The present description generally relates to power generation and particularly to power generation by solar photovoltaic and power electronic converters.
In recent years, due to growing global energy needs, sources of energy alternative to fossil fuel have gained significant popularity. One such energy source has been solar power that converts energy emitted by the sun into electricity and other useful forms of energy. One common device for converting solar energy into electricity is the photovoltaic (PV) solar cell. In one common form, a PV cell includes a semiconductor material, such as silicon, that is configured to form a p-n junction. Photons present in solar energy strike the solar cell, and photons having energy levels that exceed a band gap of the material forming the solar cell liberate electrons from the silicon atoms. A silicon atom with a missing electron has a positive charge referred to as a “hole.” The electrons and holes seek to recombine in the solar cell, and the recombination process generates an electrical voltage and current that can be used in electrical power generation.
An individual PV solar cell typically produces an output voltage of approximately 0.5-0.6 V and an output current of approximately 1.0-2.0 A when exposed to strong sunlight. In most commercial embodiments, many individual PV solar cells are arranged in a single panel and are electrically connected together to enable the panel to generate a greater amount of electrical power. Larger solar power generation facilities typically incorporate solar power arrays that include many panels with the entire facility employing thousands or even millions of the individual PV cells. Large scale solar power generation facilities can cover multiple hectares or even multiple square kilometers of land with PV solar panels.
Many solar power generation systems include a power converter that is electrically connected to one or more solar panels. The power converter is used to condition and regulate the electrical power supplied by the panels into an electrical power useful for powering various devices or for transmission via a power grid. Typical PV panels produce direct current (DC) electrical power. One type of power converter converts the DC power supplied by the PV panel into an alternating current (AC) form that is supplied to an electrical grid for delivery to remote locations or the AC current may be directly connected to one or more commonly used electrical appliances to operate the appliances.
One challenge to continued growth in the field of solar power concerns monitoring of a large number of PV panels and power converter units that are electrically connected to a large power distribution network, such as the electrical grid. Large-scale solar power generation facilities include monitoring equipment that is designed to detect and compensate for panel failures, power surges, brown-outs, and other negative events that could ramify beyond the solar power generation facility and have negative effects on the larger electrical grid. In contrast, micro-generation of solar power involves connecting a much larger number of small solar power generation facilities to the electrical grid. Examples of micro-generation facilities include residential solar power installations that typically include tens or hundreds of square meters of solar panels. Micro-generation facilities often sell excess electrical power to an electrical utility company. Existing monitoring systems are not equipped to identify that occur in micro-generation solar power systems quickly and accurately. Additionally, the costs associated with existing monitoring systems present a barrier to their use with micro-generation systems. Consequently, improvements to monitoring of solar power generation systems that enable fast diagnosis of faults without requiring extensive monitoring equipment would be beneficial.
In one embodiment, a method for identifying operational modes of a solar power system has been developed. The method includes measuring at least one operational parameter of a solar cell, measuring an output of the solar cell, generating a first estimated output for the solar cell with reference to a first model of the solar cell operating in a first operating mode with the at least one operational parameter, generating a second estimated output for the solar cell with reference to a second model of the solar cell operating in a second operating mode with the at least one operational parameter, generating a first probability value that the solar cell is operating in the first operating mode, the first probability value being generated with reference to the first estimated output of the solar cell and a difference between the first estimated output of the solar cell and the measured output of the solar cell, generating a second probability value that the solar cell is operating in the second operating mode, the second probability value being generated with reference to the second estimated output of the solar cell and a difference between the second estimated output of the solar cell and the measured output of the solar cell, identifying a current operating mode of the solar cell as being only one of the first operating mode or the second operating mode, the current operating move being identified with reference to a previous operating mode, the first probability value, and the second probability value, and disconnecting the output of the solar cell from a load in response to the identified current operating mode being the second operating mode.
