Comprehensive evaluation of photovoltaic system using MATLAB/Simulink

Comprehensive evaluation of photovoltaic system using MATLAB/Simulink

Jayshree sahu*, M. Ashfaque Khan**,Dr. S. K. Sahu***

*NIIST,Bhopal,**NIIST,Bhopal,***RGPM Bhopal

Absract-This paper presents modeling and

simulation of PVA system in matlab simulink. The model based on exponential equation of pv module. It needs less input values and is more accurate. Here by varying temperature and irradiance as input variables we obtained the I-V, P-V characteristics and hence the harmonic distortion analysis can be made in different phases of supply system. The model has been validated with experimental data of a commercial PV module KC200GT.

Key Words

Photo voltaic (PV), Matlab, Modelling, (RES)-Renewable energy source, MPPT.

Non linear I-V characteristics of P-V Cell(Nomenclature)

Ipv,cell- current generated by incident light

Id shocley diode equation

I0,cell Reverse saturation current q electron charge

k Boltzman constant

T temperature of p-n junction

a diode ideality constant

saturation current of array

Vt thermal voltage or array

Ns cell connected in series Np cell connected in parallel

Rs equivalent series resistance Rp equivalent parallel resistance Isc short circuit current

Voc open circuit voltage

(O,Isc) short circuit point Kv voltage coefficient

Ki current coefficient P max,m maximum power

Pmax,e maximum experimental

Power from data sheet (Voc ,0) open circuit point (Vmp,Imp) Maximum power point

Ipv,n Light generated current at

nominal condition at ( c and 1000 )

T actual Temperature

Tn nominal temperature

G Solar irradiance

Gn nominal irradiance Introduction-With the rapid development of study on solar cells, many models are presented to describe the characteristics of solar cells. This method helps us to construct the circuit model of pv cell. Computer simulation seems to reduce the tests for solar cells .This model accepts irradiance and temperature as environmental parameters as input variables, simulate the I- V characteristics of solar cells.

Fig-a, P-V Cell, P-V Module, P-V Array

combine to form PV module, no of module combine to form PV array.

Maximum power point tracker system(MPPT)

MPPT controller is a power electronic DC/DC chopper or DC/AC inverter system inserted between the PV array and its electric load to achieve the optimum characteristic matching.The p-v array simulation model helps in study of MPPT. Is very important consideration that is taken into account when building a new photovoltaic power system. In order to extract maximum power output from a PV array under varying atmospheric conditions to maximize the return on initial investments. This technique is based on their speed of locating the maximum power point (MPP) of a PV array under given atmospheric conditions, besides the cost and complexity of implementing them.

proportional to the light falling on the cell in parallel with a diode.

The photovoltaic array can be simulated with an equivalent circuit model based on the photovoltaic model given below,

Fig-c, characteristics I-V curve of a practical PVA device and the three remarkable points: short circuit ), maximum power point ) and open circuit ,0).

The I-V characteristic of the ideal photovoltaic cell is

qV

I I I

pv,cell

exp 1

0,cell akT

.1

The light generated current of the photovoltaic cell depends linearly on the solar irradiation and is also influenced by the temperature is given by

Fig-b, P-V Cell model-Circuit Diagram

Shunt diode ideality factor is set to achieve

I pv

I pv,n

G KI T Gn

the best curve match.

Series resistance (Rs): gives a more accurate shape between the maximum power point and the open circuit voltage.

. .2

The diode saturation current and its dependence on the temperature may be expressed by

n

n

T 3 qE 1

I0 I0,n

exp

g

Temperature dependence of the reverse

T aK Tn

T .3

saturation current of the diode is ).

Temperature dependence of the photo- generated current is ( . Current source:

where Eg is the bandgap energy of the semiconductor (Eg 1.12 eV for the polycrystalline Si at 25 C , and is the nominal saturation current. = NskT/q is

the thermal voltage of the array with Ns cells connected in series. ,n is the nominal saturation current, with Vt,n being the thermal voltage of Ns series-connected cells at the nominal temperature .

