Distributed photovoltaic grid-connected data processing method and device, terminal equipment and storage medium
By averaging the forward converter, DC-DC circuit, and DC-AC circuit of the combiner box in a distributed photovoltaic grid-connected system, the problem of low state detection efficiency was solved, automated state detection was realized, and detection efficiency was improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-25
- Publication Date
- 2026-04-07
AI Technical Summary
The status monitoring efficiency of existing distributed photovoltaic grid-connected systems is low, mainly because it is difficult for humans to process the massive amount of operational data.
By averaging the forward converter, DC-DC circuit, and DC-AC circuit in the combiner box, first, second, and third averaging models are constructed, and simulations are performed based on these models to obtain state detection results.
The system automates the status monitoring of distributed photovoltaic grid-connected systems, significantly improving monitoring efficiency.
Smart Images
Figure CN121809000A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of power systems, and more particularly to a data processing method, apparatus, terminal equipment, and storage medium for distributed photovoltaic grid connection. Background Technology
[0002] In modern power systems, the status of distributed photovoltaic grid-connected systems is usually monitored manually. However, due to the massive amount of operational data of distributed photovoltaic grid-connected systems, it is difficult for humans to determine the status of the distributed photovoltaic grid-connected systems from the vast amount of operational data.
[0003] Therefore, the current status monitoring of distributed photovoltaic grid-connected systems suffers from low efficiency. Summary of the Invention
[0004] This invention provides a data processing method, apparatus, terminal equipment, and storage medium for distributed photovoltaic grid-connected systems, which can solve the problem of low efficiency in status detection of existing distributed photovoltaic grid-connected systems.
[0005] The data processing method for distributed photovoltaic grid connection provided by this invention includes: To acquire the operating data of the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit of the distributed photovoltaic grid-connected system; wherein the distributed photovoltaic grid-connected system includes: the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit; The combiner box forward converter is modeled by averaging to obtain the first averaged model of the combiner box forward converter; the DC-DC circuit is modeled by averaging to obtain the second averaged model of the DC-DC circuit; and the DC-AC circuit is modeled by averaging to obtain the third averaged model of the DC-AC circuit. Simulations were performed based on the operating data of the combiner box forward converter and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model. Based on the simulation results of each averaging model, the state detection results of the distributed photovoltaic grid-connected system were obtained.
[0006] Further, the step of averaging the combiner box forward converter to obtain the first averaged model of the combiner box forward converter includes: Obtain the converter topology of the combiner box forward converter and determine the switching state of the combiner box forward converter; wherein, the switching state of the combiner box forward converter includes: the combiner box forward converter switch is on, the combiner box forward converter switch is off and in the magnetic reset process, and the combiner box forward converter switch is off and the magnetic reset is completed. When the forward converter switch in the combiner box is turned on, the equivalent circuit of the first converter is transformed based on the converter topology, and the state equation of the first converter is generated. When the forward converter switch in the combiner box is turned off and is in the magnetic reset process, the equivalent circuit of the second converter is transformed based on the converter topology, and the state equation of the second converter is generated. When the forward converter switch in the combiner box is turned off and cut off, based on the converter topology, the equivalent circuit of the third converter is transformed, and the state equation of the third converter is generated. According to the traditional state-space averaging method, the state equations of the first converter, the second converter, and the third converter are averaged to obtain the first state-space average equation of the combiner box forward converter. A first averaging model is formed based on the equivalent circuits of the first, second, and third converters, as well as the first state-space averaging equation. The first averaging model switches between different equivalent circuits according to the switching state of the combiner box forward converter: when the combiner box forward converter switch is on, the first averaging model consists of the first converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and in the magnetic reset process, the first averaging model consists of the second converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and the magnetic reset process ends, the first averaging model consists of the third converter equivalent circuit and the first state-space averaging equation.
[0007] Furthermore, the first state-space average equation satisfies the following condition: ; In the formula, L is the inductance value, L m Here, c is the magnetizing inductance, R is the capacitance, n is the parallel resistance, and i is the transformer turns ratio. L (t) represents the inductor current, v o (t) represents the output voltage, i Lm (t) represents the magnetizing inductor current, d1(t) is the auxiliary switching function, and v g d(t) is the input power supply voltage, d(t) is the switching function, and v c (t) represents the capacitor voltage.
