptive network just indicate the signal flow direction [18, 19].
V. PROPOSED DESIGN
In this proposed method of the solar powered 11 level cascade multilevel inverter, has
five input stages, all the five stages are alike in the construction module. All the modules
consist of GTO’s as power switches.
Fig. 4 Block Diagram of the proposed system
The modulation index at the output of 11 level cascade multilevel inverter is calculated and is
given as input to the ANFIS controller. The ANFIS controller chooses the optimized firing
angles 1, 2, 3, 4 and 5 and fires the 11 level cascade multilevel inverter.
237
- 5. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
VI. SIMULATED CIRCUITS AND WAVEFORMS
The subsystem of the solar powered 11 level cascade multilevel inverter is shown in
Fig 5. The FFT spectrum of the line voltage is found using the FFT analysis tool. The FFT
spectrum of a conventional controller and ANFIS controller are shown in Fig 6 and Fig 7
respectively. The total harmonic distortion of a conventional controller is found to be 8.51 %
and that of an ANFIS controller is found to be 4.51 %.
Fig. 5 Subsystem of the solar powered 11 level cascade multilevel inverter
Fig.6 FFT spectrum of conventional Fig.7 FFT spectrum of ANFIS controller
controller
238
- 6. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
VII. CONCLUSION
A three-phase solar powered 11 level cascade inverter has been proposed. The PV cell
modeling was performed and the dc supply for all the H-bridges were supplied through the
PV cells. The ANFIS based switching scheme is used to fire the GTOs of multilevel inverter
for reducing the Total Harmonic Distortion (THD) and to improve the power quality of the
supply voltage and current. The total harmonic distortion of a conventional controller is
found to be 8.51 % and that of an ANFIS controller is found to be 4.51 %.
REFERENCES
[1] Carlo Cecati, Fabrizio Ciancetta, “A Multilevel Inverter for Renewables with Fuzzy
Logic-based Control”, IEEE Conference Publication, International Conference on Clean
Electrical Power, 9-11 June 2009, Page(s): 227 - 231.
[2] L.G. FRANQUELO, J. RODRIGUEZ, J. I. LEON, S. KOUKO, R. PORTILLO, M. A.M. PRATS, “THE
AGE OF MULTILEVEL CONVERTERS ARRIVES”, IEEE INDUSTRIAL ELECTRONICS MAGAZINE,
JUNE 2008, PP. 28-39.
[3] L.M. Tolbert, F. Z. Peng, T. G. Habetler, “Multilevel Converters for Large Electric
Drives, ” IEEE Transactions on Industry Applications, vol. 35, no. 1, Jan./Feb. 1999, pp. 36-
44.
[4] J. Rodriguez, J. S. Lai, and F. Z. Peng, “Multilevel Inverters: Survey of Topologies,
Controls, and Applications,” IEEE Transactions on Industry Applications, vol. 49, no. 4,
Aug. 2002, pp. 724-738.
[5] J. S. Lai and F. Z. Peng, “Multilevel Converters – A New Breed of Power Converters,”
IEEE Transactions on Industry Applications, vol. 32, no. 3, May /June 1996, pp. 509-517.
[6] C. K. Duffey and R. P. Stratford, “Update of Harmonic Standard IEEE-519: IEEE
Recommended Practices and Requirements for Harmonic Control in Electric Power
Systems,” IEEE Transactions on Industry Applications, vol. 25, no. 6, Nov./Dec. 1989, pp.
1025-1034.
[7] H. S. Patel and R. G. Hoft, “Generalized Harmonic Elimination and Voltage Control in
Thyristor Inverters: Part I –Harmonic Elimination,” IEEE Transactions on Industry
Applications, vol. 9, May/June 1973, pp. 310-317.
[8] H. S. Patel and R. G. Hoft, “Generalized Harmonic Elimination and Voltage Control in
Thyristor Inverters: Part II –Voltage Control Technique,” IEEE Transactions on Industry
Applications, vol. 10, Sept./Oct. 1974, pp. 666-673.
[9] P. N. Enjeti, P. D. Ziogas, J. F. Lindsay, “Programmed PWM Techniques to Eliminate
Harmonics: A Critical Evaluation” IEEE Transactions on Industry Applications, vol. 26, no.
2, March/April. 1990. pp. 302 – 316.
