CN114217663B - Maximum power point tracking parallel control method and device for photovoltaic system - Google Patents
Maximum power point tracking parallel control method and device for photovoltaic system Download PDFInfo
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Abstract
The invention provides a method and a device for controlling tracking and parallelism of a maximum power point of a photovoltaic system, and belongs to the technical field of photovoltaic power generation. The method for controlling the maximum power point tracking parallel of the photovoltaic system comprises the following steps: according to MPPT requirements of the photovoltaic system, embodying an ACP theory; constructing an artificial MPPT control system based on an ACP theory; determining optimal MPPT control parameters based on a calculation experiment; virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are realized. The invention provides a photovoltaic system maximum power point tracking parallel control method by fusing an ACP theory, and realizes the accurate tracking of a photovoltaic system GMPP through virtual-real interaction and parallel execution. And the MPPT parallel control system constructed by the invention can accurately guide the actual GMPP tracking process in real time, so that the controller can accurately judge the actual running state of the system in real time and match the actual running state with the corresponding optimal control parameters, thereby ensuring the tracking performance of the GMPP.
Description
Technical Field
The invention belongs to the technical field of photovoltaic power generation, and particularly relates to a method and a device for tracking and controlling the maximum power point of a photovoltaic system in parallel.
Background
The solar energy is clean and environment-friendly, has huge energy, can be obtained almost everywhere, and is not limited by the land. Photovoltaic power generation therefore plays an important role in new energy power generation. The photovoltaic panel generates photovoltage which is closely related to the solar irradiation intensity, the external temperature and the like, so that the power output of the photovoltaic system is difficult to maintain at the current maximum power point (Maximum power point, MPP) at any time, the power generation efficiency and the stability are greatly reduced, and the safety of a power grid under photovoltaic parallel network is further influenced. Therefore, how to implement maximum power point tracking (Maximum power point tracking, MPPT) of a photovoltaic system is a current problem to be solved.
Under ideal uniform illumination conditions, there is only one MPP per photovoltaic array. However, local shielding of the photovoltaic array by cloud cover, building shadows, dust, fallen leaves, etc. in real environments causes multiple Local MPPs (LMPPs) to appear on the photovoltaic system power-pressure (P-V) curve. How to correctly discern the Global MPP (GMPP) from the plurality of LMPPs and maintain power generation at that power level becomes a great challenge for photovoltaic control system design. Therefore, it is necessary to implement fast and accurate tracking of the maximum power point of the photovoltaic system by designing the MPPT controller.
In addition, in the actual MPPT process of the photovoltaic system, the MPPT controller is difficult to accurately judge the real-time running state of the system and match the real-time running state with corresponding optimal control parameters, so that the GMPP tracking performance is reduced, and the safe and efficient running of the photovoltaic power generation process is not facilitated.
Therefore, a control system capable of accurately guiding an actual GMPP tracking process in real time is needed to be constructed, namely, the method and the device for controlling the maximum power point tracking parallel of the photovoltaic system are provided based on the technical problems.
Disclosure of Invention
The invention aims to at least solve one of the technical problems in the prior art and provides a maximum power point tracking parallel control method of a photovoltaic system.
In one aspect of the present invention, a method for controlling tracking and parallelism of maximum power point of a photovoltaic system is provided, comprising the following steps:
according to MPPT requirements of the photovoltaic system, embodying an ACP theory;
constructing an artificial MPPT control system based on an ACP theory;
determining optimal MPPT control parameters based on a calculation experiment;
virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are realized.
Optionally, the embodying ACP theory according to the MPPT requirement of the photovoltaic system includes:
by combining with the ACP theory, the idea of parallel control is introduced into the MPPT process of the photovoltaic system, and the specific steps of constructing the artificial MPPT control system with the virtual-real interaction function are set.
Optionally, the constructing an artificial MPPT control system based on the ACP theory includes:
building a structure of an artificial MPPT control system based on the selected simulation platform;
constructing operation scene libraries of different control scenes;
selecting an applicable control algorithm according to the actual state and the requirements of the photovoltaic system;
setting control initial parameters and parameter ranges of the MPPT controller.