[0008] Furthermore, the step of averaging the DC-DC circuit to obtain a second averaged model of the DC-DC circuit includes: Obtain the first circuit topology of the DC-DC circuit and determine the switching state of the DC-DC circuit; wherein, the switching state of the DC-DC circuit includes: the DC-DC circuit switch is on and the DC-DC circuit switch is off. When the DC-DC circuit switch is turned on, based on the first circuit topology, the equivalent circuit of the first front-end circuit is transformed, and the state equation of the first front-end circuit is generated. When the DC-DC circuit switch is turned off, based on the first circuit topology, the equivalent circuit of the second pre-stage circuit is transformed, and the state equation of the second pre-stage circuit is generated. According to the traditional state-space averaging method, the state equations of the first and second pre-stage circuits are averaged to obtain the second state-space average equation of the DC-DC circuit. A second averaging model is formed based on the equivalent circuits of the first and second pre-stage circuits and the second state-space averaging equation. The second averaging model switches between different equivalent circuits according to the switching state of the DC-DC circuit: when the DC-DC circuit is on, the second averaging model is the equivalent circuit of the first pre-stage circuit and the second state-space averaging equation; when the DC-DC circuit is off, the second averaging model is the equivalent circuit of the second pre-stage circuit and the second state-space averaging equation.
[0009] Furthermore, the second state-space average equation satisfies the following condition: ; In the formula, d′(t) is the complementary switching function, and v D For the forward voltage drop of the diode, v C (t) represents the capacitor voltage, i g Where C is the input current and C is the capacitance value.
[0010] Furthermore, the step of averaging the DC-AC circuit to obtain a third averaged model of the DC-AC circuit includes: For each switch in the DC-AC circuit, a corresponding switching function is constructed, and based on each switching function, an averaging process is performed to obtain the third state-space average equation of the DC-AC circuit. Based on the third state-space average equation, the equivalent circuit of the DC-AC circuit is determined. Based on the equivalent circuit of the subsequent stage and the third state-space averaging equation, the third averaging model of the DC-AC circuit is determined.
[0011] Furthermore, the third state-space average equation satisfies the following condition: ; In the formula, i d (t) represents the direct-axis current component in the dq coordinate system, i q (t) represents the quadrature-axis current component in the dq coordinate system, v d (t) represents the direct-axis voltage component in the dq coordinate system, vq (t) represents the quadrature-axis voltage component in the dq coordinate system, v DC (t) represents the DC-side bus voltage; D d (t) represents the duty cycle of the direct-axis modulated signal in the dq coordinate system, D q (t) is the duty cycle of the quadrature-axis modulation signal in the dq coordinate system; L is the inductance of each phase on the AC side, 3L is the total inductance of the three phases; C is the filter capacitor on the DC side; ω is the system angular frequency; 1 / (3L) is the conversion factor related to the three-phase inductance, and 1 / C is the current-voltage relationship coefficient of the DC side capacitor.
[0012] Another embodiment of the present invention provides a data processing device for distributed photovoltaic grid connection, including: a data acquisition module, a modeling module, and a result generation module; The data acquisition module is used to acquire the operating data of the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit of the distributed photovoltaic grid-connected system; wherein, the distributed photovoltaic grid-connected system includes: a combiner box forward converter, a DC-DC circuit, and a DC-AC circuit; The modeling module is used to perform average modeling on the combiner box forward converter to obtain a first average model of the combiner box forward converter; to perform average modeling on the DC-DC circuit to obtain a second average model of the DC-DC circuit; and to perform average modeling on the DC-AC circuit to obtain a third average model of the DC-AC circuit. The result generation module is used to perform simulations based on the operating data of the combiner box forward converter and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model, and to obtain the state detection results of the distributed photovoltaic grid-connected system based on the simulation results of each averaging model.
[0013] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the distributed photovoltaic grid-connected data processing method provided by the present invention.
[0014] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the distributed photovoltaic grid-connected data processing method provided by the present invention.