[10] J. N. Chiasson, L. M. Tolbert, K. J. McKenzie, Z. Du, “A New approach to solving the
harmonic elimination equations for a multilevel converter,” IEEE Industry Applications
Society Annual Meeting, October 12-16, 2003, Salt Lake City, Utah, pp. 640-645.
[11] T. Sripal Reddy, Dr. B.V.Sanker Ram, Dr. K. Raghu Ram “The Simulation And
Analysis Of Multilevel Inverter Fed Induction Motor Drive”, International Institute of
Engineering and Technology Reserch Center, Vol No. 1, Issue No. 1, pp 043-049,2011.
[12] E. Cengelci, S. U. Sulistijo, B. O. Woom, P. Enjeti, R. Teodorescu, and F. Blaabjerg,
“A New Medium Voltage PWM Inverter Topology for Adjustable Speed Drives,” in Conf.
Rec. IEEE-IAS Annual Meeting, St. Louis, MO, Oct. 1998, pp. 1416-1423.
[13] F. Filho, L. M. Tolbert, B. Ozpineci, Y. Cao, "Real Time Selective Harmonic
Minimization for Multilevel Inverters Connected to Solar Panels Using Artificial Neural
239
- 7. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN
0976 – 6553(Online) Volume 3, Issue 3, October – December (2012), © IAEME
Network Angle Generation," IEEE Transactions on Industry Applications, vol. 47, no. 5,
Sept.-Oct. 2011, pp. 2117-2124
[14] U. Boke, “A simple model of photovoltaic module electric characteristics,” European
Conference on Power Electronics and Applications, pp.1-8,Sept. 2007.
[15] O. Gil-Arias, E. I. Ortiz-Rivera, “A general purpose tool for simulating the behavior of
PV solar cells, modules and arrays,” 11th Workshop on Control and Modeling for Power
Electronics, pp. 1-5, Aug. 2008.
[16] R. Ramaprabha, B. L. Mathur, “MATLAB based modelling to study the influence of
shading on series connected SPVA,” 2nd International Conference on Emerging Trends in
Engineering and Technology, pp. 30-34, Dec. 2009.
[17] Marcelo G, Gazoli J. and Filho E., “Comprehensive Approach to Modeling and
Simulation of Photovoltaic Arrays”, IEEE Transactions On Power Electronics, vol. 24, no. 5,
May 2009, p.p.1198-1208.
[18] Mouloud A. Denai, Frank Palis, Abdelhafid Zeghbeb, ” ANFIS Based Modelling
and Control of Non-Linear Systems: A Tutorial ”,IEEE International Conference
on Systems, Man and Cybernetics, 2004.
[19] J. S. R. Jang,”ANFIS: Adaptive Network-Based-Fuzzy Inference System”, IEEE
Transactions On Systems, Man And Cybernetics, VOL. 23, No. 3,May/June,1993.
[20] A.Selwin Mich Priyadharson and Dr.T.R.Rangaswamy, “Cascaded Fuzzy Controller
Scheme For Combustion Control Of A Utility Boiler Using Control Balance Model”
International Journal of Electrical Engineering & Technology (IJEET), Volume 2, Issue 2,
2011, pp. 42 - 53, Published by IAEME.
[21] Sweeka Meshram, Ganga Agnihotri and Sushma Gupta, “A Modern Two Dof Controller
For Grid Integration With Solar Power Generator” International Journal of Electrical
Engineering & Technology (IJEET), Volume 3, Issue 3, 2012, pp. 164 - 174, Published by
IAEME.
[22] Ganni Gowtham , Ksitij Kumar , S.S Charan and K Manivannan, “Experimental
Analysis Of Solar Powered Ventilation Coupled With Thermo Electric Generator On
Unroofed Parked Vehicles” International Journal of Mechanical Engineering & Technology
(IJMET), Volume3, Issue3, 2012, pp. 471 - 482, Published by IAEME.
[23] M.S.Sujatha, Manoj Kumar.N and Dr M. Vijay Kumar, “Under Frequency Load
Shedding For Reduction Of Energy Loss Using By Adaptive Neuro Fuzzy Technique”
International journal of Computer Engineering & Technology (IJCET), Volume3, Issue2,
2012, pp. 389 - 398, Published by IAEME
240