1. Technical Field
The techniques described herein relate to balancing power among photovoltaic elements through charge redistribution. The techniques described herein also relate to differential power processing by individually setting currents through different strings of photovoltaic elements, which can reduce the power processed.
2. Discussion of the Related Art
Photovoltaic (PV) power modules include a plurality of photovoltaic cells, also referred to as “PV cells” or “solar cells.” Since each photovoltaic cell has a relatively low cell voltage, photovoltaic cells are conventionally configured as one or more strings of photovoltaic cells to produce a higher voltage. A string of photovoltaic cells has a plurality of photovoltaic cells connected in series, also referred to as a “series string” or simply a “string.” In such a configuration, the current through all the photovoltaic cells in the string (termed the “string current”) is the same. The string current is limited by the available current of the lowest-performing photovoltaic cell in the string. Conditions such as partial shading and dirt accumulation of one or more cells can severely limit the string current, which limits the available power from the string, even if only a few cells are affected out of a large string.
Connecting bypass diodes in parallel with one or more photovoltaic cells can mitigate this problem. If a cell or series combination of cells in parallel with a bypass diode does not produce a high enough voltage, the cell(s) are bypassed by the bypass diode. This approach enables the higher-performing cells to output higher currents, bypassing lower-performing PV cells or groups of PV cells altogether, potentially extracting more power from the string. However, any possible power generation from the lower performing cells is completely forgone, as they are completely bypassed by the bypass diodes. Additional losses are also incurred by directing current through the bypass diodes.
Maximum power point tracking (MPPT) algorithms are used to maximize the power produced by setting the current and voltage for individual cells or groups of cells at the point that produces the maximum power. Such algorithms can continuously adjust the current or voltage to the maximum power point, which can change with shading conditions. The inventors have appreciated that the use of bypass diodes results in an output power characteristic curve that has more than one local maximum, also termed a “non-convex” characteristic curve. The presence of local maxima complicates MPPT algorithms.
Modular architectures such as cascaded dc-dc converters with a central inverter, micro-inverters, and their sub-module variants, have been proposed to allow local MPPT through distributed control. However, such architectures process the full power from each PV cell, which is a disadvantage due to increased insertion loss. In addition, it can be impractical to scale these approaches down to the cell-level, as per-cell inductors and/or capacitor banks may be needed, which increases component count, size and/or cost.
Recently, there has been a push towards differential power processing to balance mismatches in a PV string. By only processing the power mismatch instead of the full power, significant reduction power electronics size and in power loss can be achieved, and various architectures based on this principle have been proposed. These approaches rely on the availability of external energy storage elements. For example, the sub-module integrated converter employs flyback converters, which have a discrete transformer per PV element as energy storage. In the PV-to-PV differential architecture, buck-boost converters with external inductors are used between adjacent PV elements. Discrete capacitors are needed in parallel with each PV sub-module and in between adjacent PV sub-modules in the resonant switched-capacitor converter implementation.
Some embodiments relate to a method that includes re-distributing charge among a plurality of photovoltaic elements in a string using a photovoltaic element as switched charge storage to transfer charge between respective photovoltaic elements of the plurality of photovoltaic elements.
Some embodiments relate to a circuit that includes a switch network configured to re-distribute charge among a plurality of photovoltaic elements by switching a photovoltaic element in parallel with respective photovoltaic elements of the plurality of photovoltaic elements at different times.
Some embodiments relate to a method that includes switching connections between photovoltaic cells in a plurality of phases. The plurality of phases include a first phase comprising connecting a first group of one or more photovoltaic cells in parallel with a second group of one or more photovoltaic cells. The plurality of phases also include a second phase comprising connecting the first group of one or more photovoltaic cells in parallel with a third group of one or more photovoltaic cells.
Some embodiments relate to a photovoltaic energy conversion apparatus. The photovoltaic energy conversion apparatus includes a string of photovoltaic elements comprising a first photovoltaic element and a third photovoltaic element. The photovoltaic energy conversion apparatus also includes a second photovoltaic element. The photovoltaic energy conversion apparatus further includes a switch network comprising one or more switches. The switch network is configured to switch the one or more switches in a plurality of phases. The plurality of phases includes a first phase comprising connecting the second photovoltaic element in parallel with the first photovoltaic element. The plurality of phases also includes a second phase comprising connecting the second photovoltaic element in parallel with the third photovoltaic element.
