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Transcript
FIELD MEASUREMENTS OF PV MODULE PERFORMANCE USING A
HANDY TOOL
1
A. Maheshwari1, C.S. Solanki1* and V. Agarwal2*
Department of Energy Systems Engineering, IIT-Bombay, Powai, Mumbai-400076
*1Corresponding author: Phone: +91-22-2576-7895, Fax: +91-22-2572-6875, E-mail: [email protected]
2
Department of Electrical Engineering, IIT-Bombay, Powai, Mumbai-400076
2
* Corresponding author: Phone: +91-22-2576-7422, E-mail: [email protected]
Abstract
Si based PV technology is now matured and operating life of PV module in the range of 20 to 30 years is
guaranteed. During this period, many times, it is required to find out the health of the PV module in the field in
order to estimate the performance degradation after certain time period. This paper is concerned with field testing
of the performance of PV panels, using a very handy tool, for evaluation of the effect of varying atmospheric
conditions on device performance, i.e. to reveal the characteristics of PV modules in actual conditions. The
issues that are of primary interest in these field tests are the module ratings, the modules' response to extreme
weather conditions, and the possibility of performance degradation during long-term outdoor usage. The paper
describes the preparation of the measurements including realization of the entire measurement system, which is
in form of an automatic small size, easy to carry and usable handy tool. The most important part of the
measurements is the IV-curve readings, and the construction of a functional IV-measurement system. Other part
of the work includes the selection of a functioning sensor lineup and the programming of the data acquisition
system (DAS). Environmental measurements are planned in a way that it facilitates the quality control of the
measured IV-data as well as general analysis of the meteorological variables.
Keywords: PV modules testing, field tests, field evaluation, data acquisition system
1.
Introduction
Renewable energy can play an important role in meeting the ultimate goal of replacing large parts of fossil fuels.
One of the promising applications of renewable energy technology is the installation of PV systems to generate
power without emitting pollutants while requiring no fuel. Despite relatively low power density of solar energy,
this resource could potentially satisfy the global energy demand on its own. Increasing efforts are directed
towards reducing the fabrication and installation costs and enhancing the performance of PV systems so that
these systems can be deployed at a larger scale.
PV modules can be designed for a variety of applications and operational requirements. A reliable PV module
should perform its intended purpose adequately for 20 to 30 years, under the operating conditions encountered.
But the PV module output performance is not independent as it varies over extended periods as well as depends
on varying atmospheric conditions from the output rating quoted by the manufacturer, which is measured in the
laboratory at Standard Test Conditions (STC, i.e. the solar spectrum AM1.5, 1000 W/m2 solar radiation intensity,
25°C module temperature and 2 mph wind speed) [Malik AQ et al., 2003]. So it is important to obtain
knowledge how much energy these PV modules produce in different conditions, and how well they maintain
their performance during longer periods of time, which is possible by testing of these modules.
In literature, field experiments are performed by many people, giving examples of the changes in the PV
performance after a certain time interval of outdoor light exposure [Malik AQ et al., 2003, Mitchell KW et al.,
1986]. However, the test results are site-dependent as well as subject to the period of investigation. Thus, these
data should be transformed to different situation with respect to meteorology (i.e. STC) in order to predict the
time evolution. Therefore, a handy tool, which can perform these tasks, is proposed in this paper.
The motivation of this paper is to allow one to find out the health of a PV module at any time in the field at a
very cost-effective rate and to gain extensive field-experience from the modules operating outdoors in various
operating climates, with the help of an automatic handy tool, which will be able to measure and display the
instantaneous performance of the modules. The instantaneous performance of PV modules is characterized by
module output parameters, module temperature, and meteorological data simultaneously [Malik AQ et al., 2003,
Field Measurements of PV Module Performance Using a Handy Tool
223
Green et al., 1982]. This paper describes the information required about the variables which should be measured,
the configuration of the measurement system, the method to derive relevant information from the raw data with
statistical means, etc for testing the PV module health in the field at any given time.
2.
PV Module Parameters and Their Dependencies
Since sunlight is an intermittent energy source, PV modules have to operate under conditions that vary a lot. This
places certain restrictions on their use, because they cannot produce energy at a constant rate and the power
delivered at a certain instant is still very much a function of the weather conditions at hand. Two critical
parameters are the solar irradiance and the temperature of the module. The other parameters that also affect the
performance are wind speed, module degradation and module aging [Green et al., 1982, Gxasheka et al., 2005].
