Optical storage system fine-grained decoupling simulation solving method, system, device and medium

Abstract

The application relates to the technical field of electromagnetic simulation, and discloses a light storage system fine-grained decoupling simulation solving method, system, equipment and medium. The method is characterized in that: the electromagnetic transient simulation modeling is carried out on multiple elements in the light storage system, the electromagnetic transient simulation model of the light storage system is constructed, the electromagnetic transient simulation model of the light storage system is layered, the fine-grained decoupling network after layering is carried out, the multi-thread parallel simulation solving of the electromagnetic transient simulation decoupling model of the light storage system is carried out based on a multi-thread CPU, the flexible network division is realized, the calculation amount of the large-scale light storage system is reduced, the large-scale light storage system conflict-free parallel simulation scheme and simulation process are established, the simulation efficiency is improved under the premise of ensuring the simulation precision, and the method is suitable for solving the simulation large-scale light storage system.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic simulation technology, and in particular to a fine-grained decoupling simulation solution method, system, equipment, and medium for photovoltaic-storage systems. Background Technology

[0002] The rapid development of technology in today's society has led to a continuous increase in energy demand, and the widespread grid connection of photovoltaic (PV) power generation units is a future development trend. However, the fluctuation of PV unit output power has gradually reduced grid stability. To address the issue of unstable PV unit output power, PV-energy storage systems have emerged.

[0003] Based on the different methods of power conversion, current mainstream energy storage technologies can be divided into chemical energy storage, mechanical energy storage, and electromagnetic energy storage. Among them, chemical energy storage is currently the most mature technology, which has become an important supplement to photovoltaic power generation units.

[0004] Because photovoltaic (PV) and energy storage systems contain numerous power electronic devices and the switching frequency of converters is gradually increasing, accurate simulation of these systems requires smaller simulation step sizes. However, reducing the step size significantly decreases simulation efficiency. This makes efficient and high-precision simulation of large-scale PV and energy storage systems a challenge, and places higher demands on simulation platforms with limited computing resources.

[0005] Therefore, existing solutions can be mainly divided into two aspects: research on modeling efficient and high-precision photovoltaic energy storage systems and research on accelerating hardware solutions.

[0006] In the modeling of photovoltaic (PV) and energy storage (ESS) systems, some studies take simplified modeling of PV power generation units as a starting point, significantly simplifying the parameter calculation of PV cells. However, simplified models have low accuracy and cannot reflect detailed information about the PV array, thus failing to meet the accuracy standards of some engineering projects. Other studies use mature modeling methods for typical modular devices such as power electronic components and transformers to model PV-ESS systems, including average value models, decoupled network models, and Thevenin equivalent models. Among them, the average value model improves the solution efficiency by averaging the trigger signal; however, the average value model cannot reflect the operating state of the switching transistors, resulting in low simulation accuracy and a narrow application range. Thevenin models reduce the computational load in the solution process by eliminating model nodes and preprocessing the model to be solved. However, PV-ESS power plants have numerous power electronic devices, and if the Thevenin modeling method is used, massive amounts of data need to be pre-stored, placing high demands on hardware storage resources. The decoupled network modeling method can improve the solution efficiency of the model while ensuring simulation accuracy; however, there is limited research on existing decoupled network simulation methods for PV-ESS systems.

[0007] Researchers and manufacturers have explored hardware-accelerated solution algorithms from multiple perspectives. To simulate small-scale renewable energy power plants on a single FPGA, researchers proposed a spatiotemporal parallel simulation architecture, achieving real-time simulation of 13 renewable energy power generation units. On the manufacturer side, RTDS, a company that developed commercial real-time simulators, developed a synchronous multi-rate algorithm based on the Superstep and Substep strategies, improving its simulation capabilities for large-scale power systems. To achieve electromagnetic transient simulation of large-scale systems, researchers used the Linux operating system and ultra-high-speed networks, combining multiple CPUs and FPGAs into a computing cluster; however, this approach is costly and lacks flexibility. Furthermore, due to the numerous power electronic components in large-scale photovoltaic-storage systems, this method requires a large number of processors, resulting in expensive simulation platforms. At the same time, relying solely on parallel simulation architectures may not be sufficient for efficient simulation of large-scale photovoltaic-storage systems at microsecond-level steps, nor is it sufficient to accurately reproduce the detailed information within the units.