In another embodiment a method for identifying operating modes of a solar power system has been developed. The method includes measuring at least one operational parameter of a solar cell, measuring an output of the solar cell, measuring at least one operational parameter of a power converter that is electrically connected to the solar cell, measuring an output of the power converter, generating a first estimated output for the solar cell with reference to a first model of the solar cell operating in a first operating mode with the at least one operational parameter of the solar cell, generating a second estimated output for the solar cell with reference to a second model of the solar cell operating in a second operating mode with the at least one operational parameter of the solar cell, generating a first probability value that the solar cell is operating in the first operating mode, the first probability value being generated with reference to the first estimated output of the solar cell and a difference between the first estimated output of the solar cell and the measured output of the solar cell, generating a second probability value that the solar cell is operating in the second operating mode, the second probability value being generated with reference to the second estimated output of the solar cell and a difference between the second estimated output of the solar cell and the measured output of the solar cell, identifying a current operating mode of the solar cell as being only one of the first operating mode or the second operating mode, the current operating move being identified with reference to a previous operating mode, the first probability value, and the second probability value, generating a plurality of estimated outputs for the power converter with reference to a corresponding plurality of models of the power converter, each model in the plurality of models corresponding to one operating mode in a plurality of operating modes of the power converter, generating a plurality of probability values, each probability value in the plurality of probability values being a probability that the power converter is operating in one of the plurality of operating modes of the power converter, each probability value being generated with reference to a corresponding one of the plurality of estimated outputs of the power converter and a difference between the one estimated output and the measured output of the power converter, identifying a current operating mode of the power converter with reference to a previous operating mode, and each of the plurality of probability values, comparing the identified current operating mode of the power converter to an expected operating mode of the power converter with reference to a predetermined number of power converter operating modes having a predetermined order, and disconnecting the output of the power converter from a load in response to at least one of the identified current operating mode of the solar cell being the second operating mode or the identified current operating mode of the power converter being different from the expected operating mode.
For a general understanding of the environment for the system and method disclosed herein as well as the details for the system and method, reference is made to the drawings. In the drawings, like reference numerals have been used throughout to designate like elements. As used herein, the term “operational parameter” refers to a physical property of a circuit or component in a solar power system that can be measured while the component operates. For example, a series resistance value in an individual solar cell is an operational parameter of the solar cell. Various components in the solar power system have one or more operational parameters that may be monitored during operation. As used herein, the term “operating mode” refers to a set of operating characteristics that apply to a component in a solar power system based on the conditions of the component. For example, during a normal operating mode a solar cell generates electrical voltage and current with known parameters when exposed to sunlight. The characteristics of the solar cell in the normal operating mode are modeled to enable an estimate of an output of the solar cell, such as an output voltage or current, when one or more of the operational parameters of the solar cell are measured. One or more failure modes for the solar cell include operational modes where the operational parameters and corresponding output of the solar deviate from the expected output in the normal operating mode. Systems and methods that identify changes in the operational modes of components in a solar power system, particularly failure modes, are described in more detail below.
Cell monitor 124 is configured to measure at least one operational parameter of a single solar cell 108 as well as an output of the solar cell 108 and provide data corresponding to the measurement to the controller 120.
Examples of operational parameters in a solar cell include a series resistance Rs 312, a shunt resistance Rsh, and in the case of
In
Referring again to
The converter monitor 132 provides data corresponding to the measured operating parameters and output of the converter 112 to the controller 120. The embodiment of the power converter 112 depicted in
One method for identifying various operational modes of the power converter 112 includes an averaged fault diagnosis. Switching devices in electronic power circuits result in a discrete system. The topology of the circuit changes by switching the diode and transistors between “on” and “off” states. In this regard, the model requires more details and advanced techniques for fault diagnosis. Probability density evaluation and simulation for a predefined set of faults was conducted to prove the performance of fault diagnosis in simulations. More details of the averaged fault diagnosis method are described in the attached appendix.
Another method for identifying various operating modes of the power converter 112 includes modeling the power converter 112 as a switched circuit. During normal operation, the power converter 112 cycles between three circuit configurations that are depicted in
Referring again to
The controller 120 is configured to identify the operating modes of the solar cells 108 and power converter 112 using a multiple-model adaptive estimator (MMAE).