Optionally, the determining the optimal MPPT control parameter based on the calculation experiment includes:
determining the tracking time and the tracking precision of the photovoltaic array under a certain shielding condition through a calculation experiment;
according to the actual state of the photovoltaic array, obtaining MPPT controller parameters, writing each obtained parameter vector into the MPPT controller respectively, carrying out GMPP tracking test experiments, counting tracking precision, and analyzing and evaluating the counting result to select the optimal parameters of the photovoltaic system MPPT controller under the shielding condition.
Optionally, after analyzing and evaluating the statistical result to select the optimal parameters of the MPPT controller of the photovoltaic system under the shielding condition, the method further includes:
and automatically matching or optimizing the parameters of the MPPT controller on line by using a manual MPPT control system so as to ensure the tracking effect of the GMPP in real time.
Optionally, the implementing virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system includes:
the same control strategy is selected from the actual physical MPPT control system and the artificial MPPT control system, and the same MPPT controller parameter initial value is set;
the synchronous execution of the actual physical MPPT control system and the artificial MPPT control system is realized by a control method based on an agent.
Optionally, the implementing synchronous execution of the actual physical MPPT control system and the artificial MPPT control system by the agent-based control method includes:
collecting photovoltaic array composition, running state, control strategy and parameter initialization information in an actual physical MPPT control system, and updating corresponding information in an artificial MPPT control system to construct a photovoltaic system component highly fitting with dynamic characteristics of the actual physical MPPT control system;
comparing control effects of an actual physical MPPT control system and an artificial MPPT control system, and rapidly correcting MPPT controller parameters of the artificial MPPT control system through generated feedback signals reflecting actual system states so as to reduce deviation of the two;
and analyzing and evaluating based on a calculation experiment, and realizing the high fit of the artificial MPPT control system and the actual physical MPPT control system through real-time information interaction and feedback correction.
Optionally, after the virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are implemented, the method further includes: and verifying the effectiveness of a parallel control method of the maximum power point of the photovoltaic system.
Optionally, the verifying the validity of the photovoltaic system maximum power point parallel control method includes:
performing simulation test based on simulation software;
and constructing performance indexes in the MPPT tracking control process of the photovoltaic system, and verifying the performance of the maximum power point parallel tracking method through numerical quantization and statistics.
In another aspect of the present invention, there is provided a maximum power point tracking parallel control device for a photovoltaic system, including: the system comprises an ACP main control module, a construction module, a calculation module and a virtual reality module; wherein,
the ACP main control module is used for embodying an ACP theory according to MPPT requirements of the photovoltaic system;
the construction module is used for constructing an artificial MPPT control system based on the ACP theory;
the computing module is used for determining optimal MPPT control parameters based on a computing experiment;
and the virtual reality module is used for realizing virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system.
The invention provides a maximum power point tracking parallel control method of a photovoltaic system, which comprises the following steps: according to MPPT requirements of the photovoltaic system, embodying an ACP theory; constructing an artificial MPPT control system based on an ACP theory; determining optimal MPPT control parameters based on a calculation experiment; virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are realized. The invention provides a photovoltaic system maximum power point tracking parallel control method by fusing an ACP theory, and realizes accurate tracking of a photovoltaic system GMPP through virtual-real interaction and parallel execution. And the MPPT parallel control system constructed by the invention can accurately guide the actual GMPP tracking process in real time, so that the controller can accurately judge the actual running state of the system in real time and match the actual running state with the corresponding optimal control parameters, thereby ensuring the tracking performance of the GMPP.
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FIG. 1 is a block flow diagram of a method for controlling maximum power point tracking parallelism of a photovoltaic system according to an embodiment of the invention;
FIG. 2 is a flowchart of a method for controlling maximum power point tracking parallelism of a photovoltaic system based on the ACP theory according to another embodiment of the present invention;
FIG. 3 is a schematic view of a photovoltaic system according to another embodiment of the present invention;
fig. 4 is a schematic structural diagram of a maximum power point tracking parallel control device of a photovoltaic system according to another embodiment of the present invention.
Detailed Description
The present invention will be described in further detail below with reference to the drawings and detailed description, so that those skilled in the art can better understand the technical scheme of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without creative efforts, based on the described embodiments of the present invention belong to the protection scope of the present invention.