[0008] In summary, existing electromagnetic transient simulation schemes for large-scale photovoltaic-storage systems still suffer from drawbacks such as slow simulation speed, low research level, and difficulty in reflecting the high-frequency characteristics of the system, making it difficult to simulate large-scale photovoltaic-storage systems. Summary of the Invention

[0009] In view of this, the present invention provides a fine-grained decoupled simulation solution method, system, equipment and medium for photovoltaic-storage systems, which solves the technical problems that existing electromagnetic transient simulation schemes for large-scale photovoltaic-storage systems still have slow simulation speed, low research level and difficulty in reflecting the high-frequency characteristics of the system, making it difficult to simulate large-scale photovoltaic-storage systems.

[0010] The first aspect of this invention provides a fine-grained decoupling simulation solution method for a photovoltaic-storage system, comprising:

[0011] Electromagnetic transient simulation modeling is performed on multiple components in the photovoltaic-storage system, and topological connections are made based on the electromagnetic transient simulation models of the multiple components to construct the electromagnetic transient simulation model of the photovoltaic-storage system.

[0012] The electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system of the photovoltaic-storage system are layered, and the inner and outer structures obtained by the layering are decoupled and networked in a fine-grained manner to obtain the electromagnetic transient simulation decoupled model of the photovoltaic-storage system.

[0013] The electromagnetic transient simulation decoupling model of the photovoltaic-storage system is solved by multi-threaded parallel simulation based on a multi-threaded CPU.

[0014] Preferably, the component includes a plurality of basic node components, the basic node components including resistors, inductors and capacitors;

[0015] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes:

[0016] Based on the preset modeling parameters of the basic node elements, the voltage and current equations of the basic node elements between each node in the photovoltaic energy storage system are differentially processed using the back Euler method to obtain the equivalent current of the basic node elements.

[0017] Electromagnetic transient simulation modeling is performed on the basic node element based on the equivalent current of the basic node element.

[0018] Preferably, the element includes a core component, and the core component includes a photovoltaic array;

[0019] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes:

[0020] Electromagnetic transient simulation models of multiple photovoltaic cells in the photovoltaic array are performed using a single diode equivalent model to obtain the electromagnetic transient simulation models of each photovoltaic cell.

[0021] Based on the topology of the multiple photovoltaic cells in the photovoltaic array, the electromagnetic transient simulation models of each photovoltaic cell are topologically connected to construct the electromagnetic transient simulation model of the photovoltaic array.

[0022] Preferably, the element includes a core component, which includes a transformer;

[0023] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes:

[0024] The transformer is modeled using a T-type equivalent circuit to obtain an equivalent model of the transformer.

[0025] Determine the equivalent electromagnetic transient simulation circuit of the transformer based on the type of transformer;

[0026] If the transformer is a single-phase two-winding transformer, the voltage and current equations of the basic node elements in the equivalent model of the transformer are discretized to obtain the equivalent calculation circuit for the electromagnetic transient simulation of the single-phase two-winding transformer.

[0027] If the transformer is a three-phase transformer, then the equivalent calculation circuit for the electromagnetic transient simulation of each phase of the three-phase transformer is determined, and the equivalent calculation circuit for the electromagnetic transient simulation of each phase of the transformer is connected to form the equivalent calculation circuit for the electromagnetic transient simulation of the three-phase transformer.

[0028] Electromagnetic transient simulation of the transformer is performed based on the equivalent calculation circuit of the equivalent model of the transformer.

[0029] Preferably, the component includes a core component, which includes a converter, an energy storage battery, a filter, and a transmission line;

[0030] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes:

[0031] The converter is modeled using a switching function model;

[0032] A simplified model of a voltage source and a resistor in parallel is used to perform an equivalent modeling of the energy storage battery.

[0033] The filter is modeled using a π-type LCL branch;

[0034] The transmission line is modeled using a lumped parameter line model.

