LabVIEW Based Simulator for Solar Cell Characteristics and MPPT Under Varying Atmospheric Conditions

Though intermittent, solar energy is a clean and eternal source of energy. PV (Photovoltaic) cell is one of the technology to harness the solar energy and use it as electricity. In recent years rising cost of electricity and environmental concerns have made the solar PV technology a rising research field. In this research field the efficiency improvement is the focal point for the researchers. Because of intermittent weather conditions the output power of the solar cell varies directly to the irradiance level and inversely to the cell temperature and cell never operates at its maximum power. In this paper the characteristics of the sun power A-300 solar cell is simulated in a novel way in LabVIEW using MathScript RT Module along with a MPPT (Maximum Power Point Tracker) using variable step sized incremental conductance algorithm that operates the cell at its maximum power without oscillating at maximum power point. Impacts of changing solar insolation and cell temperature on output curves are also discussed graphically and numerically. The results of the simulation verify the data sheet parameters of sun power A-300 solar cell. Graphs of output power of MPPT indicate the accuracy of the variable step sized InC (Incremental Conductance) algorithm for constant and varying solar irradiance with fast tracking and elimination of steady state oscillations about the MPP which is comparatively better than the conventional MPPT algorithms as compared in the results.

visible light falling on the cell. Band gap energy for visible region is 1.5 eV-3.5 eV while for infrared region is 2.40eV-0.95eV. The band gap energy for silicon is 1.12eV [3] and for CdTe it is 1.47 [4]. So silicon solar cell absorbs all the light with band gap energy greater than 1.12 eV. The remaining part of the solar spectrum is useless and it only increases the temperature of the cell and deteriorates cell performance.
The deviation of the seasonal parameters such as irradiance and temperature from the STC (Standard Test Conditions) diminishes the cell efficiency and cell never operate at its maximum power [5]. Maximum power from the solar cell can be attained either by using solar tracker or MPPT. In recent years many MPPT algorithms have been adopted to operate the cell at maximum power point [6]. P&O (Perturb &Observe) and InC [7][8][9] are the efficient one but because of perturbation both generates oscillations about the MPP. In this paper InC algorithm is simulated with variable step size that greatly reduces the steady state oscillations and tracks the MPP accurately.
In literature all the MPPTs were simulated in Matlab/ Simulink [10]. This paper presents a LabVIEW based solar simulator with MPPT which can also be connected to the hardware solar cell through DAQ (Data Acquisition) Assistance and by taking real time voltage and current can track the MPP.

MODELLING OF PV CELL
When sun light falls on the PV cell electrons are knocked off from the valence band to the conduction band leaving holes behind so both move in opposite direction that can be represented by a current source. In this paper a single diode model of PV solar cell shown in Fig. 1 and equivalent mathematical Equations (1-6) are used to acquire the output curves of the PV cell.

Photo current
Photo current also termed as short circuit current is the current generated by the solar irradiance falling on the PV cell presented as a current source I ph in Fig. 1 and it is calculated by using Equation (4).

Forward Biased Diode
If the PV cell is not connected to the external load then there is open circuit voltage that allows a full current to

FIG. 1. SINGLE DIODE MODEL OF SOLAR CELL
flow effectively through a P-N junction acting like a forward biased diode. But when a load is in action, though the voltage is reduced but still there is a voltage that causes the flow of current through the forward biased diode so a diode is in parallel to the current source I ph as shown in Fig. 1.

Series Resistance
The sum of all the resistances encountered by the current as it passes through the PV cell to the external metal contacts through bulk material and to the load, is termed as series resistance as it appears in series to the load as shown in Fig. 1.

Shunt Resistance
As the light falls on the PV cell electrons are knocked from the holes and entered to the conduction band. But before they flow out of the PV cell, some of the electrons and holes recombine causing the decrease in the originally generated current I ph .