As shown in fig. 1 and fig. 2, in one aspect of the present invention, a method S100 for controlling a maximum power point tracking parallel of a photovoltaic system is provided, which specifically includes the following steps S110 to S140:
s110, according to MPPT requirements of the photovoltaic system, embodying an ACP theory.
It should be noted that, in order to construct a control system for accurately guiding the actual GMPP tracking process in real time, the ACP theory based on the parallel system idea provides a new idea for solving the above problem, that is, the theory organically integrates the manual system (a), calculates the experiment (C) and the parallel execution (P), and realizes the accurate tracking of the photovoltaic maximum power point through the interaction of the virtual and real systems.
It should be further noted that, as shown in fig. 2 and 3, the photovoltaic system is generally formed by a photovoltaic array, a DC-DC voltage converter, an MPPT controller, a load, and the like. The photovoltaic array is formed by connecting photovoltaic modules in series and parallel and is used for absorbing solar energy and generating photocurrent and photovoltage so as to be further converted into output electric power. In the MPPT control process, the duty ratio d of the voltage converter is adjusted according to the measured photocurrent and photovoltage of the photovoltaic system to obtain higher output power until the power reaches the GMPP of the photovoltaic array.
Specifically, in this embodiment, by combining with the ACP theory, the idea of parallel control is introduced into the MPPT process of the photovoltaic system, so as to construct a novel MPPT parallel control system with a virtual-real interaction function, i.e., specific steps of constructing the novel MPPT parallel control system with the virtual-real interaction function are set.
S1101, firstly, constructing an artificial MPPT control system, and in the process, considering the problems of modeling of a photovoltaic system, MPPT control strategy selection, initial control parameter setting and the like.
S1102, analyzing and evaluating GMPP tracking effects of the photovoltaic array under different irradiation conditions and shielding conditions through a calculation experiment based on the constructed manual control system to obtain optimal control parameters of the controller under corresponding conditions.
S1103, performing virtual-real interaction and parallel execution of the artificial photovoltaic MPPT control system and the actual physical photovoltaic MPPT control system to lead the ideal artificial system to guide the physical system, and finally achieving the aim that the physical system behavior and the artificial system tend to be consistent.
It should be noted that, the artificial photovoltaic MPPT control system is equivalent to the actual physical MPPT control system in the virtual space, and links having a great influence on the MPPT control performance, such as modeling of the photovoltaic system, discrimination of the shielding condition of the photovoltaic array, selection of the MPPT control strategy, initialization of the controller parameters, and the like, are focused in the construction of the artificial system. Therefore, the parallel control framework of the ACP-based photovoltaic system MPPT constructed in S110 is based. That is, the overall control method is specifically designed through step S110. S120, constructing an artificial MPPT control system based on an ACP theory.
Specifically, based on the ACP materialization theory of step S110, that is, based on the specific steps of the above design, the following materialization processes S120 to S140 are performed, where S120, constructing the artificial MPPT control system includes the following steps S1201 to S1204:
s1201, based on a selected simulation platform, building a structure of an artificial MPPT control system, which is similar to an actual physical MPPT control system, wherein the artificial system consists of a photovoltaic array of M multiplied by N (M and N respectively represent the number of series-parallel photovoltaic modules), a DC-DC voltage converter, an MPPT controller, a load and the like, as shown in figure 2.
S1202, constructing an operation scene library of different control scenes.
Specifically, the output power of the photovoltaic system is often affected by meteorological factors such as different irradiation conditions, external temperature and the like. Meanwhile, local shielding caused by factors such as building shadows, dust, fallen leaves and the like cannot be avoided, and the number and the amplitude of the maximum power points of the photovoltaic array are changed due to different environmental factors, so that an operation scene library considering different control scenes is required to be constructed.
And S1203, selecting an applicable control algorithm according to the actual state and the requirements of the photovoltaic system.
Specifically, the selection of the MPPT control strategy is the core for realizing the tracking of the maximum power point of the photovoltaic system, and an applicable control algorithm is required to be selected according to the actual state and the requirement of the photovoltaic system. Therefore, the construction of the control algorithm library plays a role.