[0035] Preferably, the process of layering the electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system, and performing fine-grained decoupling and networking on the inner and outer structures obtained from the layering to obtain the electromagnetic transient simulation decoupling model of the photovoltaic-storage system, includes:

[0036] The electromagnetic transient simulation model of the photovoltaic energy storage system and the corresponding current collection system are layered to obtain an inner structure and an outer structure. The inner structure includes the various components of the photovoltaic energy storage system, and the outer structure includes the current collection system.

[0037] The decoupling nodes of the outer structure are decoupled, including the common connection node connecting the optical storage system and the collection line, and the connection node between the collection line and the transformer on the long-distance transmission line.

[0038] The controlled source decoupling method and the one-step delay decoupling method are used to decouple and network each element of the inner structure;

[0039] By connecting the decoupled inner and outer structures, an electromagnetic transient simulation decoupling model of the photovoltaic energy storage system is obtained.

[0040] Preferably, the multi-threaded parallel simulation solution of the electromagnetic transient simulation decoupling model of the photovoltaic-storage system based on a multi-threaded CPU includes:

[0041] The parameters of each component of the photovoltaic storage system and the node voltages of each subnet of the photovoltaic storage system are initialized based on the network topology of the electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[0042] Determine the communication variables between subnets based on the state variables of each subnet;

[0043] The connection variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is assigned to a thread in a multi-threaded CPU to perform multi-threaded parallel simulation and solution for each subnet.

[0044] Secondly, the present invention also provides a fine-grained decoupling simulation solution system for a photovoltaic-storage system, comprising:

[0045] The simulation modeling module is used to perform electromagnetic transient simulation modeling on multiple components in the photovoltaic-storage system, and to construct the electromagnetic transient simulation model of the photovoltaic-storage system by performing topological connections based on the electromagnetic transient simulation models of the multiple components.

[0046] The layered decoupling module is used to layer the electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system of the photovoltaic-storage system, and to perform fine-grained decoupling and networking on the inner and outer structures obtained by layering, so as to obtain the electromagnetic transient simulation decoupling model of the photovoltaic-storage system.

[0047] The simulation solution module is used to perform multi-threaded parallel simulation solutions on the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

[0048] Thirdly, the present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the fine-grained decoupling simulation solution method for the optical storage system as described in the first aspect.

[0049] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the steps of the fine-grained decoupling simulation solution method for the optical storage system as described in the first aspect.

[0050] As can be seen from the above technical solutions, this invention constructs an electromagnetic transient simulation model of the photovoltaic-storage system by performing electromagnetic transient simulation modeling on multiple components within the system. The electromagnetic transient simulation model is then layered and fine-grained decoupling and networking are performed after layering. Based on a multi-threaded CPU, the decoupled electromagnetic transient simulation model of the photovoltaic-storage system is solved in parallel using multi-threaded simulation. This achieves flexible networking, reducing the computational load of large-scale photovoltaic-storage systems. Furthermore, by establishing a conflict-free parallel simulation scheme and process for large-scale photovoltaic-storage systems, simulation efficiency is improved while ensuring simulation accuracy. This invention is suitable for solving simulations of large-scale photovoltaic-storage systems. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This invention provides an application environment for a fine-grained decoupling simulation solution method for a photovoltaic-storage system.

[0053] Figure 2 A flowchart illustrating a fine-grained decoupling simulation solution method for a photovoltaic-storage system provided in this embodiment of the invention;

[0054] Figure 3 A schematic diagram of the topology of a large-scale photovoltaic energy storage system;

[0055] Figure 4a For electromagnetic transient simulation of inductor branches;

[0056] Figure 4b Equivalent circuit;

[0057] Figure 5 This is a schematic diagram of the equivalent model of a single diode;

[0058] Figure 6 This is a schematic diagram of a photovoltaic array model based on a single diode equivalent model.

[0059] Figure 7 This is a schematic diagram of a single-phase topology for a T-type equivalent circuit.