[0015] The following benefits can be obtained by implementing the present invention: This invention discloses a data processing method for distributed photovoltaic (PV) grid-connected systems. The method involves acquiring operating data of the combiner box forward converter, DC-DC circuit, and DC-AC circuit within the distributed PV grid-connected system. The distributed PV grid-connected system includes a combiner box forward converter, a DC-DC circuit, and a DC-AC circuit. The method performs averaging modeling on the combiner box forward converter to obtain a first averaging model; it also performs averaging modeling on the DC-DC circuit to obtain a second averaging model; and it performs averaging modeling on the DC-AC circuit to obtain a third averaging model. Simulations are then performed based on the combiner box forward converter operating data and the first averaging model, the DC-DC circuit operating data and the second averaging model, and the DC-AC circuit operating data and the third averaging model. Based on the simulation results of each averaging model, the state detection results of the distributed PV grid-connected system are obtained. This invention performs averaging modeling on distributed photovoltaic grid-connected systems. By simulating the obtained operating data of the combiner box forward converter, DC-DC circuit, and DC-AC circuit with the constructed first, second, and third averaging models, the state detection results are obtained, thus realizing the automation of state detection of distributed photovoltaic grid-connected systems and greatly improving the efficiency of state detection of distributed photovoltaic grid-connected systems. Attached Figure Description
[0016] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 This is a schematic flowchart of a data processing method for distributed photovoltaic grid connection provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a distributed photovoltaic grid-connected data processing device provided in an embodiment of the present invention; Figure 3 This is a topology schematic diagram of a combiner box forward converter provided in an embodiment of the present invention; Figure 4 This is the first converter equivalent circuit of a combiner box forward converter provided in an embodiment of the present invention; Figure 5 This is the second converter equivalent circuit of the combiner box forward converter provided in one embodiment of the present invention; Figure 6This is the third converter equivalent circuit of a combiner box forward converter provided in one embodiment of the present invention; Figure 7 This is a first averaging circuit diagram of a combiner box forward converter provided in an embodiment of the present invention; Figure 8 This is a Buck-Boost circuit topology and equivalent circuits for each stage provided in an embodiment of the present invention; Figure 9 This is an embodiment of the Buck-Boost averaging equivalent circuit provided by the present invention; Figure 10 This is a schematic diagram of a three-phase inverter topology provided in an embodiment of the present invention; Figure 11 This is an embodiment of the present invention providing an equivalent circuit for averaging a three-phase inverter in the abc rectangular coordinate system; Figure 12 This is an embodiment of the present invention providing an equivalent circuit for averaging a three-phase inverter in the dq rotating coordinate system; Figure 13 This is a comparison of the simulation results of the grid-connected point output current of the refined model and the averaged model under normal operating conditions provided in an embodiment of the present invention. Figure 14 This is a comparison of the Ddc simulation results of the refined model and the averaged model under normal operating conditions provided in an embodiment of the present invention. Figure 15 This is a comparison of the simulation results of the grid-connected point output power of the refined model and the averaged model under normal operating conditions provided in an embodiment of the present invention. Figure 16 This is a comparison of the simulation results of the grid-connected point output current of the refined model and the averaged model under light intensity change provided in an embodiment of the present invention. Figure 17 This is a comparison of the Ddc simulation results of the refined model and the averaged model under light intensity changes provided in an embodiment of the present invention. Figure 18 This is a comparison of the simulation results of the grid-connected point output power of the refined model and the averaged model under light intensity change provided in an embodiment of the present invention; Figure 19 This is a comparison of the simulation results of the grid-connected point output current of the refined model and the averaged model under low voltage ride-through fault provided in an embodiment of the present invention. Figure 20 This is a comparison of the Ddc simulation results of the refined model and the averaged model under low voltage ride-through fault provided in an embodiment of the present invention. Figure 21 This is a comparison of the simulation results of the grid-connected point output power of the refined model and the averaged model under low voltage ride-through fault provided in an embodiment of the present invention. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.
[0020] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.
[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0022] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.
[0023] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).
[0024] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.
[0025] See Figure 1 To address the problem of low efficiency in status detection of existing distributed photovoltaic grid-connected systems, an embodiment of the present invention provides a data processing method for distributed photovoltaic grid connection, comprising: 101. Obtain the operating data of the forward converter in the combiner box, the operating data of the DC-DC circuit, and the operating data of the DC-AC circuit in the distributed photovoltaic grid-connected system; wherein, the distributed photovoltaic grid-connected system includes: the forward converter in the combiner box, the DC-DC circuit, and the DC-AC circuit.
[0026] 102. Perform average modeling on the combiner box forward converter to obtain the first average model of the combiner box forward converter; perform average modeling on the DC-DC circuit to obtain the second average model of the DC-DC circuit; perform average modeling on the DC-AC circuit to obtain the third average model of the DC-AC circuit.
