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mppt: a maximum power point tracking photovoltaicsystem.
INTRODUCTIONo maximize a photovoltaic (PV) system's output power, continuously tracking the maximum power point(MPP) of the system is necessary. The MPP depends on irradiance conditions, the panel's temperature,and the load connected. Maximum power point tracking (MPPT) algorithms provide the theoretical meansto achieve the MPP of solar panels; these algorithms can be realized in many different forms of hardwareand software. PV systems that lack MPPT rarely operate at the most efficient, MPP. This is why the ratedpower of the solar panel is almost never realized when connecting a load. The goal of this project was to
rapidly develop, construct, and test a working solution to the MPP problem with a limited budget.
This project was developed from the ground up with only afew references. was the team'sadvisor and provided invaluable guidance throughout theproject's lifetime. The team consisted of five undergraduatestudents: , Stephen Tirador, Nathan Wilbanks,
, and myself.
Rapid development necessitated that the team first lookthrough existing analysis and possible solutions to the MPPproblem. It became clear that the perturb and observe (P&O)technique was widely used for its ease of implementation. Itis based on the following criterion: if the operating voltage ofthe PV array is perturbed in a given direction and if the powerdrawn from the PV array increases, this means that theoperating point has moved toward the MPP and, therefore,the operating voltage must be further perturbed in the same
direction. Otherwise, if the power drawn from the PV array decreases, the operating point has moved away fromthe MPP and, therefore, the direction of the operating voltage perturbation must be reversed.
The team chose to implement the P&O algorithm in software to add flexibility to the system as well as simplify thesystem to the point where the system could be rapidly constructed and testing commenced. The followingcomponents were needed to design a minimal working solution: solar panel, current sensor, voltage sensor, DC‐DCconverter, digital controller, and the glue logic/circuitry to connect everything together.
PROJECTS PICTURES RESUME ABOUT
CONTENTS
HARDWARE COMPONENTS SOFTWARE AND ALGORITHMS FUTURE WORK
INTRODUCTION
SOLAR PANELDIGITAL CONTROLLERDCDC CONVERTERSENSING CIRCUITSDIGITALTOANALOG CONVERTER
MPPT ALGORITHMSEMBEDDED SOFTWARE
PROJECT COSTFUTURE WORKCONCLUSION
Dr. Jaber Abu‐Qahouq
Travis GrantMatt York
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SOLAR PANEL
he solar panel used in our system is an OEM40 model manufactured by and wasprovided by the Department of Electrical and Computer Engineering's . It has a powerrating of 40 W, an open‐circuit voltage (Voc) of 21 Vdc, and a short‐circuit current (Isc) of 2.68 A.
DIGITAL CONTROLLER
he microcontroller provides the control in our system. The choice of microcontroller for the system dictatesmuch of the cost, performance, and flexibility of the entire system. Taking into consideration the project'sconstraints, the Texas Instruments model digital signal controller (DSC) was chosen. Thesingle‐chip C2000 family of microcontrollers is targeted toward real‐time control applications thanks topowerful, high performance integrated peripherals. The core is "math‐optimized" and gives designers themeans to improve system efficiency, reliability, and flexibility when the application requires complex
SunWize Technologies, IncDr. Tim Haskew
TMS320F28335
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algorithms. It features:
The C2000's development tools are very useable and help minimize development time. Software for the controllercan be developed, deployed, and tested with ease thanks to the provided, easy to use IDE featuring a C/C++assembler/compiler/linker in addition to a powerful debugger and seamless device programmer.
DCDC CONVERTER
DC‐to‐DC converter is an electronic circuit which converts a source of direct current from one voltagelevel to another. It is a class of power converter. Electronic switch‐mode DC to DC converters operate bystoring the input energy temporarily and then releasing that energy to the output at a different voltageand current. Just like a transformer, they essentially just change the input energy into a differentimpedance level. So whatever the output voltage level, the output power all comes from the input;there's no energy manufactured inside the converter. In fact some energy is used by the converter
circuitry and components while doing their job. It is this principle that makes a DC‐DC Converter essential forMPPT.
The converter presents an electrical load to the solar panel that varies as the output voltage of the convertervaries. This load variation in turn causes a change in the operating point (current and voltage characteristics) of thepanel. Thus by intelligently controlling the operation of the DC‐DC converter, the power output of the panel can beintelligently controlled and made to output the maximum possible.