[0060] Figure 8 A simplified equivalent circuit diagram for an energy storage battery;

[0061] Figure 9 A schematic diagram of the decoupling model for a level VSC converter;

[0062] Figure 10 A schematic diagram of the decoupling model for a Boost converter;

[0063] Figure 11a This is a schematic diagram of a T-type LLL branch;

[0064] Figure 11b This is the equivalent circuit of a T-type LLL branch;

[0065] Figure 12 This is the equivalent circuit of a three-phase transformer.

[0066] Figure 13a This is a schematic diagram of an LCL filter structure;

[0067] Figure 13bThis is the equivalent circuit of an LCL filter;

[0068] Figure 14 This is a schematic diagram of the decoupled structure of the photovoltaic-storage system.

[0069] Figure 15 This is a schematic diagram of the decoupled current collector system.

[0070] Figure 16 Flowchart for parallel computation of subsystem state variables;

[0071] Figure 17a The simulation waveform of the stator-side A-phase current is shown below.

[0072] Figure 17b The simulation waveform diagram is shown on the DC side.

[0073] Figure 18 This is a schematic diagram of the structure of a fine-grained decoupling simulation solution system for a photovoltaic-storage system.

[0074] Figure 19 This is a schematic diagram of the structure of an electronic device. Detailed Implementation

[0075] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0076] The fine-grained decoupling simulation solution method for photovoltaic-storage systems provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, each node of the photovoltaic storage system communicates with server 102 via a network. The data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed on a cloud or other network server. Server 102 constructs an electromagnetic transient simulation model of the photovoltaic storage system by performing electromagnetic transient simulation modeling on multiple components within the system and connecting them topologically based on the electromagnetic transient simulation models of these components. It then layers the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding current collection system, and performs fine-grained decoupling and networking on the inner and outer structures obtained from the layering to obtain a decoupled electromagnetic transient simulation model of the photovoltaic storage system. Finally, it performs multi-threaded parallel simulation solving of the decoupled electromagnetic transient simulation model of the photovoltaic storage system using a multi-threaded CPU. Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0077] like Figure 2 As shown in the embodiments of this application, a fine-grained decoupling simulation solution method for a photovoltaic-storage system is provided, which is then applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps S1 to S3. Wherein:

[0078] Step S1: Perform electromagnetic transient simulation modeling on multiple components in the photovoltaic-storage system, and connect the topology based on the electromagnetic transient simulation models of the multiple components to construct the electromagnetic transient simulation model of the photovoltaic-storage system.

[0079] It is understandable that establishing an electromagnetic transient simulation model for a photovoltaic-storage system, such as... Figure 3 The photovoltaic-storage system shown includes electromagnetic transient simulation models of basic components and electromagnetic transient simulation models of core components. Basic components include resistors, inductors, capacitors, etc., while core components generally include photovoltaic arrays, converters, transformers, filters, energy storage batteries, etc.

[0080] The electromagnetic transient simulation model of the photovoltaic-storage system established in this application embodiment can reflect the detailed internal state information of the photovoltaic-storage system, eliminate the human-induced errors in the simulation of the photovoltaic-storage system caused by the average value model, and establish a high-precision, widely applicable detailed model of the photovoltaic-storage system.

[0081] Since basic components in a photovoltaic energy storage system, such as resistors, inductors, capacitors, and series-parallel combinations, cannot be directly used for electromagnetic transient simulation, when modeling the electromagnetic transients of these components, it is first necessary to use ordinary differential equations or partial differential equations to describe their transient processes. Then, numerical integration methods are used to differentiate the equations, and finally, the equivalent electromagnetic transient simulation model of the components can be obtained.

[0082] In some embodiments, the component includes multiple basic node components, which include resistors, inductors, and capacitors.

[0083] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system in step S1 includes:

[0084] Step S101: Based on the preset modeling parameters of the basic node elements, the voltage and current equations of the basic node elements between each node in the photovoltaic-storage system are differentially processed using the back Euler method to obtain the equivalent current of the basic node elements.

[0085] Among them, the coefficients and transient increment resistances of the nodes are different when the components are different. The preset modeling parameters of the basic node components are shown in Table 1.

[0086] Table 1

[0087]

[0088] Where R is resistance, L is inductance, C is capacitance, RL is resistive inductance, RC is capacitive capacitance, and G is capacitance. eq A1 and A2 are the transient increasing resistances of the element.

