05-05-2012, 11:44 AM
MAXIMUM POWER POINT TRACKING FOR PHOTOVOLTAIC OPTIMIZATION USING EXTREMUM SEEKING
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ABSTRACT
This work develops a maximum power point tracking (MPPT)
algorithm for optimizing solar array performance that is robust
to rapidly varying weather conditions. In particular, a novel
extremum seeking (ES) controller, which utilizes the inverter
ripple, is designed and tested on a simulated array with
grid-tied inverter. The new algorithm is benchmarked against
the perturb and observe (PO) method using irradiance data
gathered on a rooftop array experiment in Princeton, NJ. The
extremum seeking controller achieves an efficiency of 99.7%
and transient rise to the MPP of .1 seconds, which is 100 times
faster than perturb and observe.
INTRODUCTION
Solar power is at the forefront of clean, renewable energy,
and it is gaining momentum due to advances in solar panel
manufacturing and efficiency as well as increasingly volatile
fuel costs. Photovoltaic (PV) solar cells are the most readily
available solar technology, and they operate best on bright
days with little or no obstruction to incident sunlight. However,
frequent overcast days and partial obstructions such as tree
limbs or buildings limit the reliability of solar power in much of
the United States.
Because of the photovoltaic nature of solar panels, their
current-voltage, or IV, curves depend on temperature and irradiance
levels [1]. Therefore, the operating current and voltage
which maximize power output will change with environmental
conditions, as in Figure 1. There are a number of maximum
power point tracking (MPPT) algorithms which track the optimal
current and voltage in a changing environment [2]. A grid-tied
inverter is able to draw at a specified command current onthe-
fly, providing the control authority necessary to design and
apply MPPT algorithms even in rapidly changing weather.
MAXIMUM POWER POINT TRACKING
Currently the most popular MPPT algorithm is perturb and
observe (PO), where the current is repeatedly perturbed by a
fixed amount in a given direction, and the direction is changed
only if the algorithm detects a drop in power between steps.
Although this algorithm benefits from simplicity, it lacks the
speed and adaptability necessary for tracking fast transients
in weather.
A robust new maximum power point tracking algorithm
is based on the extremum seeking (ES) control method. A
schematic of the algorithm is shown in Figure 4. This controller
converges at a rate which is proportional to the slope of the
PI curve and has guaranteed stability over a range of system
parameters [3].
RESULTS
Figure 6 shows irradiance data for two consecutive days in
June, 2007. The data was gathered on the Princeton University
solar deck. The experiments below simulate operation using 25
minutes of measured irradiance data from 12:34-12:59AM on
June 20th, 2007 (day 2). This time period is chosen because it
includes rapid irradiance changes as a result of scattered cloud
cover. Moreover, choosing a short 25 minute window makes it
easier to see the controller response to individual irradiance
changes.