[0027] In this embodiment, the step of averaging the combiner box forward converter to obtain a first averaged model of the combiner box forward converter includes: Obtain the converter topology of the combiner box forward converter and determine the switching state of the combiner box forward converter; wherein, the switching state of the combiner box forward converter includes: the combiner box forward converter switch is on, the combiner box forward converter switch is off and in the magnetic reset process, and the combiner box forward converter switch is off and the magnetic reset is completed. When the forward converter switch in the combiner box is turned on, the equivalent circuit of the first converter is transformed based on the converter topology, and the state equation of the first converter is generated. When the forward converter switch in the combiner box is turned off and is in the magnetic reset process, the equivalent circuit of the second converter is transformed based on the converter topology, and the state equation of the second converter is generated. When the forward converter switch in the combiner box is turned off and cut off, based on the converter topology, the equivalent circuit of the third converter is transformed, and the state equation of the third converter is generated. According to the traditional state-space averaging method, the state equations of the first converter, the second converter, and the third converter are averaged to obtain the first state-space average equation of the combiner box forward converter. A first averaging model is formed based on the equivalent circuits of the first, second, and third converters, as well as the first state-space averaging equation. The first averaging model switches between different equivalent circuits according to the switching state of the combiner box forward converter: when the combiner box forward converter switch is on, the first averaging model consists of the first converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and in the magnetic reset process, the first averaging model consists of the second converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and the magnetic reset process ends, the first averaging model consists of the third converter equivalent circuit and the first state-space averaging equation.
[0028] In this embodiment, the first state-space average equation satisfies the following condition: ; In the formula, L is the inductance value, L m Here, c is the magnetizing inductance, R is the capacitance, n is the parallel resistance, and i is the transformer turns ratio. L (t) represents the inductor current, v o (t) represents the output voltage, i Lm (t) represents the magnetizing inductor current, d1(t) is the auxiliary switching function, and v g d(t) is the input power supply voltage, d(t) is the switching function, and v c (t) represents the capacitor voltage.
[0029] In one specific embodiment, firstly, a first averaged model of the combiner box forward converter is established using the traditional state-space averaging method. The forward converter topology is then averaged and modeled using the traditional state-space averaging method, yielding the first state-space averaged equation and the averaged equivalent circuit diagram of the forward converter.
[0030] Taking the RCD clamped forward converter (i.e., the combiner box forward converter described in this invention) as an example, its converter topology is as follows: Figure 3 As shown, its working process can be divided into two stages: switch on and switch off. During the switch off period, there are two stages: magnetic reset and cut-off.
[0031] During the switch-on period, its first converter equivalent circuit is as follows: Figure 4 As shown, the conduction time is dT s ,according to Figure 4 The first converter state equation during the switch-on period is: ; In the formula v L (t) and v Lm (t) represents the inductance voltages on the secondary and primary sides, respectively, i c (t) represents the current across the capacitor.
[0032] Write the voltage expression for the magnetizing inductor, and since i L (t)=ni Lm Therefore, simplifying the equation, we get the following equation: ; When the switch is turned off, the magnetic reset phase begins, lasting for (1-d-d1)T. s The equivalent circuit of the second converter is as follows: Figure 5 As shown.
[0033] At this point, the secondary side forms an independent loop, according to... Figure 5 The state equations for the second converter can be established as follows: ; If the primary side is magnetically reset, then: ; At cutoff, the equivalent circuit of the third converter is as follows: Figure 6 As shown, the duration d1T s .
[0034] For the primary side, there is no longer any excitation current, so the state equation of the third converter is: ; Based on the state equations of the first, second, and third converters, and following the principle of the traditional state-space averaging method, the inductor voltage, capacitor current, and magnetizing inductor voltage are calculated using weighted averages, yielding: Therefore, the first state-space average equation of the combiner box forward converter is obtained: In steady state, the average values of the inductor current and capacitor voltage are both zero over one cycle. The averaged equivalent circuit diagram is shown below. Figure 7 As shown.