The DC‐DC power converter used in our system is a Micro 24 Vout, 100 W V28C24C100BL model manufactured by. The input voltage range of the converter is 9‐36 Vdc. Because the voltage provided by the solar panel (which
serves as the input voltage to the converter) can drop below the converter's 9 Vdc minimum and thus cause theconverter to shut down, our MPPT system is only operational when the voltage provided by the solar panel isgreater than or equal to 9 Vdc. The output voltage of the converter can be varied between 10% and 110% of itsnominal 24 Vdc output (i.e. 2.4‐26.4 Vdc) via a reference input voltage at the SC pin with respect to the ‐OUT pinbetween 0.123‐1.353 Vdc. The converter has the capability of functioning in isolated or non‐isolated modedepending on whether the grounds of the converter (‐IN and ‐OUT) are separate or connected together,respectively.
SENSING CIRCUITSVOLTAGE SENSOR
32‐BIT FLOATING POINT CPU (<=150 MHZ, MODIFIED HARVARD ARCHITECTURE)MEMORY: 68K SARAM, 512K FLASHMAC OPERATIONS16 12‐BIT ADC CHANNELS (<=25MHZ)18 PWM OUTPUTSLOW POWER DISSIPATION (<1W @ 150MHZ AND ALL PERIPHERAL CLOCKS ENABLED)3 32‐BIT CPU TIMERS1 WATCHDOG TIMER88 GPIO6 CHANNEL DMA
Vicor
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n order for the MPPT controller to measure the voltage provided by the solar panel, two resistors, R1 and R2,are employed in parallel with the solar panel to act as a voltage divider. The voltage across R2 in the voltagedivider is fed into an analog‐to‐digital converter (ADC) driver circuit (op‐amp in a voltage follower configurationthat feeds into a low‐pass filter) before being delivered to the ADCINA0 channel of the MPPT controller. Bychoosing the values of R1 and R2 as 1.07 MΩ and 165 kΩ, respectively, the maximum amount of currentdiverted from the load, I2, is small enough, even in a worst‐case scenario, to be considered negligible.
The allowable voltage range for each ADC channel of the MPPT controller is 0‐3 Vdc. Therefore, the voltage acrossR2 (which serves as a scaled‐down representation of the solar panel's voltage) should not exceed 3 Vdc. Based onthe chosen value of R2 as 165 kΩ, the maximum voltage, V(R2,max), sent to the ADC driver circuit (and thus ADCchannel ADCINA0) is ~2.81 Vdc.
CURRENT SENSOR
n order for the MPPT controller to measure the current provided by the solar panel, a single resistor (Rsense) isplaced in series between the solar panel and the DC‐DC converter. The voltage across Rsense is fed into anAD8215 current sensor manufactured by whose output voltage is then fed into an ADC drivercircuit (op‐amp in a voltage follower configuration that feeds into a low‐pass filter) before being delivered tothe ADCINA1 channel of the MPPT controller. By choosing the value of Rsense as 51 mΩ, the maximum voltagedrop across Rsense, VRsense, is small enough, even in a worst‐case scenario, to be considered negligible.
As stated previously, the allowable voltage range for each ADC channel of the MPPT controller is 0‐3 Vdc.Therefore, the output voltage of the AD8215 current sensor (which serves as an equivalent voltage representationof the solar panel's current) should not exceed 3 Vdc. Based on the chosen value of Rsense as 51 mΩ, themaximum voltage, Vout, sent to the ADC driver circuit (and thus ADC channel ADCINA1) is ~2.73 Vdc.
COMPLETE SENSING CIRCUIT WITH ADC DRIVER CIRCUITS
Analog Devices
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In order to condition each of the voltage signals sent to the ADC channels of the MPPT controller, TexasInstruments model op‐amps are used in voltage follower configurations with each of their outputs fedinto a low‐pass filter. The OPA340s provide low output impedance to each of the ADC channels withoutmodifying each of the output voltages being sent from the voltage and current sensor circuits. Of added benefitis the op‐amps' ability to protect each of the ADC channels from being permanently damaged by an inputvoltage that exceeds its maximum operating threshold. This is accomplished by powering each of the op‐amps
with the maximum allowed voltage of the ADC channels: 3 Vdc. This effectively clips any potentially damagingvoltage that would otherwise be fed into the ADC channel at a safe value of 3 Vdc. The voltage and sensor circuitsalong with their corresponding ADC driver circuits are all combined to form the "sensing circuit" for the MPPTsystem.