It should be noted that, the control algorithm is not specifically limited in this embodiment, for example, a disturbance observation method (P & O), an incremental conductance method (IC), a hill climbing method, and a sliding mode control method are all relatively conventional MPPT control algorithms, and have been successfully applied in practical PV systems. Therefore, the method is selected from the traditional method at the moment that the requirements on the tracking precision of the GMPP of the photovoltaic system are relatively low. Along with the continuous expansion of the scale of the photovoltaic system components and the gradual strictness of control demands, some novel intelligent methods become active new elements in the photovoltaic MPPT control algorithm library, such as fuzzy logic control, neural network control, bionic algorithm control and the like. It will be apparent to those skilled in the art that the specific selection can be made according to the actual requirements.
In addition, the structure based on the current control strategy also tends to be diversified, the hierarchical structure gradually becomes a research hot spot besides the single-stage structure, and the combination of different algorithms is also common. Therefore, the MPPT control algorithm library with rich components provides a guarantee for the accurate tracking of the GMPP of the photovoltaic system.
S1204, setting control initial parameters and parameter ranges of the MPPT controller.
It should be appreciated that the choice of MPPT controller parameters is an important element in ensuring its performance. Therefore, in the construction of the artificial MPPT control system, the initial parameters or parameter ranges need to be set for control, and a foundation is laid for the acquisition of the follow-up optimal parameters.
From the aspects of operation safety, economy and the like, a large number of test experiments are difficult to directly carry out on the complex industrial processes such as the photovoltaic system, so that the advantages of design flexibility, repeatability and the like of the calculation experiments of the artificial MPPT control system in the ACP can be fully exerted.
S130, determining optimal MPPT control parameters based on a calculation experiment.
Specifically, based on the artificial MPPT control system constructed in step S120, S130 may be embodied as the following steps:
s1301, the performance of the photovoltaic MPPT control system is generally judged by the rapidness and the accuracy of the GMPP tracking process, so that a calculation experiment is needed to determine the tracking time and the tracking accuracy of the photovoltaic array under a certain shielding condition, and the tracking time Ts and the tracking accuracy shown in the following formula are taken as performance indexes in the calculation experiment.
Wherein P is pv Is the stable value of the output power of the photovoltaic system under MPPT control, P GMPP Is the theoretical GMPP of the photovoltaic array under certain shielding conditions.
The differences of shielding conditions such as S1302, irradiation intensity of the photovoltaic array, ambient temperature, and external shielding often cause the parameter of the MPPT controller to change. According to the actual state of the photovoltaic array, obtaining MPPT controller parameters, writing each obtained parameter vector into the MPPT controller respectively, carrying out a GMPP tracking test experiment and counting tracking precision, and analyzing and evaluating the counting result to select the optimal parameters of the photovoltaic system MPPT controller under the shielding condition.
It should be noted that, due to randomness of weather changes and the condition of external shielding, the operation condition of the photovoltaic system often inevitably changes slowly or suddenly, which results in a change of the parameters of the MPPT controller.
Therefore, after the statistical result is analyzed and evaluated to select the optimal parameters of the MPPT controller of the photovoltaic system under the shielding condition, the method further comprises S1303, and the artificial MPPT control system is utilized to automatically match or optimize the parameters of the MPPT controller on line so as to ensure the tracking effect of the GMPP in real time.
The method of the embodiment provides references for timely coping with various conditions in an actual MPPT control system, considers influence of weather condition time variability and external shielding randomness on the photovoltaic GMPP, enables the MPPT control process to be closer to the actual condition, and further improves tracking rapidity and accuracy of the GMPP.
S140, virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are realized, and the method specifically comprises the following steps:
s1401, selecting the same control strategy from an actual physical MPPT control system and an artificial MPPT control system, and setting the same MPPT controller parameter initial value.
S1402, implementing synchronous execution of an actual physical MPPT control system and a manual MPPT control system by a control method based on an agent, comprising:
s1402.1, collecting photovoltaic array composition, running state, control strategy and parameter initialization information in an actual physical MPPT control system, and updating corresponding information in an artificial MPPT control system to enable the artificial MPPT control system to construct a photovoltaic system component, such as a photovoltaic array, a voltage converter, a corresponding controller and the like, which is highly matched with dynamic characteristics of the actual physical MPPT control system.