[0089] Taking the inductor branch as an example, its equivalent circuit is as follows: Figure 4a As shown in ~b.

[0090] The voltage and current equations of the basic node elements in the photovoltaic-storage system are differentially processed using the backward Euler method, resulting in the equivalent current of the basic node elements:

[0091] In the formula, Let be the equivalent current of the basic node element at time t. Let be the voltage across the basic node element at time t. This is the historical current source current value. , These are the historical equivalent current and the historical voltage across the terminals, respectively.

[0092] Step S102: Perform electromagnetic transient simulation modeling on the basic node elements based on the equivalent current of the basic node elements.

[0093] In some embodiments, the element includes a core component, which in turn includes a photovoltaic array. The photovoltaic array includes multiple photovoltaic cells.

[0094] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system in step S1 includes:

[0095] Step S111: Use a single diode equivalent model to perform electromagnetic transient simulation modeling on multiple photovoltaic cells in the photovoltaic array to obtain the electromagnetic transient simulation model of each photovoltaic cell.

[0096] In electromagnetic transient modeling of photovoltaic arrays, the basic component is the photovoltaic cell. To achieve accurate simulation of the photovoltaic cell and consider internal losses, a single-diode equivalent model is used, that is, a series resistor R is added to the ideal model. s and parallel resistor R sh like Figure 5 As shown, its output current can be expressed as:

[0097]

[0098] In the formula, I is the output current of the photovoltaic cell port; U is the voltage of the photovoltaic cell port; I ph q is the photocurrent, Is is the diode reverse saturation current, q is the electron charge, A is the diode ideality factor, k is the Boltzmann constant, and T is the absolute temperature.

[0099] Among them, the series resistance R s This is used to simulate the resistance of semiconductor materials, the contact resistance between metal electrodes and semiconductor materials, the lateral resistance of the diffusion layer, and the bulk resistance of the metal electrode in real photovoltaic cells. Parallel resistance R sh It is used to simulate the resistance caused by factors such as surface contamination and edge leakage in photovoltaic cells.

[0100] Among them, photocurrent I ph The reverse saturation current Is of a diode is strongly correlated not only with the ambient irradiance but also with temperature, and its expression is:

[0101]

[0102] In the formula, S is the light irradiance; S ref I represents the irradiance under standard operating conditions. phref This refers to the photocurrent under standard operating conditions; I sref T represents the diode saturation current under standard operating conditions. ref The operating temperature under standard conditions is measured using a Kelvin thermometer; C T E is the temperature coefficient. g This refers to the bandwidth of the no-bandwidth area.

[0103] Step S112: Based on the topology of multiple photovoltaic cells in the photovoltaic array, connect the electromagnetic transient simulation models of each photovoltaic cell to construct the electromagnetic transient simulation model of the photovoltaic array.

[0104] In this invention, multiple photovoltaic (PV) modules are connected in parallel and series to form a complete PV array. Generally, the characteristic parameters of each PV module within a PV array can be considered identical. The accuracy of the single-diode equivalent model can reach the standard of most simulation scenarios in electromagnetic transient simulations. Therefore, the PV array model of this invention is also based on the single-diode equivalent model. When the connection losses between PV modules are ignored, the equivalent circuit can be obtained as follows: Figure 6 As shown.

[0105] Among them, the characteristic parameters include the resistance of the semiconductor material in the photovoltaic cell, the contact resistance between the metal electrode and the semiconductor material, the lateral resistance of the diffusion layer and the bulk resistance of the metal electrode, as well as the resistance caused by surface contamination and edge leakage of the photovoltaic cell.

[0106] The corresponding current-voltage characteristic relationship is as follows:

[0107]

[0108] In the formula, N s N represents the number of photovoltaic cells connected in series. p This represents the number of photovoltaic cells connected in parallel.

[0109] In some embodiments, the element includes a core component, which includes a transformer.

[0110] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system in step S1 includes:

[0111] Step S121: Use a T-type equivalent circuit to perform equivalent modeling of the transformer to obtain the equivalent model of the transformer.