The short circuit current Isc is proportional to the irradiance on the PV module. This Isc rises with increasing
temperature, as the rise is less than 0.1% per ºC, though the standard temperature for reporting Isc is usually
25°C. The open circuit voltage Voc depends logarithmically on the irradiance and decreases at a faster rate with
rising temperature (-2.3mV per ºC) than the Isc increases. Therefore, the PV modules’ maximum power decreases
with rising temperature, as the decrease is 0.4% per ºC and the module efficiency also decreases. Use of the
modules over extended periods also affects the module performance as the output degrades with ageing of the
modules [Dixon et al., 1978]. Voc and Isc depend on parameters like temperature and irradiance, and the
dependency is shown in the following equations [Green et al., 1982]:
VOC =
kT ⎛ I SC ⎞
ln ⎜
⎟
q ⎝ IO ⎠
I SC = bG
(1)
(2)
Where Io is the saturation current, q is the electronic charge, k is the Boltzmann constant, T is the absolute
temperature, G is incident light intensity, and b is a constant, depends on the properties of the semiconductor
junction, the geometry of the detector and the size of the collector area. With the known dependency of Voc and
Isc on the parameters like temperature, irradiance, wind speed, it would be possible to estimate the values of PV
module parameters at any environmental condition. This feature can be built-in in the proposed handy tool and
would enable to estimate the status of a given module in different times of day or different seasons, even though
measurement is performed just once.
3.
Description of the Proposed Measurement Tool
The measurement system for PV modules described in this paper consists of sensors for measuring both
environmental and module parameters, a data-logger for data acquisition, and a display unit to display the
measured values instantly or there can be an option for storage in which the read values can be stored
permanently. The whole measurement process is automated so that the measurements can be conducted for
prolonged intervals. The sensors are calibrated to ensure that they give correct values. Simply assuming that
sensors give the right value can be very disadvantageous, because faulty values are hard to spot afterwards in the
data analysis stage. The features that are taken care of in this tool are that it should be compact, should meet the
technical requirements of the measurements, and satisfies the budget constraints.
Figure 1: Basic block diagram of the measurement system [Dalimin, 1987]
224
Advances in Energy Research (AER – 2006)
Figure 1 shows the basic block diagram of the proposed measurement system [Dalimin, 1987]. Data from the PV
module and the meteorological data are collected through various sensors and electronic circuits. All these data is
in analog form and converted into digital form by an Analog to Digital Converter (ADC). A multiplexer selects
one data at once to convert into digital format and display. For displaying purpose, a 16 character x 2 line display
LCD unit is used. All the electronic units and circuits are controlled and programmed by an 89C51
Microcontroller unit.
Figure 2: Basic schematic diagram of the measurement system
Figure 2 shows the basic schematic diagram of the proposed measurement system. It also gives an idea about the
structure of the measurement system. In a block, shown by dotted lines in Figure 2, the electronic circuitry part
and the displaying unit is situated, and this is connected to the panel and the sensors via wires and cables.
3.1
The Variables to be Studied in Field Experiments
PV-related variables can be grouped into module variables and environmental variables. Module variables
include the parameters related to the IV-curve (ISC, VOC, VMPP and IMPP), the module temperatures and the power
output of the module [Green et al., 1982, Gxasheka et al., 2005]. On the other hand, the most common
environmental parameters include ambient temperature, global irradiance, as well as wind speed and wind
direction. The following sections contain brief descriptions of why these parameters are important for the
operation of PV modules, and how they are measured.
3.1.1
Module Temperature
PV module parameters are sensitive functions of module temperature. The real significance of measuring the
temperature of the modules is to evaluate how it changes with irradiance, wind speed and wind direction, or
ambient temperature. Module temperature can change relatively quickly if the weather conditions change, so it
has to be monitored on a continuous basis. Since the actual temperature inside a PV module cannot be measured,
the temperature sensors are usually attached directly to the back surfaces of the modules. The measured
temperature is not quite equal to the temperature inside the module, but it provides a good starting point for an
estimate. One of the most popular sensors used for this purpose is the thermistor sensor, which provides a rugged
and inexpensive choice for sensor. The fundamental property of a thermistor (dependence of resistance on
temperature) is used to convert temperature into voltage. Amplified and calibrated output of the thermistor
circuit in is send to microcontroller after multiplex and digitization for displaying purposes.
3.1.2
Solar Irradiance
A standard solar module circuit is used to measure the global irradiance. Photodiodes have the unique property
that the output current, i, is directly proportional to the incident light intensity G expressed in W/m2.
Mathematically this is shown in equation (2). Knowing the factor b, suitable electronic circuit is used to convert
Field Measurements of PV Module Performance Using a Handy Tool
225
the short-circuit current to voltage, amplify and calibrate the signal and convert the solar radiation measurements
into binaries digits and the result is displayed by the LCD unit [Benghanem et al., 1997].
3.1.3
IV-curve Parameters
IV-curve parameters contain information of the electrical characteristics
of the modules. The most important parameters are ISC, VOC, VMPP and
IMPP. These parameters are used directly in characterizing the
performance of the modules, and degradation of module performance is
also shown through them. The actual measurement of IV-curves requires
the module to be connected to an electronic circuit in which the load
changes at a certain rate with the help of microcontroller control.