S1402.2, comparing control effects of an actual physical MPPT control system and an artificial MPPT control system in real time, and rapidly correcting MPPT controller parameters of the artificial MPPT control system through generated feedback signals reflecting actual system states so as to reduce deviation of the two.
S1402.3, analyzing and evaluating based on a new round of calculation experiment, and realizing the high fit of the artificial MPPT control system and the actual physical MPPT control system through real-time information interaction and feedback correction, namely, the state of the physical MPPT control system is approximate to the ideal state of the artificial system.
The steps of the embodiment design a photovoltaic system maximum power point tracking parallel control method fused with ACP (A: manual system, C: calculation experiment, P: parallel execution) theory.
Further, in order to verify the feasibility and effectiveness of the method in the GMPP tracking of the photovoltaic system, after implementing the virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system in step S140, the method further includes step S150: and verifying the effectiveness of a parallel control method of the maximum power point of the photovoltaic system.
Specifically, step S150 includes the following specific procedures: s1501, performing simulation test based on the simulation software, namely performing simulation test by depending on Matlab, python, C/C++ and other software.
S1502, performance indexes in the MPPT tracking control process of the photovoltaic system are built, and the performance of the maximum power point parallel tracking method provided by the embodiment is verified through quantitative and statistical analysis.
In order to improve the power generation efficiency of the photovoltaic system and the safety and stability of the power system under the photovoltaic grid connection, the embodiment provides a parallel control method for tracking the maximum power point of the photovoltaic system by fusing the ACP theory, and accurate tracking of the GMPP of the photovoltaic system is realized through virtual-real interaction and parallel execution.
As shown in fig. 4, in another aspect of the present invention, there is provided a maximum power point tracking parallel control device 200 for a photovoltaic system, including: ACP master control module 210, construction module 220, calculation module 230, and virtual reality module 240; the ACP main control module 210 is configured to embody an ACP theory according to an MPPT requirement of the photovoltaic system. The construction module 220 is configured to construct an artificial MPPT control system based on the ACP theory. The calculating module 230 is configured to determine an optimal MPPT control parameter based on the calculation experiment. The virtual reality module 240 is configured to implement virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system.
It should be understood that, based on the above control method, the control apparatus 200 of the present embodiment further includes a verification module 250 to verify the validity of the parallel control method of the maximum power point of the photovoltaic system.
It should be noted that, the specific control method of the control device provided in this embodiment is described with reference to the foregoing, and will not be described herein.
The following describes the maximum power point tracking parallel control method of the photovoltaic system in further detail with reference to specific embodiments:
fig. 3 is a schematic diagram of a photovoltaic system on which the MPPT control method of the present embodiment depends. The photovoltaic system is composed of a photovoltaic array (M parallel photovoltaic modules, each photovoltaic module comprises N photovoltaic units connected in series, and m=n=4 in this embodiment), a DC-DC voltage converter (DC-DC boost converter is selected in this embodiment), an MPPT controller and a load. In the GMPP tracking process of MPPT, the duty cycle d of the DC-DC converter is adjusted according to the change of the output current and voltage of the photovoltaic array to obtain higher actual output power. Therefore, the fitness function of the control target of MPPT, i.e., the duty cycle optimization process, is defined as:
J(d)＝P PV ＝V PV ·I PV (2)
in this example, the control method based on a 140W photovoltaic array of 4×4 as shown in fig. 1 and 2 includes the following steps:
s1: considering MPPT requirements of a photovoltaic system, and embodying an ACP theory;
s2: constructing an artificial MPPT control system;
s3: establishing optimal MPPT control parameters based on calculation experiments;
s4: virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system;
s5: and verifying the validity of the designed maximum power point tracking parallel control method of the photovoltaic system.
Wherein, step S1 may be embodied as:
s1.1: firstly, constructing an artificial MPPT control system, wherein the problems of modeling of a photovoltaic system, MPPT control strategy selection, initial control parameter setting and the like are considered in the process.
S1.2: based on the constructed manual control system, the GMPP tracking effect of the photovoltaic array under different irradiation conditions and shielding conditions is analyzed and evaluated through a calculation experiment, and the optimal control parameters of the controller under the corresponding conditions are obtained.