[0035] In this embodiment, the step of averaging the DC-DC circuit to obtain a second averaged model of the DC-DC circuit includes: Obtain the first circuit topology of the DC-DC circuit and determine the switching state of the DC-DC circuit; wherein, the switching state of the DC-DC circuit includes: the DC-DC circuit switch is turned on and the first DC-DC circuit switch is turned off. When the DC-DC circuit switch is turned on, based on the first circuit topology, the equivalent circuit of the first front-end circuit is transformed, and the state equation of the first front-end circuit is generated. When the DC-DC circuit switch is turned off, based on the first circuit topology, the equivalent circuit of the second pre-stage circuit is transformed, and the state equation of the second pre-stage circuit is generated. According to the traditional state-space averaging method, the state equations of the first and second pre-stage circuits are averaged to obtain the second state-space average equation of the DC-DC circuit. A second averaging model is formed based on the equivalent circuits of the first and second pre-stage circuits and the second state-space averaging equation. The second averaging model switches between different equivalent circuits according to the switching state of the DC-DC circuit: when the DC-DC circuit is on, the second averaging model is the equivalent circuit of the first pre-stage circuit and the second state-space averaging equation; when the DC-DC circuit is off, the second averaging model is the equivalent circuit of the second pre-stage circuit and the second state-space averaging equation.
[0036] In this embodiment, the second state-space average equation satisfies the following condition: ; In the formula, d′(t) is the complementary switching function, and v D For the forward voltage drop of the diode, v C (t) represents the capacitor voltage, i g Where C is the input current and C is the capacitance value.
[0037] In one specific embodiment, an averaged model of the preceding DC-DC circuit (i.e., the DC-DC circuit described in this invention) is established using the conventional state-space averaging method. By using the conventional state-space averaging method, the preceding DC-DC circuit is modeled using averaging, resulting in the state-space averaging equation and the averaged equivalent circuit diagram of the preceding DC-DC circuit.
[0038] Taking the Buck-Boost circuit as an example, the first circuit topology is as follows: Figure 8 As shown in (a); the equivalent circuit of the first pre-stage circuit during the switch-on phase is as follows: Figure 8 As shown in (b); the equivalent circuit of the second pre-stage circuit during the switch-off phase is as follows: Figure 8 As shown in (c).
[0039] The state variable in this circuit is defined as the state-independent inductor current i.L and capacitor voltage v C Input variables include the circuit's input voltage v. g The equivalent voltage source of the diode v D The output variable is defined as the input current i. g .
[0040] When the switch is turned on, that is, according to Figure 8 (b) The state equation of the first pre-stage circuit is: Extract the parameter matrix from the above formula: When the switch is off, that is, according to Figure 8 (c) State equations of the second pre-stage circuit: Therefore, the parameter matrix for the second stage is obtained, as shown in the following equation: According to the traditional state-space averaging method, the two stages of switch conduction (conduction time d) and switch cutoff (cutoff time d') are averaged: Therefore, the second state-space averaging equation for the Buck-Boost circuit is: Output equation: Averaged equivalent circuit diagram as follows Figure 9 As shown.
[0041] In this embodiment, the step of averaging the DC-AC circuit to obtain a third averaged model of the DC-AC circuit includes: For each switch in the DC-AC circuit, a corresponding switching function is constructed, and based on each switching function, an averaging process is performed to obtain the third state-space average equation of the DC-AC circuit. Based on the third state-space average equation, the equivalent circuit of the DC-AC circuit is determined. Based on the equivalent circuit of the subsequent stage and the third state-space averaging equation, the third averaging model of the DC-AC circuit is determined.
[0042] In this embodiment, the third state-space average equation satisfies the following condition: ; In the formula, i d(t) represents the direct-axis current component in the dq coordinate system, i q (t) represents the quadrature-axis current component in the dq coordinate system, v d (t) represents the direct-axis voltage component in the dq coordinate system, v q (t) represents the quadrature-axis voltage component in the dq coordinate system, v DC (t) represents the DC-side bus voltage; D d (t) represents the duty cycle of the direct-axis modulated signal in the dq coordinate system, D q (t) is the duty cycle of the quadrature-axis modulation signal in the dq coordinate system; L is the inductance of each phase on the AC side, 3L is the total inductance of the three phases; C is the filter capacitor on the DC side; ω is the system angular frequency; 1 / (3L) is the conversion factor related to the three-phase inductance, and 1 / C is the current-voltage relationship coefficient of the DC side capacitor.
[0043] In one specific embodiment, an averaged model of the subsequent DC-AC circuit (i.e., the DC-AC circuit described in this invention) is established using an improved state-space averaging method based on the piecewise principle. By using the improved state-space averaging method based on the piecewise principle, the subsequent DC-AC circuit is modeled using averaging, resulting in the state-space averaging equation and the averaged equivalent circuit diagram of the subsequent DC-AC circuit.