Some embodiments relate to a photovoltaic energy conversion system comprising a plurality of strings of photovoltaic elements. The photovoltaic energy conversion system includes a controller that selects, based on an output power of the photovoltaic system, a total current to be drawn from the photovoltaic system and individual string currents to be drawn from individual strings of the plurality of strings of photovoltaic elements. The photovoltaic energy conversion system also includes at least one current source controlled by the controller to draw the total current from the photovoltaic system and the individual string currents from the individual strings.
Some embodiments relate to a photovoltaic energy conversion method for a photovoltaic energy conversion system comprising a plurality of strings of photovoltaic elements. The photovoltaic energy conversion method includes selecting, based on an output power of the photovoltaic system, a total current to be drawn from the photovoltaic system and individual string currents to be drawn from individual strings of the plurality of strings of photovoltaic elements. The photovoltaic energy conversion method also includes drawing the total current from the photovoltaic system and the individual string currents from the individual strings.
Some embodiments relate to a method that includes re-distributing charge among a plurality of photovoltaic elements in a string using a capacitive element as switched charge storage to transfer charge between respective photovoltaic elements of the plurality of photovoltaic elements. The photovoltaic elements may be individual photovoltaic cells.
Some embodiments relate to a circuit that includes a switch network configured to re-distribute charge among a plurality of photovoltaic elements by switching a capacitive element in parallel with respective photovoltaic elements of the plurality of photovoltaic elements at different times. The photovoltaic elements may be individual photovoltaic cells.
The foregoing summary is provided by way of illustration and is not intended to be limiting.
In the drawings, each identical or nearly identical component that is illustrated in various figures is represented by a like reference character. For purposes of clarity, not every component may be labeled in every drawing. The drawings are not necessarily drawn to scale, with emphasis instead being placed on illustrating various aspects of the techniques and devices described herein.
Described herein is a technique and apparatus that can balance power among photovoltaic cells to increase energy extraction. Such a technique can improve power production under partial shading conditions, and can enable extracting the maximum power from each photovoltaic cell. To balance power among photovoltaic cells, one or more capacitive elements are connected and disconnected to respective photovoltaic cells (or groups of cells) at a suitable switching frequency to re-distribute charge among them, such that they are maintained at substantially the same voltage. By re-distributing charge among photovoltaic cells in a string, the effects of partial shading on peak power tracking efficiency can be eliminated. Such a charge re-distribution technique allows for high efficiency, as it processes the power mismatch between respective photovoltaic cells or groups of photovoltaic cells instead of processing the full power produced. A string of photovoltaic cells balanced by such a technique exhibits a power versus current characteristic that is convex, and does not have local minima or maxima, which can greatly reduce the cost and complexity of the maximum power point tracking (MPPT) algorithm.
The inventors have recognized and appreciated that the intrinsic capacitance of a photovoltaic cell (e.g., the diffusion capacitance) may be used as an energy storage element for transferring charge among respective photovoltaic cells or groups of cells. The intrinsic capacitance of a photovoltaic cell may be used as a switched capacitance that is connected and disconnected from respective photovoltaic cells or groups of cells in succession, thereby re-distributing and balancing charge among them. Since the diffusion charge is shown to dominate at the maximum power point, such a technique is termed diffusion charge redistribution (DCR). An advantage of implementing charge re-distribution using the intrinsic capacitance of a photovoltaic cell is that no external passive components are needed for charge re-distribution, which can reduce power electronics cost, size and/or complexity. Power balancing can be performed by switching one or more photovoltaic cells or combinations of photovoltaic cells (e.g. series/parallel combinations) in parallel with respective cells or groups of photovoltaic cells. Accordingly, the effects of partial shading can be reduced or eliminated without needing to introduce any passive energy storage components (e.g., capacitors, inductors, or transformers) into the system.
Significant advantages in manufacturing of photovoltaics can be obtained by power balancing between photovoltaic cells. Since power balancing can compensate for mismatches between photovoltaic cells, the complexity of testing and binning during cell manufacturing can be reduced or even eliminated entirely. For example, testing on a cell-by-cell basis may be eliminated. Accordingly, the complexity and cost of manufacturing photovoltaics can be reduced significantly. Prior to describing embodiments of techniques and circuits for charge re-distribution, analysis and characterization of a photovoltaic cell capacitance will be described.