S1.3: the virtual-real interaction and parallel execution of the artificial photovoltaic MPPT control system and the actual physical photovoltaic MPPT control system lead the ideal artificial system to guide the physical system, and finally achieve the aim that the physical system behavior and the artificial system tend to be consistent.
In the construction of the artificial system, links with great influence on MPPT control performance are focused, such as photovoltaic system modeling, photovoltaic array shielding condition judgment, MPPT control strategy selection, controller parameter initialization and the like.
Therefore, based on the ACP-based photovoltaic system MPPT parallel control framework constructed in S1, step S2 is embodied as:
s2.1: in the embodiment, a structure of an artificial MPPT control system is built based on a Matlab simulation platform. In the process, the photovoltaic modules are connected in series and parallel to obtain a required photovoltaic array, and a DC-DC booster circuit is built. And then selecting a required control strategy from an MPPT control algorithm library according to the control requirement and setting initial control parameters.
S2.2: the output power of the photovoltaic system is often influenced by meteorological factors such as different irradiation conditions, external temperature and the like. Meanwhile, local shielding caused by factors such as building shadows, dust, fallen leaves and the like cannot be avoided, and the number and the amplitude of the maximum power points of the photovoltaic array are changed due to different environmental factors, so that an operation scene library considering different control scenes is required to be constructed. In the embodiment, the irradiance of each photovoltaic panel is 1000W/m respectively by considering the conditions of uniform irradiance and local shielding 2 、800W/m 2 、600W/m 2 、 500W/m 2 And 300W/m 2 。
S2.3: the MPPT control strategy is a core for realizing the tracking of the maximum power point of the photovoltaic system, and an applicable control algorithm is required to be selected according to the actual state and the requirement of the photovoltaic system. The control algorithm library in the parallel control system provided by the invention comprises traditional MPPT control algorithms such as a disturbance observation method (P & O), an incremental conductance method (IC), a hill climbing method and a sliding mode control method, and intelligent control methods such as fuzzy logic control, neural network control and bionic algorithm control. Meanwhile, the MPPT control system comprises a single-stage control structure and a multi-stage control structure, and also comprises a plurality of algorithm hybrid MPPT control methods. In this embodiment, an MPPT control method based on a gray wolf algorithm is selected.
S2.4: the choice of the controller parameters is an important element in ensuring its performance. Therefore, in the construction of the artificial MPPT control system, the initial parameters or parameter ranges of the variables to be optimized are required to be set, a foundation is laid for the acquisition of the subsequent optimal parameters, and the value range of the duty ratio is (0, 1).
From the aspects of operation safety, economy and the like, a large number of test experiments are difficult to directly carry out on the complex industrial processes such as the photovoltaic system, so that the advantages of design flexibility, repeatability and the like of the calculation experiments of the artificial MPPT control system in the ACP can be fully exerted.
The artificial MPPT control system constructed based on S2, S3 can be embodied as follows:
s3.1: the performance of the photovoltaic MPPT control system is generally judged by the rapidity and the accuracy of the GMPP tracking process, so the tracking time Ts and the tracking accuracy shown in the following formula are used as performance indexes in a calculation experiment.
Wherein P is pv Is the stable value of the output power of the photovoltaic system under MPPT control, P GMPP Is the theoretical GMPP of the photovoltaic array under certain shielding conditions.
S3.2: differences in shielding conditions such as irradiation intensity, ambient temperature and external shielding of the photovoltaic array often cause changes in parameters of the MPPT controller. Therefore, based on the 5 different photovoltaic irradiation conditions described in S2.2, the parameters of the MPPT controller can be obtained by adopting the conventional (P & O and IC algorithms are selected in this embodiment) and intelligent (gray wolf optimization algorithm and synchronous heat transfer search algorithm are selected in this embodiment) optimization methods, the obtained parameter vectors are written into the MPPT controller respectively, GMPP tracking test experiments are performed, tracking accuracy is counted, and finally the obtained numerical statistical junctions are analyzed and evaluated to select the optimal parameters of the MPPT controller of the photovoltaic system under the shielding condition.