In the MMAE system 200, the hypothesis center 216 weights the outputs of each of the models 208A-208N based on the current residual signal identified for the model, and also with reference to a prior history of residual signal differences between the actual output from the system 204 and the estimated output from each of the models 208A-208N. The prior history of residual errors used in the hypothesis center 216 enables the MMAE system 200 to weight the values of models based not only on the currently measured residual signal values, but on previous residual signals. In one exemplary configuration, model 208B has a current residual signal value of zero, but has a history of residual values with large magnitudes, while model 208A has a non-zero current residual signal value with a history of low or zero magnitude residual signal values. The hypothesis center 216 weights the output of model 208A more heavily even though the current residual signal value for the model 208A is greater than the residual signal value for model 208B based on the historic residual signal values for both models.
MMAE systems, such as system 200, often include various filters, including Kalman filters, to compensate for noise in the input U(k) and in the corresponding outputs from the models 208A-208N and from the system 204. The exemplary MMAE system 200 additionally includes self-tuning modules 212A-212N. Each of the self-tuning modules 212A-212N is configured to adjust a corresponding one of the models 208A-208N to account for changes in the operating parameters in each model that may occur over time. Examples of changes in an operating parameter for a model that occur over time include changes to internal resistance of a solar cell, or changes to the switching characteristics of the power converter. Thus, the self-tuning modules 212A-212N are configured to selectively discount or “forget” prior residual signal values when the operating parameters of a selected model change over time. The self-tuning modules 212A-212N enable the MMAE system 200 to compensate for changes in the operating parameters of the actual system 204 in each of the models 208A-208N. The tuning modules 212A-212N may employ various algorithms, including the forgetting-factor recursive least square (FFRLS) algorithm. The hypothesis center 216 selectively discounts the weight of historic residual signal values from each of the models 208A-208N based on the tuning values generated by each of the self-tuning modules 212A-212N.
The hypothesis center 216 generates a plurality of probability values that are assigned to each of the models 208A-208N. Each probability value indicates a probability that the actual system 204 is presently operating in an operating mode that corresponds to each one of the models 208A-208N. The MMAE system 200 generates a probability distribution 220 with probability values assigned to each of the models 208A-208N. In one configuration, the controller 120 identifies the model having the highest probability value in the distribution 220 as the current operating mode of the actual system 204. As described in more detail in the attached appendix, the MMAE system 200 is configured to identify changes in the operating mode of the solar cells 108 and power converter 112 in the system 100 using a small number of data samples. Thus, the controller 120 is configured to identify and take appropriate action in a short time period when transient faults occur.
In operation, the solar cells 108 in the solar panel 104 generate electricity that is supplied to the power converter 112 and subsequently to the load 116. The controller 120 receives operating data and output data from the cell monitor 108 and applies the data to an MMAE system. Controller 120 employs circuit models, such as the circuit models depicted in
The controller 120 is also configured to monitor the operating modes of the power converter 112. As seen in
While
In various configurations, the controller 120 performs actions in addition to or instead of operating the switches 110 and 114 when a fault operating mode is identified. In one configuration, the controller 120 generates a record of the failure, including information, such as the time and duration of the failure, and stores the record in the memory 122. Some embodiments of the controller 120 include a networking module (not depicted) that transmits alerts or records of faults via wired or wireless data networks to a remote computing device for further monitoring and diagnostics.
While the embodiments have been illustrated and described in detail in the drawings and foregoing description, the same should be considered as illustrative and not restrictive in character. It is understood that only the preferred embodiments have been presented and that all changes, modifications and further applications that come within the spirit of the invention are desired to be protected.
This patent claims priority to U.S. provisional patent application Ser. No. 61/490,673, which was filed on May 27, 2011, and is entitled “DIAGNOSTICS OF INTEGRATED SOLAR POWER,” the entire disclosure of which is expressly incorporated by reference herein.
Number | Date | Country | |
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61490673 | May 2011 | US |