P-V Array equivalent circuit block model using Matlab / Simulink

I0,n

exp

I sc, n

V oc , n 1

aV t , n

.4

Maximum experimental power from datasheet

P V I I exp

q Vmp Rs Imp 1 Vmp Rs Imp

max,e mp PV 0

kT aNs Rp

.5

For any value of Rs there will be a value of Rp that makes the mathematical I-V curve cross the experimental (Vmp, Imp) point.

Fig .e-Matlab model of P-V system

R V V I R / V I V I exp

Vmp

ImpRs q

V I P }

p mp mp mp s mp pv mp 0

Nsa kT

mp 0 max,e

.6

Input T & G

eq from eq 3 =0

Input T & G

eq from eq 3 =0

Algorithm to adjust the I-V model

End tol

no

Fig.f- Subsystem for calculation of

yes

and from eq -2

from eq -6 Cal P for o <v <

Find

=II – II

Increment

Fig.d-Flowchart Fig.g- Subsystem for calculation of

Fig.h- Subsystem for calculation of

Fig.i-subsystem of input as temperature and irradiance

Fig.j-Subsystem of Photovoltaic Array Model

Simulation Results

The output of a model is evaluated with typical Parameters of the KC200GT solar array at 25C, 1.5AM, 1000W/m2

TABLE I

Fig.k-Simulated Current and voltage curve of KC200GT at 2 c and 1000 W/

Fig.l-Simulated Power and voltage curve of KC200GT at c and 1000

Fig.n- Phase to phase inverter voltage after filter

Fig.o-Phase to phase Inverter voltage without filtering

Fig.p- Phase to ground transformer voltage

Fig.r- grid current and grid voltage

Fig.q- load current and load voltage

Fig.s- V-I waveform of ac bus

Fig.t- Active and Reactive power at load

Fig.u- Active and Reactive power at grid

Fig.v- THD of simulated output at (60 hz)

Fig.w- THD of simulated output(50 hz)

Fig.x- THD of simulatd output(40 hz)

Fig.y-Total harmonic distortion with filter

module,shows harmonic distortion in phase voltage. As we know due to non linear load a lot of harmonic distortion occurs in supply system, due to non linear load harmonic component occurred in voltage waveform of different phases .

The simulation model allows studies such as:

Fig.z-Total harmonic distortion without filter

Result Analysis

The maximum output power form the array under the stated conditions (1000 W/m2 and 25 C) should have been 200W.

Harmonic analysis of voltage waveform

Table-II

1.

At

60 Hz

THD is-

.23%

2.

At

50 Hz

THD is-

39.0%

3.

At

40 Hz

THD is-

108.15%

Table-III

It can be seen a voltage waveform distortion caused by electronic devices inverters used for energy conversion in DC/AC

renewable energy sources electrical parameters (powers, voltages, currents etc.)

renewable energy sources constructive parameters (blades length and number of wind turbine, PV panels number)

voltage and frequency control (control algorithms)

electrical energy conversion (type of DC/AC conversion)

Consumer modeling and control.

Power quality distortion phenomena and analysis.

Renewable energy availability.

Conclusions

The full mathematical models for PV array modules were fully developed including the inherently nonlinear I-V characteristics and variations under ambient temperature and solar irradiation conditions.Grid connected renewable photovoltaic dynamic control strategies were digitally simulated and validated, using matlab/simulink/simpower system software environment.

The dynamic controllers require only the measured values of voltage and current signals in addition to the motor speed low cost sensors and transducers.

The proposed Grid connected renewable photovoltaic schemes are suitable for resort/village electricity application in the range of (1500 watts to 50000 watts), mostly for water pumping, ventilation, lighting, irrigation and village electricity use in arid remote communities.

Future scope

It is necessary to validate the proposed novel dynamic maximum photovoltaic power tracking control strategies by a specific laboratory facility using the low cost micro controllers.

The proposed dynamic effective and robust error driven control strategies can be extended to other control system applications. They are also flexible by adding supplementary control loops to adapt any control objectives of any systems. Further work can be focused on Artificial Intelligence (AI) control strategies.

The research can be expanded to the design and validation of dynamic FACTS with stabilization and compensation control strategies for other stand-alone renewable energy resource schemes as well as grid- connected renewable energy systems to make maximum utilization of the available energy resources.

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