S3.3: due to the randomness of weather changes and the condition of external shields, the actual irradiation conditions of the photovoltaic system inevitably change slowly or suddenly, which in turn results in changes in the parameters of the MPPT controller. In this example, the algorithm performance was tested when the photovoltaic irradiation conditions were changed from 1000W/m2 to 600W/m2, respectively, and then slowly changed to 800W/m2, respectively. At the moment, the automatic matching or the online optimization of the manual system to the controller parameters is required to ensure the tracking effect of the GMPP in real time, and references are provided for timely coping with various conditions in the actual MPPT control system.
Based on the step S3, optimal MPPT control parameters of the photovoltaic system under different irradiance conditions can be obtained in real time, and based on this, the step S4 can be embodied as follows:
s4.1: the same control strategy is selected and the same initial value of the controller parameter is set in the actual physical MPPT control system and the artificial MPPT control system (in the embodiment, the MPPT control strategy based on the gray wolf algorithm is selected).
S4.2: and synchronously executing the actual physical MPPT control system and the virtual MPPT control by a control method based on the agent.
S4.2.1: and collecting information such as photovoltaic array composition, running state, control strategy selection, parameter initialization and the like in the actual physical photovoltaic MPPT control system so as to update corresponding information in the artificial MPPT control system, and constructing photovoltaic system components such as the photovoltaic array, the voltage converter, the corresponding controller and the like which are highly matched with the dynamic characteristics of the actual system.
S4.2.2: and comparing control effects of the physical photovoltaic MPPT control system and the artificial MPPT control system in real time, generating a feedback signal reflecting the actual system state, and rapidly correcting the controller parameters of the artificial MPPT control system to reduce deviation of the two.
S4.2.3: and analyzing and evaluating based on a new round of calculation experiment, and realizing the high fit of the artificial MPPT control system and the actual physical MPPT control system through real-time information interaction and feedback correction. I.e., the state of the physical MPPT control system approaches the ideal state of the manual system.
In the steps, an ACP (A: manual system, C: calculation experiment, P: parallel execution) theory fused photovoltaic system maximum power point tracking parallel control method is designed, and simulation test is carried out by depending on Matlab, python, C/C++ and other software in S5 in order to verify feasibility and effectiveness of the method in photovoltaic system GMPP tracking.
S5.1: and (5) performing simulation test by depending on Matlab, python, C/C++ and other software. (this example relies on Matlab platform)
S5.2: and constructing performance indexes, GMPP tracking time, tracking precision and the like in the MPPT tracking control process of the photovoltaic system, and then verifying the effectiveness of the maximum power point parallel tracking method by numerical quantization and statistics.
The invention provides a method and a device for tracking and controlling the maximum power point of a photovoltaic system in parallel, which have the following beneficial effects compared with the prior art:
the invention provides a photovoltaic system maximum power point tracking parallel control method based on an ACP fusion theory, and the photovoltaic system GMPP accurate tracking is realized through virtual-real interaction and parallel execution.
Secondly, the influence of weather condition time variability and external shielding randomness on the photovoltaic GMPP is considered, so that the MPPT control process covers different irradiation conditions of the photovoltaic array as comprehensively as possible, and the tracking of the GMPP is quicker and more accurate.
Third, the MPPT parallel control system constructed by the invention can accurately guide the actual GMPP tracking process in real time, so that the MPPT controller can accurately judge the actual running state of the system in real time and match the actual running state with the corresponding optimal control parameters so as to ensure the tracking performance of the GMPP.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (4)
1. The maximum power point tracking parallel control method of the photovoltaic system is characterized by comprising the following steps of:
according to MPPT demand of photovoltaic system, embody ACP theory, include:
combining with an ACP theory, introducing the idea of parallel control into the MPPT process of the photovoltaic system, and setting and constructing a specific step of an artificial MPPT control system with a virtual-real interaction function;
constructing an artificial MPPT control system based on the ACP theory, comprising:
building a structure of an artificial MPPT control system based on the selected simulation platform;
constructing operation scene libraries of different control scenes;
selecting an applicable control algorithm according to the actual state and the requirements of the photovoltaic system;
setting control initial parameters and parameter ranges of an MPPT controller;
determining optimal MPPT control parameters based on a calculation experiment, comprising:
determining the tracking time and the tracking precision of the photovoltaic array under a certain shielding condition through a calculation experiment;
according to the actual state of the photovoltaic array, obtaining MPPT controller parameters, writing each obtained parameter vector into the MPPT controller respectively, carrying out a GMPP tracking test experiment and counting tracking precision, and analyzing and evaluating the counting result to select the optimal parameters of the photovoltaic system MPPT controller under the shielding condition; the parameters of the MPPT controller are automatically matched or optimized on line by using a manual MPPT control system, so that the tracking effect of the GMPP is ensured in real time;
the virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system are realized, and the method comprises the following steps:
selecting the same control strategy from an actual physical MPPT control system and an artificial MPPT control system, and setting the same MPPT controller parameter initial value;
collecting photovoltaic array composition, running state, control strategy and parameter initialization information in an actual physical MPPT control system, and updating corresponding information in an artificial MPPT control system to construct a photovoltaic system component highly fitting with dynamic characteristics of the actual physical MPPT control system;
comparing control effects of an actual physical MPPT control system and an artificial MPPT control system, and rapidly correcting MPPT controller parameters of the artificial MPPT control system through generated feedback signals reflecting actual system states so as to reduce deviation of the actual physical MPPT control system and the artificial MPPT control system;
and analyzing and evaluating based on a calculation experiment, and realizing the high fit of the artificial MPPT control system and the actual physical MPPT control system through real-time information interaction and feedback correction.
