Control of Grid-tied solar photovoltaic power using quasi z-source inverter and MPC- MPPT algorithm

CONTROL OF GRID- TIED SOLAR PHOTOVOLTAIC
POWER USING QUASI – Z – SOURCE INVERTER AND
MPC-MPPT ALGORITHM
P R E S E N T E D B Y,
S.RAJESH KUMAR - 412414105062
S.SASIDHARAN - 412414105073
S.SETHURAMAN - 412414105076
UNDER GRADUATE – ELECTRICAL AND
ELECTRONICS ENGINEERING
PROJECT WORK 2018
ANNA UNIVERSITY : CHENNAI 600025
Guided by,
Mrs. A. Sasikala, M.Tech,
Assistant Professor , Department of EEE,
Sri Sai Ram Institute of Technology, Chennai.
Sri Sai Ram Institute of Technology – Chennai. Tuesday, May 8, 2018

ABSTRACT
The speculative nature of solar energy compels the usage of robust
controllers for effective photovoltaic (PV) power electronic interfaces and
power transfer in the system. The entire energy yield can be maximized by
using a maximum power point tracker (MPPT). This ability of the MPPT is
combined with a quasi-Z-source inverter in order to provide a predictive and an
efficient control of the grid-connected photovoltaic cells. MPC is a robust
suboptimal controller which provides a linear model and thus, a simplified
solution for the optimization problem. It provides better performance along
with perturb and observe (P&O) technique compensating for its poor dynamic
performance under rapidly varying meteorological changes. The qZSI(Quasi-Z-
source-inverter) is a single – stage topology that can guarantee a better MPPT
operation and can control the injected power to the grid simultaneously. The
improved control certifies a better stature for operation and maximizes the
photovoltaic power in the grid- tied system.
Tuesday, May 8, 2018
Sri Sai Ram Institute of Technology 2

OBJECTIVE
Sri Sairam Institute of Technology – Chennai.
• To propose a single-stage power conditioning converter that is capable
of robust and effective operation.
• To ensure safe and integrated operation with the grid.
• To provide good dynamic performance under changing ambience.
• To study about various converters like Quasi-Z-Source inverter
and Model Predictive Controller (MPC) and also, analyze their performance
and drawbacks.
Tuesday, May 8, 2018 3

LITERATURE REVIEW
TITLE AUTHOR DESCRIPTION
Model predictive sensorless
control of standalone doubly fed
induction generator
S. Bayhan and H.
Abu-Rub
Throughout the course of a day, the dc voltage
and current of a given module will vary
considerably with temperature and available
sunlight
Differential Power Processing
for Increased Energy Production
and Reliability of Photovoltaic
Systems
P. S. Shenoy, K. A.
Kim, B. B. Johnson,
and P. T. Krein
Maximum Power Point Tracking (MPPT)
ensures that maximum available photovoltaic
energy is harvested as useful energy
Control and Circuit techniques to
Mitigate Partial Shading Effects
in Photovoltaic Arrays
A. Bidram, A.
Davoudi, and R. S.
Balog
P&O algorithm, which is used widely, may
not always converge to the maximum power
point (MPP) under a variety of ambience.
High Efficiency MPPT by Model
Predictive Control Considering
Load
Disturbances for Photovoltaic
Applications Under Dynamic
Weather Condition
M. Metry, M. B.
Shadmand, R. S.
Balog, and H. Abu
Rub
Using system parameters, a PV module can
be implemented along with the inverter model
to determine PV current and voltage as a
function of inverter operation, and thus
provide the reference current for the MPPT
algorithm
Tuesday, May 8, 2018Sri Sai Ram Institute of Technology 4

TITLE AUTHOR DESCRIPTION
Model Predictive Control: Theory
and Design
J. B. Rawlings and D. Q. Mayne A basic concept of MPC is to use
the record of measurements to
determine the most likely initial
state of the system
Quasi-Z-Source Inverter-Based
Photovoltaic Generation System
With Maximum Power Tracking
Control Using ANFIS
H. Abu-Rub, A. Iqbal, S. Moin
Ahmed, F. Z. Peng, L. Yuan, and B.
Ge
The qZSI handles both the wide
input voltage range and avoids
current discontinuity in the PV
module
LITERATURE REVIEW
Tuesday, May 8, 2018Sri Sai Ram Institute of Technology 5

COMPARISON WITH EXISTING SYSTEM
Sri Sai Ram Institute of Technology
• P&O algorithm used under dynamically changing ambience produces high
oscillations, which are vanquished in proposed system.
• Two stage conversion process is condensed to a single stage conversion by
the usage of Quasi-Z- source inverter.
• Quasi-Z- source inverter provides reduced source stress, lower component
ratings and simplified control strategies.
• Synchronization of grid parameters is improved by using MPC algorithm.
• Total harmonic distortion is reduced.