The commonly used single-diode equivalent circuit model of photovoltaic cells proposed in previous studies is shown in
However, the model in
The capacitance of a photovoltaic cell (also referred to herein as the “intrinsic capacitance” of the photovoltaic cell) is equal to the sum of the diffusion capacitance and the depletion layer capacitance. Since the intended operating photovoltaic cell voltage is near the maximum power voltage (Vmp), the diffusion capacitance effect dominates at the maximum power voltage and the depletion layer capacitance can be neglected. Diffusion capacitance is the capacitance due to the gradient in charge density inside a photovoltaic cell. The diffusion capacitance has an exponential dependency on the photovoltaic cell voltage, or a linear dependency on the photovoltaic cell diode current. Specifically, the diffusion capacitance Cd can be expressed as
In Equation (2), Vd is the photovoltaic cell diode voltage, Id is the photovoltaic cell diode current, VT is the thermal voltage, and η is the diode factor. Moreover, I0 is the dark saturation current of the cell due to diffusion of the minority carriers in the junction, and C0 is the dark diffusion capacitance. The time constant can be defined as
τF−1=τ−1+τB−1, (3)
where τ is the minority carrier lifetime and τE is the transit time of the carrier across the diode. If the photovoltaic cell base thickness is greater than the minority carrier diffusion length, τF can simply be approximated as τ. In general, photovoltaic cells made from materials with longer minority carrier lifetimes are more efficient because the light-generated minority carriers persist for a longer time before recombining.
Previous work has revealed that photovoltaic cells (e.g., solar cells) can exhibit diffusion capacitance in the range of microfarads to hundreds of microfarads near the maximum power point voltage. Comparing, for example, to the energy storage capacitance of seven 1 μF capacitors used in the resonant switched-capacitor converter in Stauth, J. T.; Seeman, M. D.; Kesarwani, K., “A Resonant Switched-Capacitor IC and Embedded System for Sub-Module Photovoltaic Power Management,” Solid-State Circuits, IEEE Journal of, vol. 47, no. 12, pp. 3043,3054, December 2012, the photovoltaic cell itself possesses a sufficient amount of capacitance and offers a great opportunity to reduce the number of external passive components or eliminate them entirely. External energy storage capacitors are needed in the case of the resonant switched-capacitor converter in the Stauth et al. paper because power balancing is applied at the sub-module string level, and the effective capacitance of a sub-module string may not be adequate, as it is a series combination of a large number of diffusion capacitors.
Published measurements of photovoltaic cell diffusion capacitance are typically performed by applying a bias voltage across the photovoltaic cells, which may not accurately represent the effect of diffusion capacitance in the context of a switched-capacitor converter. The switching circuit shown in
The characterized photovoltaic cell has a worst-case, i.e., dark, capacitance of 4.64 μF. This minimum capacitance is sufficient for DCR power balancing. Note that the photovoltaic cell diode current is roughly equal to the difference between the short-circuit current and the extracted current. With the typical maximum power current (Imp) being approximately 80-95% of the short-circuit current, the diode current is 5-20% of the short-circuit current at the maximum power point, assuming negligible current through the shunt resistance. Hence, the effective diffusion capacitance for this example cell during normal operation can be as high as 6 to 9 μF.
According to some embodiments, charge redistribution among photovoltaic cells or groups of cells may be performed using a flying capacitor. A diagram of a charge re-distribution circuit that includes a flying capacitor 8 is shown in
The charge redistribution circuit of
As mentioned above, the switch network 6 switches the flying capacitor into different configurations, with the phases repeating at a rate termed the switching frequency. The switching frequency may be in the range of kHz to MHz, in some embodiments. The range of suitable switching frequencies can vary depending upon the capacitances of the cells 2a-2c and the capacitance of the flying capacitor 8, among other considerations.
By using an external energy storage element (e.g., flying capacitor 8) to balance power among photovoltaic cells, differential power processing is preserved and insertion loss is insignificant. That is, if the cells are well-matched and experience the same irradiance, the cell voltages at maximum power should be the same, resulting in nearly zero net current flow into the flying capacitor 8, and therefore zero power loss.