The acquisition of voltages is obtained directly on each module while the
currents are measured with shunts with a little energy consumption. The
module power output is obtained just by measuring the voltage and
current of the module and the required multiplication task is done in the
microcontroller. By gathering most of the data points close to the load
value that corresponds to the maximum power point on the IV-curve, the
MPP can be determined more precisely. The maximum power is
determined using the hill climbing algorithm, which is shown in a flow
chart in Figure 3. The instantaneous power is estimated and a step-by-step
search maximizes the solar panel power transfer. The lastly measured
powers readings are averaged, the power variation is compared with the
last variation in order to decide if the duty-cycle must be increased or
reduced. When the power variation is close to zero, the duty-cycle of the
converter circuit remains in its optimum value since the maximum power
has been attained [Simaes et al., 2000].
Figure 3: Hill climbing algorithm structure
[Simaes et al., 2000]
3.1.4
Other Variables of Interest
Other variables that one may choose to observe are wind speed and direction, UV-radiation, the spectrum of
sunlight, and the air moisture level. Wind speed plays an important role in determining module temperature,
since convective heat losses at the surface of the module are much larger at high wind speeds. Wind direction has
to be related to module placement to determine how strong this effect is at any given time. A rotating wind speed
sensor is called an anemometer that outputs electrical pulses at a rate that is proportional to its rotation
frequency, and wind direction is measured with a windvane, whose output voltage depends on the direction it
points to.
3.2
The Data Acquisition System (DAS)
The DAS consists of an Analog to Digital Converter (ADC), a multiplexer and a microcontroller unit interfaced
with the various measuring circuits and the displaying unit. Figure 4 shows the basic flow chart and Figure 45
shows the state diagram of the DAS [Eftichios et al., 2003, Mukaro et al., 1999].
Figure 4 and 5 shows that when power is first applied or a reset is signaled, the first state entered is the Initialize
state. This state ensures that all internal variables have a defined initial value and that the input/output lines are
properly configured. The system then goes into the Wait state. In this mode, the oscillator remains active to keep
track of time but the system does nothing except to wait for the interrupts. Instruction execution is stopped,
internal power consumption is decreased, however, and internal RAM contents are preserved. The program then
starts the timer and reads for any output device to be connected to the data acquisition system. If it is not
connected the timer awakens the system from the Wait mode. A set of readings is then taken and stored after
which the DAS goes back into the Wait state to wait for another data acquisition and storage cycle. If display
device is connected, the system makes a transition into the Display mode in which the data is send to that device.
When the system start time has been entered, data and reference voltage corresponding to this start time is
immediately sampled and stored. After taking this initial set of readings, the DAS goes back into the Wait state
to wait for another data acquisition and storage cycle. After this state, the microcontroller goes into the
Measurement state where the system increments lapse time and lights an LED to indicate that samples are being
226
Advances in Energy Research (AER – 2006)
taken. In this Measure state, reference voltage is sampled and A/D converter readings from the sensor are taken
and averaged. If the data from sensor is less than a predefined value, the system assumes it is night time and does
not record this data. This is done to save memory. Only lapsed time is recorded, and the data acquisition system
returns to the Wait mode. The system repeatedly sleeps, awakens and keeps track of time until the data are valid.
If the sampled value is above the predefined value, the system goes into the Store state where the data are written
in the external EEPROM chip. Upon completion of data storage, the system switches off the LED to indicate that
the acquisition and storage processes are complete. It then returns to the main program where it will go back into
the Wait mode again to wait for the next data acquisition [Mukaro et al., 1999].
Figure 4: Basic flow chart of the DAS
[Eftichios et al., 2003]
4.
Figure 5: State diagram of the DAS
[Mukaro et al., 1999]
Current Status and Future Work
Sensor circuit realizations for temperature, solar radiation, and I-V curve with their interface with the
microcontroller and displaying circuit are underway. The devices and the circuits have been decided. Some of
the measuring circuits has been discussed and implemented but yet to be calibrated and tested. The monitoring of
different variables will be performed in future for some period to pursue the goal of monitoring the behavior of
the module parameters as functions of the environmental variables.
5.
Conclusion
The motivation of the paper is to allow one to know the health of the PV module in field and monitor their
performance over extended period of time. To achieve the objective, the proposal for a DAS in form of an
automatic handy tool for PV modules field testing is described. This automated field-testing tool will allow
evaluating, analyzing, and testing PV modules under actual operating conditions in the field itself and will show
the interdependence between the electrical parameters of a PV module and the environmental parameters and the
need to take modules in laboratories for testing purposes will be eliminated.
Field Measurements of PV Module Performance Using a Handy Tool
227
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