[0044] Taking a three-phase inverter as an example, the topology of a DC-AC circuit is as follows: Figure 10 As shown.
[0045] Since the switching on and off in an inverter requires coordination, the traditional state-space weighted average analysis method is insufficient to describe its dynamic performance in detail. Therefore, it is necessary to establish a piecewise state-space average equation based on a piecewise constant function Di with a large step size.
[0046] Switching functions are established for Sa1, Sa2, Sb1, Sb2, Sc1, and Sc2 respectively. To ensure that two switches in the same bridge arm do not conduct simultaneously and cause a short circuit on the DC side, only one switch in each phase is conducted during the switching cycle. Si is defined as follows: In the formula, Si represents the switching function of each phase, and Si1 and Si2 are the switching functions of the upper half-bridge and the lower half-bridge, respectively. When S=1, the switch is on; when S=0, the switch is off.
[0047] according to Figure 10 The relationship between the input and output sides of the three-phase inverter topology can be represented by the switching function described above, as shown below: In the formula, Sab, Sbc, and Sca are the line switching functions corresponding to the line voltages vab, vbc, and vca, respectively.
[0048] Similarly, the relationship between phase current and DC side current can be written out: Therefore, the following state equation applies to the DC side: After adding the switching function and output inductor to the AC side, according to Figure 10 The state equations of the line voltages at the inverter output can be expressed by the characteristic equation of the output inductor: Rearranging the above equation, we get: Therefore, the state equation model of a three-phase inverter during one circuit switching cycle can be derived: Since the switching function is a discontinuous function, it needs to be linearized. A piecewise duty cycle function is defined for the three-phase inverter switching function: Combining the above equation, the state equation model of the three-phase inverter within one circuit switching cycle is averaged to obtain the state-space average model of the three-phase inverter: Based on the above derivation, the averaged equivalent circuit of the three-phase inverter is as follows: Figure 11 As shown.
[0049] The variables in the three-phase stationary coordinate system are transformed into variables in the dq coordinate system rotating at the fundamental frequency. The rotation transformation matrix is shown below: Therefore, the third state-space average model of a three-phase inverter can be transformed into an expression in the dq coordinate system, ignoring the 0-axis component: Based on the above formula, the averaged equivalent circuit of the three-phase inverter in the dq coordinate system is obtained, such as... Figure 12 As shown.
[0050] Based on the above scheme, a distributed photovoltaic grid-connected averaging modeling method was constructed. Simulation verification shows that the averaging model established by the proposed method can maintain accuracy under different operating conditions, such as normal operation, sudden changes in light intensity, and low voltage ride-through faults, and can be approximately equivalent to the refined model, while the simulation speed is greatly improved.
[0051] 103. Simulations are performed based on the operating data of the forward converter in the combiner box and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model. Based on the simulation results of each averaging model, the state detection results of the distributed photovoltaic grid-connected system are obtained.
[0052] In a specific embodiment, a refined model and an averaged model were built in Matlab / Simulink, with simulation step sizes set to 1e-6s and 5e-5s, respectively. The parameters were set as follows: number of photovoltaic modules 45, photovoltaic array operating output voltage 15×39.67V, photovoltaic array operating output current 3×5.37A, photovoltaic array maximum power 45×213.15W, inverter AC side maximum rated output power 10kVA, inverter DC side maximum rated voltage 1000V, inverter maximum AC output current 25A, and inverter DC side maximum input power 12000W.
[0053] For a comparison of the simulation results of the two models under normal operating conditions (light intensity of 900 W / m2 and temperature of 25℃), please refer to [link / reference]. Figure 13 , 14 15.
[0054] For a comparison of the simulation results of the two models when the light intensity changes (the light intensity decreases from 1000W / m2 to 800W / m2 in 0.5s), please refer to [link / reference]. Figure 16 , 17 18.
[0055] For a comparison of simulation results between the two models during low-voltage ride-through faults, see [link to simulation results]. Figure 19 , 20 ,twenty one.
[0056] The simulation results above show that the averaging model can approximate the refinement model in terms of accuracy.
[0057] The simulation step size for both models was set to 1e-6s, and the simulation times of the two models under different operating conditions were compared: Under normal operating conditions, the simulation time for the refined model was 88.54s, and the simulation time for the averaged model was 15.56s; when the light intensity changed abruptly, the simulation time for the refined model was 86.67s, and the simulation time for the averaged model was 14.45s; when the low voltage ride-through occurred, the simulation time for the refined model was 97.23s, and the simulation time for the averaged model was 18.07s.