To demonstrate the capability of the photovoltaic cell diffusion capacitance as an energy handling component in a power converter, a prototype was constructed with a single 10 μF capacitor as flying capacitor 8. The prototype included three mono-crystalline photovoltaic cells 2 and six switches 6 implemented as IRF9910 MOSFET switches, in this example.
To evaluate the efficacy of the diffusion capacitances in the context of power balancing, a partial shading condition was imposed by covering half of the top cell 2a. In the experiment, the flying capacitor 8 was switched at approximately 300 kHz with a 33% duty cycle for each phase. The output current was swept linearly on an HP 6063B DC Electronic Load at 1 A/s and the output voltage and current were measured and recorded. The output power versus output current curve for a series string with single-capacitor diffusion charge redistribution is shown in
Under a partial shading condition, the series string current is limited by the weakest link, and therefore the extracted power is reduced dramatically. With bypass diodes in place as shown in
Although
As discussed above, a photovoltaic cell may exhibit substantial diffusion capacitance. In some embodiments, the flying capacitor 8 of
Two exemplary architectures for using a photovoltaic cell to transfer charge between photovoltaic cells are illustrated in
During a first phase, the switches of the switch network 12 connect photovoltaic element PVL1 in parallel with photovoltaic element PV1 and connect photovoltaic element PVL2 in parallel with photovoltaic element PV2. Then, during a second phase, the switches of the switch network 12 connect photovoltaic element PVL1 in parallel with photovoltaic element PV2 and connect photovoltaic element PVL2 in parallel with photovoltaic element PV3. The first and second phases are repeated at a suitable switching frequency, thereby re-distributing charge among all the photovoltaic elements.
SPICE simulations were performed for the configurations of
In the configuration of
One difference between the capacitor-less arrangements of
The switched-capacitor analysis can be generalized to distributed power generation for calculating the insertion loss of adopting diffusion charge redistribution. The switched-capacitor conversion loss can be characterized by two asymptotic limits: the slow- and fast-switching limits. In the slow-switching limit (SSL), the output impedance of the switching converter is calculated assuming all switches and interconnects are ideal, and the capacitors experience impulses of current. In the fast-switching limit (FSL), the capacitor voltages are assumed to be constant, and the switch and interconnect resistances dominate the losses. After deriving both the SSL and FSL losses, the total switched-capacitor loss can be computed as a combination of the slow-switching and fast-switching limit losses.
For illustration, the SSL insertion loss calculation is performed on a 3-2 example string, where N is equal to 3 following the convention shown in
q
ph
1
=q
ph
2
=q
ph/2. (4)
The output is represented by a constant current load drawing a total charge of qout during a complete switching period. That is, qout is the sum of the output charges delivered during phase 1 and phase 2, and therefore
q
out
1
=q
out
2
=q
out/2. (5)
By using capacitor charge balance in steady state, we can write
q
pv,i
1
+q
pv,i
2
=q
ph, (6)
for i=[1, 2, . . . , 5]. By Kirchhoff's current law (KCL), we can further write (7) and (8) for the two phases.
q
pv,1
1
+q
pv,2
1
=q
pv,3
1
+q
pv,4
1
=q
pv,5
1
=q
out/2 (7)
q
pv,1
2
=q
pv,2
2
+q
pv,3
2
=q
pv,4
2
+q
pv,5
2
=q
out/2 (8)
Solving this system of equations (6), (7) and (8) iteratively yields the relationship between the photo-current from each cell and the string output current, as shown in (9).
Each charge flow can then be expressed in terms of the output charge over a complete switching period. The normalized charge flow, or the charge multiplier will be defined as:
The SSL charge multiplier for each photovoltaic cell during the two phases for the 3-2 DCR string is summarized in Table I.
The net charge flowing into any diffusion capacitance over a complete switching cycle in steady state will be zero. Each capacitor in
Equation (11) can be used to determine the SSL charge multipliers of the capacitors, which are summarized in Table II.