SIMULATION OF PV CELL IN LABVIEW
To simulate the characteristics curves of a solar cell, its parametric Equations (1-6) are used. In LabVIEW simulation of these complex equations have been done in literature in a more complex way. Jaleel [11], Srinivas [12] and Pradeep [13] have used the complex way of simulation of PV cell. As a reference the complex way of simulating the short circuit current using Equation (4)

SIMULATION RESULTS
The output characteristics curve of Sun Power A-300 solar cell at standard test conditions (G=1000 W/m 2 , T=25 0 C) are shown in Fig. 5(a-b).  Table 1 and compared in Table 2.

Simulation at Constant Cell Temperature and Varying Solar Irradiance
Throughout the year, continuously changing seasonal pattern affects the solar cell performance negatively.
Because of the absence of solar tracker the number of suns falling on the cell is maximum once a day for a short duration generating maximum power of its capacity. The rest of the day PV cell operates below its rated power because of low irradiance level. P-V and Equations (1)(2)(3)(4)(5) curves are simulated for a wide range of irradiance levels at constant cell temperature 25 0 C explaining the effect of irradiance on output power as shown in Fig. 7. Fig. 7(a) shows the PV curves and Fig. 7

(b) indicates Equations
(1-5) curves for a wide range of irradiance levels at constant STC temperature. , efficiency and fill factor. As the solar irradiance goes on decreasing, P mpp , efficiency and fill factor are also decreased which degrades the performance of the solar cell. If some arrangement is made to collect maximum irradiance on the cell by using solar tracker or Fresnel lens, efficiency of the cell can be increased.

LabVIEW Based Simulator for Solar Cell Characteristics and MPPT Under Varying Atmospheric Conditions
simulated for a wide range of temperatures as depicted in Fig. 8(a-b) respectively. LabVIEW provides the concatenation function of graphs that holds the graph for one value and then shows the output for that range of input values.   FIG.7(b).

Simulation at Constant Solar Irradiance and Varying Cell Temperature
With   Fig. 7(a-b) clearly indicates that the output power of the solar cell is reduced by irradiance and temperature and hence the efficiency of the cell is declined as stated by Equation (6). To let the cell function at maximum power a MPPT controller is used that follows an algorithm to extract the duty cycle for the power converter.

Incremental Conductance Algorithm
In this paper InC algorithm with variable step is simulated for the Sun power A-300 solar cell. This algorithm compares the incremental conductance (dI/dV) with instantaneous conductance Equation (1/5) and decides the operating point of the cell according to Equations (7-9) [10,14].
The Equations (7-9) decide whether to increment or decrement the duty cycle to reach the maxima. Increment and decrement are calculated by Equation (10) called variable step size [17]. Flow chart of the InC algorithm is shown in Fig. 9.
MPPT controller takes voltage and current from the output of the solar cell as simulated in Fig. 4 and then implements the InC algorithm according to flow chart shown in Fig. 9.
LabVIEW provides shift registers that hold V(K) and I(K) and use them in next iteration as V(K-1) and I(K-1) to compare the dI/dV with Equations (1/5) determining the operating point and deciding whether to increment or decrement the duty ratio. Simulated block diagram of the InC algorithm is   Fig. 11. Then the irradiance level was changed from 1000 W/m 2 to 800 W/m 2 to 600 W/m 2 and it was observed that the chosen InC algorithm performed its duty well and accurately tracked the MPP for varying solar irradiance with minute oscillations as given in Fig 12. In Fig  7(a) MPP at 800 W/m 2 is 2.55W and at 600 W/m 2 it is 1.91W which was accurately tracked by the implemented InC algorithm as shown in Fig. 12. Ishaque [18] and Joshi [19] have implemented HC (Hill Climbing) and P&O conventional algorithms respectively for tracking the maximum power point shown in Fig. 10. The duty cycle calculated by InC. was fed to the DC-DC boost converter imported from multisim using co-simulation method as described in [2].
of the solar panel. Both of these algorithms have been extensively used because of simplicity but both have the problems of oscillations at the maximum power point and hence the power at load is degraded. Fig. 13 shows the output power of solar panel with HC algorithm under varying solar irradiance that does track the maximum power but generates steady state oscillations at MPP. Fig. 14