September 15, 2009 - In measuring the performance of a photovoltaic (PV) cell, it is common practice to assume typical conditions of irradiance, temperature, and cell parameters, and that these conditions are uniform across all cells in a PV array. However, there are many situations such as various forms of partial shading of the array that cause significant variations of these factors within an array or a single string of PV panels. The result is panel mismatch and lowered performance; in short, actual performance will deviate significantly from what would be expected.
From testing and field trial results collected at National Semiconductor Labs, and referencing other studies, panel mismatch resulting from shade or other factors can result in disproportionate power loss in solar panels, whereby as little as 10% of shading can lead to a 50% loss of energy harvested. Additionally, for crystalline silicon PV arrays, depending on the array connection, as little as 2.6% shading could lead to a total array loss of 16.7% (Figure 1) [1].
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| Figure 1. The difference in performance of arrays in shaded conditions. |
Some commercial and residential installations fail to meet their
full potential in energy output, and other projects are
abandoned due to a less-than-ideal projection of energy output
due to mismatch. Essentially, there is an inherent
under-utilization of space and under-delivery of energy. For
example, present commercial installations could be 10%-20%
bigger on average and one can only hazard a guess as to the
amount of energy that could be generated from "shaded out"
installations. From a survey conducted by Greenberg Quinlan
Rosner Research of 150 installers in the US in January 2009,
installers acknowledged the problem as endemic, with as many as
54% stating that any shade on installations was unacceptable.
Installers instead choose to "design around the problem,"
leading to an average cost increase of 19%
[2].
This article will explain the phenomenon of panel mismatch and
also analyze why small variations in cell parameters can affect
the system-level performance of the PV array. Additionally,
power optimizer technology will be examined as a solution to the
panel mismatch problem, and the potential benefits of
distributed maximum power point tracking (MPPT) enabled by power
optimizers over centralized MPPT and traditional solutions.
Distributed vs. centralized MPPT
Power generated by a solar module is calculated by multiplying
current (I) by voltage (V). At any given time under any given
conditions, there exists one optimal point -- the maximum power
point (MPP) -- where a module is generating the most power
possible for those conditions. In other words, the single MPP of
a PV module is a function of an exponential relationship between
current and voltage. MPPT is an electronic form of tracking that
utilizes algorithms and control circuits to search for this
maximum energy point and thus allow a converter circuit to
harvest the maximum power available from a PV module.
In cases where irradiation, temperature, and other cell
parameters are uniform, there would be no difference between the
performance of distributed MPPT and centralized MPPT besides
conversion efficiency differences. However, where partial
shading is present, the panel mismatch problem is at its
greatest. Partial shading will result in an array having
multiple MPPs from different panels because of non-uniform
parameters. With a centralized MPPT, this can lead to additional
disproportionate losses. This is for two reasons: First, the
centralized MPPT becomes confused, stopping on a local maximum
point and settling in a sub-optimal point of the voltage to
power configuration; Second, the voltage point of the MPP can be
very diverse due to irregular conditions, going beyond the scope
and voltage range of the centralized MPPT. Because the
variations between panels are significant, it is in these cases
where the ability of power optimizers in distributed MPPT can
enhance the performance of panels independently and boost
performance.
PV arrays for residential, commercial, or utility installations
are typically configured as shown in Figure 2,
with a centralized
inverter that not only converts solar energy from DC to
grid-use AC, but also provides centralized MPPT. In this setup,
multiple strings of PV panels are connected in parallel and they
feed the input of a grid-tied inverter. The centralized inverter
not only converts DC to AC power as a primary function, but also
contains a MPPT controller which seeks to maximize the energy
harvest through a MPPT algorithm from the PV array at all times
by regulating its input impedance.
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| Figure 2. Grid-tied PV system with centralized MPPT. |
PV arrays for residential, commercial, or utility installations
are typically configured as shown in Fig. 2. In this setup,
multiple strings of PV panels are connected in parallel and they
feed the input of a grid-tied inverter. The centralized inverter
not only converts DC to AC power as a primary function, but also
contains an MPPT controller which seeks to maximize the energy
harvest through an MPPT algorithm from the PV array at all times
by regulating its input impedance.
In a PV array with power optimizer technology and distributed
MPPT (Figure 3), a power optimizer unit is
attached at each panel. Power optimizers have a dual track: on
the one hand, they track the best localized MPP, and on the
other, they translate the input voltage/current to a different
output voltage/current to maximize the energy transport in the
system. The power optimizers communicate with each other in an
indirect manner. Optimizers are "cognitive" and self-organizing
-- they sense the I & V environment and adjust themselves until
a total string optimum is achieved, while simultaneously
arriving at a local optimization point at the panel level. At
present, only power optimizers are capable of doing so.
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| Figure 3. Grid-tied inverter with Power Optimizer distributed MPPT. |
Power optimizers keep the time-proven series-parallel panel
arrangement and improve it by distributing only the DC/DC and
MPPT function to the panels. Meanwhile, the power optimizer
architecture is perfectly compatible with existing multi-stage
inverters and will actually allow them to run more efficiently
because the bus voltage can be kept higher and more constant.
Power optimizers are much more than just boosting DC/DC
converters. They deal with extra energy as well as reduced
energy. This means additional light from reflection that also
causes panel mismatch is handled equally well as various forms
of shading. Likewise, it means that power optimizers are capable
of power changes caused by adding panels to a string (making
that string generate more energy) or subtracting a panel or two
from a string (thus reducing energy.) The power optimizer
architecture enables the system to harvest the most energy
available.
Power optimizers: Distributed MPP solutions
We have seen how panel mismatch caused by shade across the cells
as well as other factors can lead to disproportionate losses of
generation from the array. We also see that at present,
installers have addressed the panel mismatch issue by avoiding
the problem, such as designing around shade/not installing at
all, or installing a smaller array, which leads to lowered
energy output.
Bypass diodes in the junction box shorted across strings of
cells and modules can nominally mitigate to a certain degree the
effect of mismatch by diverting the current around shaded cells
and thereby reducing the voltage losses through the module.
However, this is an insufficient solution: all panels today are
already equipped with bypass diodes, and although they prevent
entire strings of panels from dropping out completely, we can
see from the data that there are still sizeable disproportionate
losses of energy harvested.
Conclusion
Power optimizer technology is available today from National
Semiconductor; SolarMagic power optimizers offer the ability to
maximize the energy extracted from every panel while maximizing
the energy transfer in the PV system, recuperating up to 57% of
energy lost to panel mismatch issues. An ideal solution performs
MPP at the panel level; power optimizers address head-on the
problems inherent with centralized systems by increasing total
energy output by up to 37%, therefore mitigating successfully
the panel mismatch problem.
Biography
Ralf Muenster holds a masters degree in physics from the
Technical U. of Munich and served as a scientist at the UC
Berkeley. He is director of the
Renewable Energy Business Unit at National
Semiconductor, 2900 Semiconductor Dr., P.O. Box 58090, Santa
Clara, CA 95052; ph.: (408) 721-5000; e-mail
SolarMagic@NSC.com.
References
[1] Installer Survey by Greenberg Quinlan Rosner Research,
January 2009.
[2]N. Chaintreuil, F. Barruel, X. Le Pivert, H. Buttin, J.
Merten. "Effects of shadow on a grid connected PV system," INES
R.D.I., Laboratory for Solar Systems (L2S); 23rd European PV
Energy Conference, 2008