The capacitor charge multiplier vector can be generalized to a DCR string with 2N−1 cells, where there are N cells in the load-connected string and N−1 cells in the ladder-connected string. In the general case, the output current to photocurrent ratio and the capacitor charge multiplier expressions are shown in (12) and (13) respectively.
The SSL output impedance of the DCR string can then be written as
In order to calculate percentage insertion loss, the ratio of the SSL output impedance to the load resistance is calculated. This can be found as an expression in terms of the performance of each cell in steady state, operating at its maximum power point with voltage Vmp and current Imp. Using (12), which effectively relates cell current to output current, and the fact that the DCR string voltage equals N times the cell voltage as shown in
The insertion loss fraction, ILSSL can be calculated as the ratio of the SSL output impedance of the DCR string to the load resistance,
and the SSL efficiency of the array can be defined as one minus the SSL insertion loss. Equation (16) represents a fundamental result that is dependent on technology and material choices. It states that the SSL efficiency of a photovoltaic array configured as a DCR string is effectively dictated by the ratio of the maximum power current to the diffusion capacitance, for large N. For illustration, assume the following rounded numbers for our photovoltaic cells under maximum illumination: a maximum power voltage of 0.5V, a maximum power current of 2 A, and a diffusion capacitance of 9 μF. For a DCR string with N of 20 and a switching frequency of 1 MHz, the insertion loss can be calculated to be a manageable 3.5%.
The SSL insertion loss is not the only loss mechanism. It is possible for the DCR string to operate near the SSL-FSL transition where the loss contributions are approximately equal, or deep in FSL where the FSL losses dominate. The string output characteristics in the fast-switching limit are discussed below.
In the fast-switching limit (FSL), the capacitor voltages are assumed to be constant during a switching period. In addition, the duty cycle becomes an important consideration. For the following analysis, a 50% duty cycle is assumed for simplicity. The output impedance will again be derived in the context of the 3-2 DCR example string for illustration, then generalized to a DCR string of arbitrary size.
From
where boundary cases, i.e., apv,01 and apv,2N2 are assumed to be zero. The resulting FSL charge multiplier vector for the 3-2 DCR string is summarized in Table III.
For a DCR string with 2N−1 total cells, the FSL switch charge multiplier vector can be derived as
Hence, the FSL output impedance of an arbitrarily sized DCR string is
where Reff is the effective resistance of the switch on-resistance in series with any interconnect resistance. Relating the FSL output impedance back to the load resistance, the FSL percentage insertion loss can be calculated as
The result in (20) makes intuitive sense because the loss from the fast-switching limit is expected to be inversely proportional to the number of cells behaving like current sources. The dissipated power in the switches is approximately constant for sufficiently large N, while the total generated power increases linearly with N. Note that the factor of 4 in (20) can be derived by using the fact that the power extracted from the ladder-connected string passes through two switching devices. In addition, the current through the switches resembles a square wave, which gives an additional factor of two in power.
From (20), the FSL insertion loss, or conduction loss, can almost always be made negligible for a sufficiently large string. For example, for a DCR string with N of 20, maximum power current of 2 A, maximum power voltage of 0.5V, and an effective switch on-resistance of 15 mΩ, the insertion loss is only 0.58%.
The total insertion loss can be calculated by combining the SSL and FSL losses. A conservative approximation, the root of the quadratic sum the two loss components, will be used. That is,
IL
TOT≅√{square root over ((ILSSL)2+(ILFSL)2)}{square root over ((ILSSL)2+(ILFSL)2)}. (21)
The charge re-distribution approach also effectively corrects for process variations between cells, which normally would limit power extraction from a string of cells. Charge re-distribution, therefore, can improve power extraction from an array of mismatched cells in comparison to other approaches for processing power. Alternatively or additionally, charge redistribution can be viewed as easing the manufacturing problem of assembling a photovoltaic array by accommodating greater cell variation while maximizing power extraction.
Process variation in photovoltaic manufacturing typically refers to the I-V mismatch between the photovoltaic cells. For a series string of photovoltaic cells, I-V mismatch can negatively impact the overall tracking efficiency because the cells may not operate at their individual maximum power points. Instead, they operate at a collective maximum power current for all the cells present in the series string.