2. The method of claim 1, wherein after implementing the virtual-real interaction and parallel execution of the artificial MPPT control system and the actual physical MPPT control system, further comprising: and verifying the effectiveness of a parallel control method of the maximum power point of the photovoltaic system.
3. The method of claim 2, wherein verifying the validity of the photovoltaic system maximum power point parallel control method comprises:
performing simulation test based on simulation software;
and constructing performance indexes in the MPPT tracking control process of the photovoltaic system, and verifying the performance of the maximum power point parallel tracking method through numerical quantization and statistics.
4. The utility model provides a photovoltaic system maximum power point tracking parallel control device which characterized in that includes: the system comprises an ACP main control module, a construction module, a calculation module and a virtual reality module; wherein,
the ACP main control module is used for embodying an ACP theory according to MPPT requirements of a photovoltaic system, and comprises: combining with an ACP theory, introducing the idea of parallel control into the MPPT process of the photovoltaic system, and setting and constructing a specific step of an artificial MPPT control system with a virtual-real interaction function;
the construction module is configured to construct an artificial MPPT control system based on an ACP theory, and includes:
building a structure of an artificial MPPT control system based on the selected simulation platform;
constructing operation scene libraries of different control scenes;
selecting an applicable control algorithm according to the actual state and the requirements of the photovoltaic system;
setting control initial parameters and parameter ranges of an MPPT controller;
the calculation module is configured to determine an optimal MPPT control parameter based on a calculation experiment, and includes:
determining the tracking time and the tracking precision of the photovoltaic array under a certain shielding condition through a calculation experiment;
according to the actual state of the photovoltaic array, obtaining MPPT controller parameters, writing each obtained parameter vector into the MPPT controller respectively, carrying out a GMPP tracking test experiment and counting tracking precision, and analyzing and evaluating the counting result to select the optimal parameters of the photovoltaic system MPPT controller under the shielding condition; the parameters of the MPPT controller are automatically matched or optimized on line by using a manual MPPT control system, so that the tracking effect of the GMPP is ensured in real time;
the virtual reality module is configured to implement virtual-real interaction and parallel execution of an artificial MPPT control system and an actual physical MPPT control system, and includes:
selecting the same control strategy from an actual physical MPPT control system and an artificial MPPT control system, and setting the same MPPT controller parameter initial value;
collecting photovoltaic array composition, running state, control strategy and parameter initialization information in an actual physical MPPT control system, and updating corresponding information in an artificial MPPT control system to construct a photovoltaic system component highly fitting with dynamic characteristics of the actual physical MPPT control system;
comparing control effects of an actual physical MPPT control system and an artificial MPPT control system, and rapidly correcting MPPT controller parameters of the artificial MPPT control system through generated feedback signals reflecting actual system states so as to reduce deviation of the actual physical MPPT control system and the artificial MPPT control system;
and analyzing and evaluating based on a calculation experiment, and realizing the high fit of the artificial MPPT control system and the actual physical MPPT control system through real-time information interaction and feedback correction.
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