[0058] The simulation time comparison shows that the averaged model significantly reduces the simulation time, achieving rapid simulation.
[0059] like Figure 2As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; One embodiment of the present invention provides a data processing device for distributed photovoltaic grid connection, including: a data acquisition module 201, a modeling module 202, and a result generation module 203; The data acquisition module is used to acquire the operating data of the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit of the distributed photovoltaic grid-connected system; wherein, the distributed photovoltaic grid-connected system includes: a combiner box forward converter, a DC-DC circuit, and a DC-AC circuit; The modeling module is used to perform average modeling on the combiner box forward converter to obtain a first average model of the combiner box forward converter; to perform average modeling on the DC-DC circuit to obtain a second average model of the DC-DC circuit; and to perform average modeling on the DC-AC circuit to obtain a third average model of the DC-AC circuit. The result generation module is used to perform simulations based on the operating data of the combiner box forward converter and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model, and to obtain the state detection results of the distributed photovoltaic grid-connected system based on the simulation results of each averaging model.
[0060] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the distributed photovoltaic grid-connected data processing method provided by any of the above-described method embodiments of the present invention.
[0061] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.
[0062] Based on the above embodiments of the distributed photovoltaic grid-connected data processing method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the distributed photovoltaic grid-connected data processing method of any embodiment of the present invention.
[0063] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.
[0064] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.
[0065] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.
[0066] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the distributed photovoltaic grid-connected data processing method described in any of the above-described method embodiments of the present invention.
[0067] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.
[0068] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.
Claims
1. A data processing method for distributed photovoltaic grid connection, characterized in that, include: To acquire the operating data of the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit of the distributed photovoltaic grid-connected system; wherein the distributed photovoltaic grid-connected system includes: the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit; The combiner box forward converter is modeled by averaging to obtain the first averaged model of the combiner box forward converter; the DC-DC circuit is modeled by averaging to obtain the second averaged model of the DC-DC circuit; and the DC-AC circuit is modeled by averaging to obtain the third averaged model of the DC-AC circuit. Simulations were performed based on the operating data of the combiner box forward converter and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model. Based on the simulation results of each averaging model, the state detection results of the distributed photovoltaic grid-connected system were obtained.
2. The data processing method for distributed photovoltaic grid connection as described in claim 1, characterized in that, The step of averaging the forward converter of the combiner box to obtain the first averaged model of the forward converter of the combiner box includes: Obtain the converter topology of the combiner box forward converter and determine the switching state of the combiner box forward converter; wherein, the switching state of the combiner box forward converter includes: the combiner box forward converter switch is on, the combiner box forward converter switch is off and in the magnetic reset process, and the combiner box forward converter switch is off and the magnetic reset is completed. When the forward converter switch in the combiner box is turned on, the equivalent circuit of the first converter is transformed based on the converter topology, and the state equation of the first converter is generated. When the forward converter switch in the combiner box is turned off and is in the magnetic reset process, the equivalent circuit of the second converter is transformed based on the converter topology, and the state equation of the second converter is generated. When the forward converter switch in the combiner box is turned off and cut off, based on the converter topology, the equivalent circuit of the third converter is transformed, and the state equation of the third converter is generated. According to the traditional state-space averaging method, the state equations of the first converter, the second converter, and the third converter are averaged to obtain the first state-space average equation of the combiner box forward converter. A first averaging model is formed based on the equivalent circuits of the first, second, and third converters, as well as the first state-space averaging equation. The first averaging model switches between different equivalent circuits according to the switching state of the combiner box forward converter: when the combiner box forward converter switch is on, the first averaging model consists of the first converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and in the magnetic reset process, the first averaging model consists of the second converter equivalent circuit and the first state-space averaging equation; when the combiner box forward converter switch is off and the magnetic reset process ends, the first averaging model consists of the third converter equivalent circuit and the first state-space averaging equation.
3. The data processing method for distributed photovoltaic grid connection as described in claim 2, characterized in that, The first state-space average equation satisfies the following condition: ； In the formula, L is the inductance value, L m Here, c is the magnetizing inductance, R is the capacitance, n is the parallel resistance, and i is the transformer turns ratio. L (t) represents the inductor current, v o (t) represents the output voltage, i Lm (t) represents the magnetizing inductor current, d1(t) is the auxiliary switching function, and v g d(t) is the input power supply voltage, d(t) is the switching function, and v c (t) represents the capacitor voltage.