In order to improve the cell-level tracking efficiency by reducing cell-to-cell variation, photovoltaic panel manufacturers have invested greatly in improving their manufacturing process as well as evaluating different cell binning algorithms. In the past ten years, manufacturers have been able to refine their production process and reduce the power tolerance from ±10% down to ±3%. Nevertheless, the I-V mismatch can still have higher tolerance when cells are sorted by maximum power.
The subsequent analysis follows in using a first-order approximation for cell output power under deviation from the maximum power point operation. Assuming approximately constant voltage near the maximum power point, the output power (Pcell) can be assumed to be step-wise linear when the cell output current (Icell) is slightly perturbed around the maximum power current:
I
cell=(1−δ)·Imp (22)
P
cell(1−|δ|)·Pmp (23)
To understand the effect of variation on a string, let δi be a random variable which describes the deviation of the current at the collective maximum power of the string to the current of cell i at its maximum power operation. That is, the total power from a series string can be written as
Then the expected power from a series string of N cells can be expressed as
E[P
string
]=N·P
mp·(1−E[|δ|]) (25)
Using (25), the power loss due to process variation can be approximated as the deviation from the maximum available string power N·Pmp. This represents a conservative estimate; the actual power loss can be higher because the magnitude of dP/dI can be much higher when I>Imp. For a more detailed treatment, a Monte Carlo analysis of the expected power with cell-to-cell variation can be performed.
Assuming a uniform distribution of δi with a range of ±5%, the loss in tracking efficiency in a series string due to process variation is approximately 2.5%. Since the DCR string is able to mitigate even larger partial shading mismatches, it will be practically indifferent to the asymmetry from process variation. Hence, the loss in tracking efficiency from cell-to-cell variation, illustrated by E[|S|] in (25), can be naturally recovered. A correction factor is introduced in the overall insertion loss calculation, and complete insertion loss from using a charge re-distribution can then be approximated as
IL
DCR≅(ILSSL)2+(ILFSL)2−E[|δ|]. (26)
A great advantage in performing cell-level MPPT with diffusion charge redistribution lies in the fact that the string output power becomes independent of cell-to-cell process variation. Therefore, it is possible to drastically reduce manufacturing cost by relaxing the extensive and stringent binning process currently employed in manufacturing. It may also greatly simplify manufacturing and assembly processes, as mentioned above.
A 5-cell series string experimental prototype and a 3-2 DCR string experimental prototype were constructed to further validate the proposed concept. The DCR prototype included five P-Maxx-2500 mA mono-crystalline photovoltaic cells, six IRF9910 MOSFET switches, and five LSM115J Schottky diodes. The characteristic output power versus output current curve is obtained by recording both the string output voltage and the output current as an HP 6063B DC Electronic Load sweeps the output current from 0-10 A at a slew rate of 1 ampere per second.
As the electronic load demands more current than the series string can supply, the current saturates at the short-circuit current of the string, as illustrated in
The measured output power of the 5-cell series string has a peak at 2.63 W, and the measured output power of the 3-2 DCR string has a maximum of 2.49 W. This gives a measured efficiency of 94.7%, or a measured DCR insertion loss of 5.3%. The lower measured insertion loss, compared to the calculated 7.1%, can be attributed to the recovery of losses from process variation as shown in (26).
The maximum measured power for each configuration is tabulated in Table IV, where the extracted percentage column illustrates the ratio of power extracted to the total available power under uniform irradiance for the same configuration. It can be seen that with charge re-distribution, the extracted percentage follows one minus the overall shading percentage quite closely, which validates the effectiveness of the power balancing technique using charge re-distribution.
The ladder configuration shown in
Although the insertion losses have been shown to be manageable, having insertion loss on the common-mode generated power may not be attractive for panel manufacturers and system integrators when long-term project economics are considered. Therefore, in the next section, methods for enabling differential processing will be discussed and presented.
An architecture is described which enables fully differential power processing, according to some embodiments. As discussed above, differential power processing (DPP) can enable increasing the photovoltaic energy conversion efficiency. By only processing the generally small mismatch in power among PV elements, the incurred power conversion loss from performing maximum power point tracking (MPPT) can be reduced significantly. Specifically, when the PV elements are operating under matched conditions, their energy production can be extracted directly by the output load, such as a grid-tie inverter, without any intermediate processing.