DIGITALTOANALOG CONVERTER
he DC‐DC converter is controlled via a reference input voltage at the SC pin with respect to the ‐OUT pin between0.123‐1.353 Vdc. The digital signal controller utilizes on‐chip pulse width modulated (PWM) signal generators tocreate an output signal meant to control the DC‐DC converter. An analog low‐pass filter can remove the highfrequency components of the PWM signal, leaving only the low‐frequency content. In this MPPT application, asecond‐order passive filter was used to provide adequate filtering and resolution. The PWM duty cycle is
OPA340
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controlled via software; the duty cycle values for which the reference input voltage of the converter is 0.123‐1.353Vdc were obtained experimentally and the software ensures that the signal is never out‐of‐range. This(PWM as DAC) solution is a legitimate lower cost alternative to dedicated off‐chip DACs.
MPPT ALGORITHMSarious algorithms may perform MPPT. Important factors to consider when choosing a technique toperform MPPT are the ability of an algorithm to detect multiple maxima, costs, and convergence speed.
The irradiance levels at different points on a solar panel's surface tend to vary. This variation leads tomultiple local maxima power points in one system. The efficiency and complexity of an algorithmdetermine if the true maximum power point or a local maximum power point is calculated. In the latter
case, the maximum electrical power is not extracted from the solar panel.
The type of hardware used to monitor and control the MPPT system affect the cost of implementing it. The type ofalgorithm used largely determines the resources required to build an MPPT system.
For a high‐performance MPPT system, the time taken to converge to the required operating voltage or currentshould be low. Depending on how fast this convergence needs to occur and your tracking system requirements,the system requires an algorithm (and hardware) of suitable capability.
PERTURB AND OBSERVE
he concept behind the "perturb and observe" (P&O) method is to modify the operating voltage or currentof the photovoltaic panel until you obtain maximum power from it. For example, if increasing the voltage toa panel increases the power output of the panel, the system continues increasing the operating voltageuntil the power output begins to decrease. Once this happens, the voltage is decreased to get back towardsthe maximum power point. This pertubulance continues indefinitely. Thus, the power output valueoscillates around a maximum power point and never stabilizes.
P&O is simple to implement and thus can be implemented quickly. The major drawbacks of the P&O method arethat the power obtained oscillates around the maximum power point in steady state operation, it can track in thewrong direction under rapidly varying irradiance levels and load levels, and the step size (the magnitude of thechange in the operating voltage) determines both the speed of convergence to the MPP and the range ofoscillation around the MPP at steady state operation.
INCREMENTAL CONDUCTANCE
ncremental conductance considers the fact that the slope of the power‐voltage curve is zero at the maximumpower point, positive at the left of the MPP, and negative at the right of the MPP. The MPP is found bycomparing the instantaneous conductance (I/V) to the incremental conductance (ΔI/ΔV). Once you have theMPP, the system maintains this power point unless a change in V or I occurs (caused by an external event). Ifthis happens, the algorithm will find the new MPP.
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This technique has an advantage in that it can reach and maintain the MPP without losing some efficiency byhaving to oscillate around this point. Under rapidly changing conditions this algorithm tracks more accurately thanthe P&O method. The disadvantage of this method is that it can take longer to reach the MPP because theincreased computation required decreases the number of perturbations to the operating voltage and currentpossible in a set amount of time.
EMBEDDED SOFTWARE
o implement this intelligence, the group employed the aforementioned TF320F28335 digital controller.With this development target in mind, the software development began immediately. The team focused ongetting minimal "working" code onto the controller as soon as possible. The team became familiar with theTI IDE, debugger, programmer, and most importantly the header files. Through the course of a couple ofweeks different projects were deployed to the board, ranging from flashing an LED to running programsfrom the flash memory. Each peripheral to be used in the MPPT project was investigated and played with in
these first few weeks. Most significantly, unit tests for the PWM and the ADC (using DMA) were developed. Eachunit test was built with pre‐defined pass/fail criteria.
For the PWM unit test, the duty cycle of the PWM would be automatically, continuously varied through the entireoperating range of the final MPPT project as defined by the DC‐DC converter control pin specs. The test would passif the PWM duty never exceeded or fell under the defined upper and lower limits and if the PWM duty wascontinuously increasing or decreasing. This test could run without interfacing with the DC‐DC converter; anoscilloscope was hooked into the PWM pins of the controller and the test behavior was observed.
For the ADC unit test, the result of an ADC conversion would be stored in a monitored variable. The referenceanalog signal was varied through a range of values and the variables value was recorded for each analog value.These recorded values were compared to calculated, expected values to verify operation.