[0112] In modeling the transformer, a T-type equivalent circuit is used for equivalence, such as... Figure 7 As shown, where v T1 i T1 v T2 , i, are the primary side port voltage and port current, and the secondary side port voltage and port current, respectively; the winding resistance and leakage reactance are both attributed to the secondary side.

[0113] Step S122: Determine the equivalent electromagnetic transient simulation circuit for the transformer's equivalent model based on the transformer type;

[0114] If the transformer is a single-phase two-winding transformer, the voltage and current equations of the basic node elements in the equivalent model of the transformer are discretized to obtain the equivalent calculation circuit for the electromagnetic transient simulation of the single-phase two-winding transformer.

[0115] If the transformer type is a three-phase transformer, then determine the equivalent calculation circuit for the electromagnetic transient simulation of each phase of the three-phase transformer, and connect the equivalent calculation circuits for the electromagnetic transient simulation of each phase of the transformer to form the equivalent calculation circuit for the electromagnetic transient simulation of the three-phase transformer.

[0116] The process of obtaining the equivalent calculation circuit for the electromagnetic transient simulation of each phase transformer is carried out according to the equivalent calculation circuit for a single-phase two-winding transformer.

[0117] Step S123: Perform electromagnetic transient simulation on the transformer based on the equivalent calculation circuit of the electromagnetic transient simulation of the transformer's equivalent model.

[0118] In some embodiments, the component includes a core component, which includes a converter, a storage battery, a filter, and a transmission line;

[0119] The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system in step S1 includes:

[0120] Step S131: Use a switching function model to perform equivalent modeling of the converter.

[0121] In modeling the converter, a switching function model is used for equivalence. For a 2-level VSC converter, each bridge arm is equivalent to a resistor connected in series with a controlled voltage source. The equivalent resistance represents the conduction loss of the switching transistor, and S is set. i (i = a,b,c) represents the switching function, S i =1 indicates that the upper bridge arm switch is on, S i =0 indicates that the lower bridge arm switch is on, and at this time the value of the controlled voltage source is S. iud1 +(S i-1 )u d2 , where u d1 The voltage of the clamping capacitor on the upper bridge arm of the DC side, u d1 This is the clamping capacitor voltage on the lower bridge arm of the DC side. For the Boost converter, its switching transistors are also equivalent to resistors connected in series with a controlled voltage source, where the equivalent resistance represents the switching transistor's conduction loss. S is set... Boost (i = a,b,c) represents the switching function, S Boost =1 indicates that the switch is on, S Boost =0 indicates that the switching transistor is off, and at this time the value of the controlled voltage source is S. Boost (ud1+ud2).

[0122] Step S132: Use a simplified model of a voltage source and a resistor in parallel to perform equivalent modeling of the energy storage battery.

[0123] In modeling the energy storage battery, a simplified model is used for equivalence, that is, it is equivalent to a voltage source and a resistor in parallel, such as... Figure 8 As shown. The voltage source voltage is related to the battery temperature and state of charge, and can be expressed as...

[0124]

[0125] In the formula, E is the battery voltage. Here, θ represents the battery's state of charge (per unit), and θ represents the battery temperature. For nominal voltage, K E is the polarization constant.

[0126] The resistor R is used to simulate the ohmic resistance R0 and polarization resistance R1 in a real battery, and its expression is:

[0127]

[0128] In the formula, k is the battery coefficient, which can be determined from the battery specification chart. is the per-unit value of state of charge based on battery capacity, and k is the battery coefficient.

[0129] Step S133: Use a π-type LCL branch to perform equivalent modeling of the filter.

[0130] Step S134: Use a lumped parameter line model to perform equivalent modeling of the transmission line.

[0131] Step S2: The electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system of the photovoltaic-storage system are layered, and the inner and outer structures obtained by the layering are decoupled and networked in a fine-grained manner to obtain the electromagnetic transient simulation decoupled model of the photovoltaic-storage system.