As discussed above, charge re-distribution has been shown to effectively perform cell-level power balancing on the level of a photovoltaic cell or group of cells, without needing local intermediate energy storage components. Described herein is a technique for differential processing of power from a plurality of strings of series-connected power generating elements (e.g., photovoltaic elements). Such a technique can be used for differential processing of power from a plurality of strings of series-connected photovoltaic elements, with our without performing charge re-distribution.
A differential power processing architecture is described that can be applied to the string-level power electronics. In some embodiments, differential power processing is performed at the string level in a way that is independent of, and decoupled from, the MPPT algorithm and associated electronics. In some embodiments, string-level differential power processing allows direct energy extraction from both the load-connected string 20 and the ladder-connected string 22.
In such a topology, cell-level power balancing and maximum power point tracking may be achieved by charge redistribution on the photovoltaic cells' diffusion capacitance. When all the cells operate under perfectly matching condition, they have the same maximum power voltage Vmp and maximum power current Imp. To extract the maximum power from the strings, the current sources would need to extract Imp from each and every cell, which can be accomplished by each current source 24 and 26 demanding a current of Imp from their respective strings 20 and 22. This corresponds to an even current divide ratio of D=0.5. Under this condition, the photovoltaic cells would each exhibit the maximum power voltage Vmp so that no charge transfer will occur during the switching events in the switches 12 of the ladder. Hence, there is no power processing and no insertion loss associated with adopting diffusion charge redistribution in a ladder architecture compared to that of a series string.
It can also be observed that when the maximum power current Imp is being extracted from the ladder-connected string of photovoltaic cells 22, their active elements are effectively nulled from the perspective of the load-connected string of cells 20. Therefore, the ladder-connected cells 22 appear as a passive string of capacitors to the load-connected string of cells 20. By symmetry, the same observation can be made of the load-connected cells 20 from the perspective of the ladder-connected cells 22. Under matched conditions, this means that no power from the ladder-connected string 20 is processed by the load-connected string 22, and vice versa.
To validate the differential power processing capability in the proposed topology, a SPICE simulation is performed comparing the following three configurations: a 9-series string, a 5-4 DCR string with one output, as shown in
For minimum insertion loss under perfectly matched conditions, the current sources 24 and 26 should demand equal currents, in particular the maximum power current Imp, from their respective strings 20 and 22. However, in some cases asymmetric shading conditions may exist between the strings 20 and 22. In some embodiments, the current divide ratio of the current sources 24 and 26 can be used as an extra degree of freedom to minimize the amount of processed power. This is illustrated in
For example, in the case of a dDCR system of
A SPICE simulation comparing a 9-series string with per-cell bypass diodes, a 5-4 DCR string, and a 5-4 dDCR string is again used to illustrate the utility of the current divide ratio tuning. In this simulation, four cells are affected by partial shading, and partial shading conditions are simulated by decreasing the short-circuit current by 50% in the affected cells. In the 5-4 DCR and dDCR architectures, the four shaded cells are chosen to be the ladder-connected cells 22 according to the discussed example
In the general case with arbitrary shading patterns, finding the optimal current divide ratio may not be as simple as described in the previous example. An output power optimization may be performed over the space spanned by the following two variables: the total output current Iout and the current divide ratio D. The convexity of such a multivariable optimization problem is discussed below.
It was demonstrated above that the output power versus output current characteristic for the original DCR configuration is a convex upwards function, i.e., there is no more than one maximum, regardless of partial shading conditions. This is perhaps one of the most appealing benefits of adopting charge re-distribution. Without the possibility of being stuck at a local maximum power point, the string-level maximum power optimization algorithm can be greatly simplified.
The intuition behind the output power convexity with respect to output current of the single-output DCR topology can be derived from the switching configuration. The ladder switching topology effectively transforms the series string connections of the photovoltaic cells into pseudo-parallel ones. A parallel combination of photovoltaic cells is essentially equivalent to constructing a single large photovoltaic cell, and the pseudo-parallel combination of photovoltaic cells then creates a single “super-cell” with rescaled voltage and current characteristics. Regardless of scaling, if a string behaves as and exhibits characteristics of a single cell, then the output power versus output current curve should be convex.