Once the team was very comfortable working with the C2000, work began on a custom MPPT algorithm based onthe P&O algorithm from before. This algorithm was attempted first since it was the simplest solution requiring theleast amount of effort while still fulfilling requirements. The simplicity of the algorithm could also afford the teammore time to integrate the hardware and software near the end of development if necessary. This system andalgorithm does not require a scheduler; if the controller needed to be more reactive to more inputs (tracking theMPP of more solar panels) then a scheduling method would likely be necessary to ensure a quick response to allinputs and efficient utilization of the processor.
This system is designed to run for a long time; the software is single purpose and loops forever. Each loop is aniteration of the P&O algorithm described earlier. Each iteration starts by setting a variable to the calculatedamount of power being supplied by the panel (current and voltage values known from ADC). The program thenswitches on whether the power point is increasing or decreasing in voltage. Inside each case the iteration's powervalue is compared to the previous iteration's and the duty of the PWM is either increased or decreased to movecloser to the MPP; if the PWM duty is increased, the voltage will be increasing, if the PWM duty is decreased, the
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voltage will be decreasing. Before repeating the loop, the previous iteration's power variable is set to the currentiteration's. Pseudo code for this behavior is below.
next_pwr = calcPwr(adc_voltage, adc_current); switch(voltage_direction){ case PV_RIGHT : if (next_pwr > prev_pwr){incDuty();} else if (next_pwr <= prev_pwr){ decDuty(); voltage_direction = PV_LEFT;} break; case PV_LEFT : if(next_pwr >= prev_pwr){decDuty();} else if (next_pwr < prev_pwr){ incDuty(); voltage_direction = PV_RIGHT;} break; }prev_pwr = next_pwr;
PROJECT COSTItem Notes Price
Solar Panel SunWize OEM40 (on hand) 0.00
Digital Controller TMS320F28335 Experimenter Kit 110.00
DC‐DC Converter Vicor Micro 24 Vout, 100 W (V28C24C100BL) 175.00
Circuit Materials OPA340s, AD8215, prototyping board, passive components, etc… 35.00
$320.00
hen proposing this project, the projected cost and budget was $500. We came in considerably underbudget primarily thanks to having a solar panel on hand. A solar panel could have been constructedfrom solar cells available at $.5/Watt, or about $20, though construction materials would add morecost. Our simple system (40W panel and P&O algorithm) could have been constructed with a verysimple microcontroller and a less capable DC‐DC converter, bringing the cost down to close to $150.
However, with a cheaper microcontroller, the math operations take longer to evaluate. The incrementalconductance algorithm is more math intensive and has more control flow for one iteration; a cheapmicrocontroller will not offer the same performance as the C2000. Also, the C2000 has enough performancecapabilities and ADC and PWM channels to calculate the MPPT of many different solar panels simultaneously.
FUTURE WORK
he scope of this project was simply to create a working prototype of a MPPT system. This systemsuccessfully uses the simple P&O algorithm to reach the MPP. The additional resources (labor) needed toimplement the more complex incremental conductance algorithm is quite modest. Reaching a stable, trueMPP at steady state instead of oscillating around this point would improve the system's efficiency andincrease reliability. Thus implementing the incremental conductance algorithm is a good choice incontinuing this project.
Another extension of this project would be to directly power the microcontroller and other circuits from the solarpanel instead of from a power supply. Or to incorporate a power supply into the system that draws energy fromthe solar panel or an energy storage element that is in turn charged by the solar panel. This extension would allowthe system to be deployed to remote locations.
Yet another more useful system would be one that could directly power a DC or AC load. An additional DC‐DCconverter would be needed to supply a regulated DC signal. An inverter is needed to supply an AC signal. If the ACsignal is meant to connect to the grid, it is necessary to synchronize the frequency of the signal with that of the gridin addition to limiting the voltage to no higher than the grid voltage.
This digital controller would allow us to add these features to our system with relative ease thanks to its highperformance and many peripherals.
UPDATE: Thanks to the success of this project and the large amount of documentation left behind, two new teamswill be working on extending different parts of this project for next year.
CONCLUSION
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Arenewable energy system, like the one implemented here, is suitable for residential and/or industrial applications.
Such a system would typically provide a regulated AC output voltage that may also track the input mainsutility voltage in phase and amplitude at hundreds to thousands of watts. Thus a system such as this canbe deployed easily with little concern about adapting a home or business's electrical wiring to takeadvantage of solar energy. Many areas allow surplus energy generated by systems such as this to be soldto the utility grid in a policy known as "net metering." But for this project, these features were out ofscope.
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