Block diagram
Solar PV array
Impedance
Network
Voltage Source
Inverter
Grid
PLL and
Gate pulse
Generator
MPPT MPC
Transformer
PWM Generator
Sri Sairam Institute of Technology – Chennai.

GENERAL CIRCUIT DIAGRAM
Sri Sai Ram Institute of Technology Tuesday, May 8, 2018 8

SIMULATED CIRCUIT DIAGRAM

SIMULATED CIRCUIT DIAGRAM – MPPT SUBSYSTEM

SIMULATION CIRCUIT - DESCRIPTION
COMPONENT PARAMETERS RATING
Solar Panel
V(oc), I(sc) 11.05 V, 10 A
P(out) 93 W
T(cell) 64.375 degree Celsius
Irradiance 1000 W/m^2
MOSFET(IRF7103Q) Voltage, Current 50V, 3A
Inductor [L1,L3] Inductance 0.5mH
Capacitor [C1,C2] Capacitance 470uF
Transformer Transformer Ratio 3:230 [Yg : Yg]
Grid Voltage 208 x sqrt(2)
X/R Ratio 7

SIMULATION CIRCUIT - DESIGN
Design of Inductor and capacitor
1. Average current through inductor :-
From the description , P= 93W and V dc = 11.05 volts , such that
2. Average capacitor voltage :-
Initial temperature T0= 25 degree Celsius, Final temperature T= 40 degree Celsius,V dc = 11.05
Volts
=> Vc = -16.575 volts
𝑰 𝑳 =
𝑷
𝑽 𝒅𝒄
𝑰 𝑳 =
𝟗𝟑
𝟏𝟏.𝟎𝟓
= 𝟖. 𝟒𝟏𝟔𝟐 𝑨
𝑽 𝒄 =
𝟏 −
𝑻 𝟎
𝑻
× 𝑽 𝒅𝒄
𝟏 −
𝟐𝑻 𝟎
𝑻
𝑽 𝒄 =
𝟏 −
𝟐𝟓
𝟒𝟎 × 𝟏𝟏. 𝟎𝟓
𝟏 −
𝟐 𝑿 𝟐𝟓
𝟒𝟎

3. Minimum Value of inductor :-
From the above equations , Imax = 33.75 A and Vc,avg = 16.575 volts , such that
L1= L2= 0.5 m H
4. capacitor :-
Settling Time Ts = 235 nS , Vc= 4.2801, thus, C= 470 uF
𝑳 𝟏 = 𝑳 𝟐 =
𝑽 𝒄𝒂𝒗𝒈
𝑰 𝒎𝒂𝒙
𝑳 𝟏 = 𝑳 𝟐 =
𝟏𝟔. 𝟓𝟕𝟓
𝟑𝟑. 𝟕𝟓
𝑪 = 𝑰 𝑳(𝒂𝒗𝒈) × 𝑻 𝒔 ×
𝟏
𝑽 𝒄

Design of Model Predictive Controller
1. Sampling time: 1 (seconds)
2. Prediction Horizon: 10
3. Control Horizon: 2
4. Weights:
ManipulatedVariables : 0
ManipulatedVariablesRate : 0.1000
OutputVariables : 1
ECR : 100000
5. State Estimation: Default Kalman gain

MATLAB SIMULATIONS - MPC CHARACTERISTICS

MATLAB SIMULATIONS – TRANSFORMER OUTPUT -
VOLTAGE AND CURRENT VS TIME

MATLAB SIMULATIONS - LOAD VOLTAGE AND CURRENT
VS TIME

MATLAB SIMULATIONS – CURRENT WAVEFORMS VS
TIME

MATLAB FFT ANALYSIS - TOTAL HARMONIC DISTORTION
IN THE LOAD CURRENT.

MATLAB FFT ANALYSIS - TOTAL HARMONIC DISTORTION
IN THE LOAD VOLTAGE.

HARDWARE CIRCUIT DIAGRAM

HARDWARE CIRCUIT - DESCRIPTION
COMPONENT PARAMETERS RATING
Solar Panel
V(oc), I(sc) 11.05 V, 1.5 A
P(out) 16 W
MOSFET(IRF7840) Voltage, Current 500V, 8A
Inductor [L1,L3] Inductance 400uH
Capacitor [C1,C2] Capacitance 470uF
Transformer Transformer Ratio 230:18
Gate driver (TLP250) Voltage, Current 10-35V, +/- 1.5A
PIC16F877A MICRO
CONTROLLER
Memory size, CCM & PWM
& voltage
14kb, 2 no's & 2 to 5.5 Volts