[0132] Specifically, in step S2, the electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system are layered, and the inner and outer structures obtained from the layering are decoupled and networked in a fine-grained manner to obtain the electromagnetic transient simulation decoupled model of the photovoltaic-storage system, including:

[0133] Step S201: The electromagnetic transient simulation model of the photovoltaic energy storage system and the corresponding current collection system of the photovoltaic energy storage system are layered to obtain an inner structure and an outer structure. The inner structure includes the various components of the photovoltaic energy storage system, and the outer structure includes the current collection system.

[0134] Among them, the power collection system generally consists of long-distance transmission lines, transformers, and power grids.

[0135] Step S202: Decouple the decoupling nodes of the outer structure. The decoupling nodes include the common connection node connecting the optical storage system and the collection line, and the connection node between the collection line and the transformer on the long-distance transmission line.

[0136] In some embodiments, the collector system can be decoupled using a transmission line decoupling method based on the natural delay characteristics of long transmission lines.

[0137] Step S203: Decouple and network each component of the inner structure based on the controlled source decoupling method and the one-step delay decoupling method.

[0138] The components of a photovoltaic-storage system include converters, transformers, filters, and inductor branches.

[0139] The converters typically consist of Boost converters and three-phase inverters. The three-phase inverter operates in two states: latched and unlatched. In the latched state, both the three-phase inverter and adjacent branches can be considered as open circuits, thus achieving natural decoupling of the converter.

[0140] When decoupling the converter, a method assuming that the DC-side voltage and AC-side current remain constant within a single step is adopted. The converters in the photovoltaic-storage system mainly consist of Boost converters and three-phase two-level VSC converters. For the three-phase two-level VSC converter, decoupling is automatically achieved when the converter is in a latched state. When the converter is in a non-latched state, since the DC side of the photovoltaic-storage system contains a large capacitor and the AC side contains a large inductor, the DC-side voltage and AC-side current can be considered constant within a single step. A one-step delay decoupling method can be used to decouple the converter, that is, assuming that the inductor current and capacitor voltage on both sides of the converter remain constant within adjacent steps. The differential equation for the three-phase two-level VSC converter is as follows:

[0141]

[0142] In the formula, S i (i = a, b, c) represents the switching function; u i i i (i = a, b, c) represent the phase voltage and phase current on the AC side, respectively; i dc Indicates the current on the DC side; u d1 u d2 These represent the voltage values ​​across the two DC capacitors; R on This represents the on-state resistance of the IGBT. The superscript n indicates the value at time n, and n+1 indicates the value at time n+1. The decoupling of the two sub-networks on both sides of the three-phase inverter can be achieved through the differential equation of the three-phase two-level VSC converter, and its equivalent circuit diagram is shown below. Figure 9 As shown.

[0143] The same decoupling method is used for Boost converters, assuming that the slowly changing variables on both sides of the converter have a constant single step size. The difference equation can be obtained as follows:

[0144]

[0145] In the formula, S Boost Represents the switching function, u C i is the DC-side capacitor voltage. L For the boost converter inductor current, u eq i eq These represent the voltage and current of the Boost converter's switching transistors, respectively. The decoupling of the photovoltaic arrays on both sides of the Boost converter and the three-phase inverter has been completed, and its equivalent circuit diagram is shown below. Figure 10 As shown.

[0146] The decoupling of the transformer also adopts a one-step delayed decoupling method. Since the transformer has been equivalent to a T-type circuit when modeling it, the T-type LLL branch is shown in Figure 11(a), and its state-space equation is:

[0147]

[0148]

[0149]

[0150] The state-space equations are discretized at time (n, n+1) by combining the trapezoidal integral method and the explicit Euler method; simultaneously, considering i m =i A +i B , can eliminate i m After the above processing is completed, the state equation can be obtained:

[0151]

[0152]

[0153]

[0154] In the formula, L A R A These are the primary inductance and resistance of the transformer, respectively, L B R B These are the self-inductance and resistance on the secondary side of the transformer, respectively, L m For leakage sensing, i A i B u m These are the primary current, secondary current, and node voltage, respectively.

[0155] Based on the discretized equations of the transformer, the transformer can be divided into three subnets. The voltage and current values ​​of the three inductive branches at time n+1 are independent of the other branches, depending only on the values ​​at time n. Therefore, it can be divided into three subnets. Subnet A and subnet B are the left and right circuits connected by the transformer, respectively. After decoupling, each subnet can have its own set of nodal voltage equations, which can then be solved using an improved nodal voltage method.

