Renewable energy is obtained from naturally repetitive and persistent flows of energy occurring in the environment. Electricity demand is rising over the years around the globe. So, use of renewable energy based methods like photovoltaic systems is being driven by the need for lower carbon emissions, decreasing capital investment.
Due to the concerns about the levels of greenhouse gas emission and over exploitation of fossil fuel, solar energy is emerging as a clear, free, alternative power source, and attracting a growing amount of political and commercial interest.
Power obtained from solar array depends upon solar insulation, climate etc. Researches conducted on photovoltaic systems face major issues related to high expenditures required for purchasing photovoltaic panels and applying validation test conditions.
A PV emulator, which is an electronic device that simulates VI characteristics of actual PV arrays under different temperatures and solar irradiance conditions is the best suited alternative to such problems. PV emulator was initiated for the testing of PV application such as inverters, MPPT charge controller. The time and money of researchers can be reduced by using a PV emulator since it can replicate different types of panels and in different environmental conditions. The terminal characteristics of a PV cell are non-linear in nature.
Key features of solar emulator
- It should predict nearly same static IV characteristics of real solar array and panel under various weather conditions and local conditions.
2. It should give satisfactory results under partial shading conditions with more than one Peak and Step.
3. Output current and voltage should follow the diode equivalent model as closely as possible.
A DC-DC converter has property of variable resistance, which plays an important role to emulate solar IV characteristics and its respective PV curve of PV array.
Various control schemes for Buck converter based PV emulator
- Hysteresis control.
2. Voltage mode control.
3. Current mode control.
4. Fuzzy Logic control.
The soft computing techniques like Fuzzy Logic, Genetic Algorithm, Artificial Neural Network are frequently used artificial intelligence schemes.
Fuzzy Logic Control stages includes
- Input stage that senses voltage.
b. Intermediate stage where Fuzzy Logic operations take place and generate output for every input
c. Output stage transforms the whole result to respective control output value.
The role of controller is to get full IV characteristics accurately i.e., having very less percentage of deviation from its actual characteristics.
Advantages of using Fuzzy Logic Control in PV applications
- It mimics human control logic.
2. It is inherently robust.
3. It can be modified easily.
4. It uses imprecise language.
However the limitation of Fuzzy Logic control includes:
- Requirement of skilled operator with experience.
2. Complexity in system.
3. Generalised results are not available, so they are programmed for specified application.
For solar power, the output power at a given condition is maximum at a particular operating condition, and the point is known as the Maximum Power Point (MPP). Now-a-days many MPPT control methods are available. The most widely used is the perturbation and observation, P&O method also known as hill-climbing method. This method searches the MPP by checking the differential coefficient of the power, P with respect to the voltage,V or current, I . The main drawback of this method is the oscillations that happen around the optimum voltage point. This results in loss of energy capture that increases with the step size of the perturbation. But by reducing the step size width, the response time to track the MPP would be longer.
MPPT control can also be done by incremental conductance method, which avoids the oscillation appearing in previous P&O method. This is based on comparing the values of conductance increment with the conductance . It removes the effect of the oscillations but performance is not satisfactory enough in lower irradiation regions as only a small range of voltage is covered. Short-current method requires the optimum output current, calculated by multiplying the short circuit current by proportionality constant. This technique although solves the oscillation problem, the step size problem is not eliminated. So, research on computing techniques like Partial Swarm Optimisation (PSO), biogeography-based Optimisation (BBO) are also at a good pace to get MPP.
The Fig a. presents an equivalent electrical model of a PV panel. The characteristic equation for the model is given in Eq. 1
where Vpv = Output voltage of the panel
N = Number of cells
Vt = Thermal voltage
Iph = Photocurrent
Ipv = Output current of the panel
Isat = Diode saturation current
A = Ideality factor
k = Boltzman’s constant
q = Charge of an electron
T = Temperature
Isc = Short-circuit current
Vpv,oc = Open-circuit voltage
(2)
The output power of a PV panel depends on the irradiance incident on the panel and the temperature. Eq. 3 and Eq. 4 present the relationship with irradiance (Ra) and temperature (T). ΔVoc and ΔIsc gives the temperature coefficient of open-circuit voltage and short-circuit current.
(3)
(4)
Photocurrent (I ) can be approximated to short-circuit current when considering the short-circuited PV panel. Considering the open-circuit condition of the panel, the diode saturation current of the model can be found from Eq. 5. These equations (1 to 5) are used to develop general photovoltaic emulator. Power converters-based photovoltaic emulator can be used for reproducing the PV module’s output curve. Designing of PV emulator can be done in different ways. The emulator output I-V characteristics are obtained from a lookup table stored in a memory or using a mathematical exponential model or by amplifying the output of a solar cell in order to produce the I-V curve of a solar panel. Power electronic components can be easily employed for obtaining a solar emulator that closely follows a real solar panel characteristics. One such model utilising this is shown in Fig 1.
Figure 1: PV Emulator using Power electronic components and Fuzzy Logic Controller
The circuit gives best results by varying the load resistance. The Fuzzy Logic controller can be replaced by PID to get parameters like maximum overshoot, transient time, settling time corresponding to the PV panel under study.
Further, Bode and Nyquist Plots can be obtained by calculating transfer function. Thus, the circuit can be utilised to get control parameters using power electronics components. Thus, the modern software approach is the key to fast, efficient, economic and reliable research to provide a common platform to the new researchers without being in direct contact to the field. The new optimisation techniques can be treated as the key to success for our new researchers.
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