HARDWARE CIRCUIT - DESIGN
1. Average current through inductor :-
From the description , P= 16W and V dc = 11.05 volts , such that
2. Average capacitor voltage :-
Initial temperature T0= 25 degree Celsius and Final temperature T= 40 degree Celsius and V dc =
11.05 Volts
Such that
Vc = -16.575 volts
𝑰 𝑳 =
𝑷
𝑽 𝒅𝒄
𝑰 𝑳 =
𝟗𝟑
𝟏𝟏.𝟎𝟓
= 𝟏. 𝟒𝟓𝑨
𝑽 𝒄 =
𝟏 −
𝑻 𝟎
𝑻
× 𝑽 𝒅𝒄
𝟏 −
𝟐𝑻 𝟎
𝑻
𝑽 𝒄 =
𝟏 −
𝟐𝟓
𝟒𝟎
× 𝟏𝟏. 𝟎𝟓
𝟏 −
𝟐 𝑿 𝟐𝟓
𝟒𝟎

HARDWARE CIRCUIT - DESIGN
3. Minimum Value of inductor :-
From the above equations , Imax = 41.4375 A and Vc,avg = 16.575 volts ,
such that ; L1= L2= 400 u H
4. capacitor :-
Settling Time Ts = 235 nS , Vc= 4.2801, thus, C= 470 uF
𝑳 𝟏 = 𝑳 𝟐 =
𝑽 𝒄𝒂𝒗𝒈
𝑰 𝒎𝒂𝒙
𝑳 𝟏 = 𝑳 𝟐 =
𝟏𝟔. 𝟓𝟕𝟓
𝟒𝟏. 𝟒𝟒
𝑪 = 𝑰 𝑳(𝒂𝒗𝒈) × 𝑻 𝒔 ×
𝟏
𝑽 𝒄
Tuesday, May 8, 2018
27

HARDWARE RESULTS - DC INPUT AND AC OUTPUT

HARDWARE RESULTS – PWM PULSES AND
DC - LINK CAPACITOR VOLTAGE

COMPARISON OF SIMULATION
RESULTS WITH HARDWARE
RESULTS

SIMULATION RESULT AND HARDWARE RESULT OF
DC-LINK CAPACITOR VOLTAGE

GATE PULSE TO THE INVERTER

3 PHASE INVERTER (PHASE TO PHASE VOLTAGE)

APPLICATIONS OF OUR PROJECT WORK
1. Space and orbital stations
2. Solar vehicles
3. Grid interactive PV power generation

CONCLUSION AND FUTURE SCOPE
• Major concern in solar grid-tied system, about effective power harvesting from solar
energy under dynamic conditions, has been inquired.
• New methods of controlling the solar harvest such as MPC has been studied and
implemented. A quasi Z-source inverter is also introduced replacing the two-stage
conversion topology.
• The advantages of the proposed system include rapid attainment of steady state during
the period of control and reduced harmonic distortions in the load side.
• It also provides highly efficient power harvest from the incoming irradiance.
• The rise of new and effective controllers might provide a better performance. Also,
improved algorithms for MPPT techniques might provide a better performance in the
future when combined with such controllers.

HARDWARE IMPLEMENTED – ASSEMBLED CIRCUIT

REFERENCES
[1] P. Fang Zheng, "Z-source inverter," IEEE Trans. Ind. Appl., vol. 39, pp. 504-510, 2003.
[2] P. S. Shenoy, K. A. Kim, B. B. Johnson, and P. T. Krein, "Differential Power Processing for
Increased Energy Production and Reliability of Photovoltaic Systems," IEEE Trans. Power
Electron., vol. 28, pp. 2968- 2979, Jun 2013.
[3] Bidram, A. Davoudi, and R. S. Balog, “Control and Circuit Techniques To Mitigate Partial
Shading Effects in Photovoltaic Arrays,” IEEE J. Photovolt., vol. 2, pp. 532-546, Oct 2012.
[4] Y. Liu, H. Abu-Rub, and B. Ge, "Z - Source/Quasi-Z-Source Inverters: Derived Networks,
Modulations, Controls, and Emerging Applications To Photovoltaic Conversion," IEEE Ind.
Electron. Mag., vol. 8, pp. 3244, Dec 2014.

REFERENCES
[5] M. Gole et al., "Guidelines for modelling power electronics in electric Power
engineering applications," IEEE Trans. Power Del., vol. 12, pp. M 505-514, Jan 1997.
[6] M. Nabipour, M. Razaz, G.H. Seifossadat, S.S. Mortazavi, A new MPPT
Scheme based on a novel fuzzy approach, Renew. Sustain. Energy
Rev.74 (2017) 1147–1169
[7] J. B. Rawlings and D. Q. Mayne, Model Predictive Control: Theory and Design: Nob
Hill Publishing, 2009.

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