4. The data processing method for distributed photovoltaic grid connection as described in claim 3, characterized in that, The step of averaging the DC-DC circuit to obtain a second averaged model of the DC-DC circuit includes: Obtain the first circuit topology of the DC-DC circuit and determine the switching state of the DC-DC circuit; wherein, the switching state of the DC-DC circuit includes: the DC-DC circuit switch is on and the DC-DC circuit switch is off. When the DC-DC circuit switch is turned on, based on the first circuit topology, the equivalent circuit of the first front-end circuit is transformed, and the state equation of the first front-end circuit is generated. When the DC-DC circuit switch is turned off, based on the first circuit topology, the equivalent circuit of the second pre-stage circuit is transformed, and the state equation of the second pre-stage circuit is generated. According to the traditional state-space averaging method, the state equations of the first and second pre-stage circuits are averaged to obtain the second state-space average equation of the DC-DC circuit. A second averaging model is formed based on the equivalent circuits of the first and second pre-stage circuits and the second state-space averaging equation. The second averaging model switches between different equivalent circuits according to the switching state of the DC-DC circuit: when the DC-DC circuit is on, the second averaging model is the equivalent circuit of the first pre-stage circuit and the second state-space averaging equation; when the DC-DC circuit is off, the second averaging model is the equivalent circuit of the second pre-stage circuit and the second state-space averaging equation.
5. The data processing method for distributed photovoltaic grid connection as described in claim 4, characterized in that, The second state-space average equation satisfies the following condition: ； In the formula, d′(t) is the complementary switching function, and v D Forward voltage drop of the diode, v C (t) represents the capacitor voltage, i g Where C is the input current and C is the capacitance value.
6. The data processing method for distributed photovoltaic grid connection as described in claim 5, characterized in that, The step of averaging the DC-AC circuit to obtain a third averaged model of the DC-AC circuit includes: For each switch in the DC-AC circuit, a corresponding switching function is constructed, and based on each switching function, an averaging process is performed to obtain the third state-space average equation of the DC-AC circuit. Based on the third state-space average equation, the equivalent circuit of the DC-AC circuit is determined. Based on the equivalent circuit of the subsequent stage and the third state-space averaging equation, the third averaging model of the DC-AC circuit is determined.
7. The data processing method for distributed photovoltaic grid connection as described in claim 6, characterized in that, The third state-space average equation satisfies the following condition: ； In the formula, i d (t) represents the direct-axis current component in the dq coordinate system, i q (t) represents the quadrature-axis current component in the dq coordinate system, v d (t) represents the direct-axis voltage component in the dq coordinate system, v q (t) represents the quadrature-axis voltage component in the dq coordinate system, v DC (t) represents the DC-side bus voltage; D d (t) represents the duty cycle of the direct-axis modulated signal in the dq coordinate system, D q (t) is the duty cycle of the quadrature-axis modulation signal in the dq coordinate system; L is the inductance of each phase on the AC side, 3L is the total inductance of the three phases; C is the filter capacitor on the DC side; ω is the system angular frequency; 1 / (3L) is the conversion factor related to the three-phase inductance, and 1 / C is the current-voltage relationship coefficient of the DC side capacitor.
8. A data processing device for distributed photovoltaic grid connection, characterized in that, include: Data acquisition module, modeling module, and result generation module; The data acquisition module is used to acquire the operating data of the combiner box forward converter, the DC-DC circuit, and the DC-AC circuit of the distributed photovoltaic grid-connected system; wherein, the distributed photovoltaic grid-connected system includes: a combiner box forward converter, a DC-DC circuit, and a DC-AC circuit; The modeling module is used to perform average modeling on the combiner box forward converter to obtain a first average model of the combiner box forward converter; to perform average modeling on the DC-DC circuit to obtain a second average model of the DC-DC circuit; and to perform average modeling on the DC-AC circuit to obtain a third average model of the DC-AC circuit. The result generation module is used to perform simulations based on the operating data of the combiner box forward converter and the first averaging model, the operating data of the DC-DC circuit and the second averaging model, and the operating data of the DC-AC circuit and the third averaging model, and to obtain the state detection results of the distributed photovoltaic grid-connected system based on the simulation results of each averaging model.
9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the distributed photovoltaic grid-connected data processing method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the distributed photovoltaic grid-connected data processing method as described in any one of claims 1-7.