In the case of the two-variable optimization problem, the same intuitive argument does not apply directly as the optimization now is trying not only to maximize the power extraction from the photovoltaic cells, but also to minimize the amount of power processed by diffusion charge redistribution. Simulation over key corner cases of partial shading conditions as well as randomly generated shading patterns are presented.
The output power contour when the system is operating in uniform irradiance condition is shown in
Since the output power contour is observed to be generally convex over a wide range of shading conditions, there is little to no risk of the optimization being stuck in a local maximum power point. Hence, the MPPT algorithm complexity for this multivariable optimization problem at the string level can be reduced, and well-known MPPT methods such as gradient descent or conjugate gradient methods can be adopted.
In conventional DPP topologies, where a single functional block capable of simultaneously achieving DPP and MPPT is employed and distributed at the desired level of optimization granularity, local MPPT controls the duty ratio of individual converters such that each PV elements operates at its local maximum power point. Although any of the existing and established MPPT algorithms can be adopted, having local control requires additional measurement and sensing hardware for each PV element.
In contrast, power balancing and optimization is inherent in the DCR switching topology such that charge redistribution occurs naturally. In this case, switch synchronization hardware may be used among adjacent converters. There is no need for full-fledged MPPT converters nor localized control to optimize the power for each PV element.
It was shown above that in order to achieve low overall insertion loss, a switching frequency in the range of hundreds of kilohertz was used given the available diffusion capacitance to maximum power current ratio. This constraint arises from the fact that the original DCR configuration processes the generated power from roughly half of the photovoltaic cells at all times. In the case of dDCR, the amount of processed power can be reduced significantly. Therefore, it is possible to decrease the switching frequency while maintaining a certain level of overall conversion efficiency.
For example, given a photovoltaic array installation and its expected amount of mismatch, a slower switching frequency can be determined and fixed at installation time to meet the desirable efficiency target of the project developer. Some embodiments may use adaptive frequency scaling during real-time operation
The dual current interface 28 can be implemented with two isolated string inverters as mentioned in the previous section. In this configuration, the two inverters can perform MPPT individually as the optimization space is shown to be generally convex. Moreover, redundancy and fault tolerance can be gained as added benefits. If one of the inverters fails, it does not necessarily result in total system failure and shutdown. The remaining inverter can continue to operate the system as a single-output DCR system with increased insertion loss, given that appropriate power rating headroom is factored into the system design.
In systems where centralized inverters are used, a current divider interface preceding the inverter can be used. An example implementation of a current divider interface is shown in
The differential power processing architecture can also be extended to other existing maximum power point tracking topologies to enable differential power processing. For example, in PV installations with cascaded dc-dc converters, string connections may be added to the output of the PV modules in addition to the string connections at the output of the dc-dc converters. Together with the dual current source inverter interface, this enables both direct power extraction from the PV string and processed power extraction from the output of the cascaded dc-dc converters, and thereby achieves differential power processing with minimal extra hardware.
Various aspects of the apparatus and techniques described herein may be used alone, in combination, or in a variety of arrangements not specifically discussed in the embodiments described in the foregoing description and is therefore not limited in its application to the details and arrangement of components set forth in the foregoing description or illustrated in the drawings. For example, aspects described in one embodiment may be combined in any manner with aspects described in other embodiments.
Use of ordinal terms such as “first,” “second,” “third,” etc., in the claims to modify a claim element does not by itself connote any priority, precedence, or order of one claim element over another or the temporal order in which acts of a method are performed, but are used merely as labels to distinguish one claim element having a certain name from another element having a same name (but for use of the ordinal term) to distinguish the claim elements.
Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having,” “containing,” “involving,” and variations thereof herein, is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. For example, an apparatus, structure, device, layer, or region recited as “including,” “comprising,” or “having,” “containing,” “involving,” a particular material is meant to encompass at least the material listed and any other elements or materials that may be present.
This application claims priority to U.S. Provisional Application Ser. No. 61/907,780, titled “CAPACITOR-LESS PHOTOVOLTAIC (PV) CELL-LEVEL POWER BALANCING USING DIFFUSION CHARGE REDISTRIBUTION” filed on Nov. 22, 2013, which is hereby incorporated by reference herein in its entirety.
Number | Date | Country | |
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61907780 | Nov 2013 | US |