[0156] Specifically, the steps for dividing the transformer into three subnets for parallel solution are as follows:

[0157] First, the port voltage at time n is known. , and branch current , Solve for the excitation voltage at time n. .

[0158] Secondly, substitute the obtained excitation voltage into the state equation to complete the branch current at time n+1. , Solve for it.

[0159] Next, the obtained branch current is injected into the subsystem as a controlled source, so that subsystem A and subsystem B are independent of each other at time n+1, thus achieving decoupling of the two subsystems, as shown in Figure 11(b).

[0160] Finally, after decoupling, each subsystem can be solved in parallel at time n+1, and the port voltage of each subsystem at time n+1 can be obtained in parallel. , .

[0161] Three-phase transformers in photovoltaic power generation units generally use the D / yn1 connection method. For this type of transformer, to achieve parallel solution of the transformer and the electrical systems on both sides, the high-voltage side winding impedance can be reduced to the low-voltage side and then decoupled using the LLL branch method. Its equivalent circuit is as follows: Figure 12 As shown.

[0162] For the three-phase transformer in the photovoltaic-storage system, the impedance of the high-voltage side winding can be attributed to the low-voltage side, and then the above decoupling method can be used for decoupling and network separation.

[0163] When decoupling the filter, a combination of explicit and implicit integration is used. After discretizing the inductor branch using explicit integration and the capacitor branch using the back-Euler method, the discretized equation of the filter can be obtained as follows:

[0164]

[0165]

[0166]

[0167] In the formula, u C Δt represents the capacitor voltage value, and Δt represents the simulation step size.

[0168] The inductor branch is discretized using explicit integration, while the capacitor branch is discretized using implicit integration.

[0169] Based on the discretization equations of the filter, the filter can be decoupled, and the equivalent circuit diagram of the filter decoupling can be obtained as follows: Figure 13a As shown in ~b.

[0170] For the remaining short transmission lines, a lumped parameter model can be used for modeling.

[0171] Based on the above decoupling method, the photovoltaic-storage system can be decoupled into 8 subnets, such as... Figure 14 As shown.

[0172] Step S204: Connect the decoupled inner structure and the decoupled outer structure to obtain the electromagnetic transient simulation decoupling model of the photovoltaic energy storage system.

[0173] Specifically, regarding the connection point between the photovoltaic-storage system and the power collection system, since the various components in the photovoltaic-storage system have been decoupled as mentioned above, a one-step delay decoupling method has been adopted. After decoupling, each subsystem is independent of each other within a single simulation step, which means that the subsystems are decoupled from each other, and the subgrids are decoupled from each other. After the transformer is decoupled, the systems on both sides of the transformer are also decoupled. The connection between the systems on both sides and the transformer is transformed into a connection with the controlled current source. The controlled current source is then connected to the power collection system, that is, the subsystem is connected to the power collection system. The connection method is the same as the connection method between the transformer and the power collection system before the grid separation. Therefore, it is only necessary to connect the decoupled subsystem of the transformer to the power collection system to achieve the decoupling of the power collection system and the photovoltaic-storage system.

[0174] It is understandable that the network is segmented. In this application embodiment, a two-layer segmentation is implemented, that is, the inner layer and the outer layer use different segmentation methods. The outer layer is the decoupling of the current collection system, and the inner layer is the decoupling of the direct-drive wind turbine. The outer layer uses the controlled source decoupling method, and the inner layer uses the MATE decoupling method.

[0175] This embodiment proposes a two-layer network simulation method, which, compared to a single network algorithm, offers advantages such as high flexibility, high simulation accuracy, and ease of implementation, significantly improving simulation efficiency.

[0176] Step S3: Perform multi-threaded parallel simulation to solve the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

[0177] Specifically, step S3 involves performing multi-threaded parallel simulation solutions on the electromagnetic transient simulation decoupling model of the photovoltaic-storage system based on a multi-threaded CPU, including:

[0178] Step S301: Initialize the parameters of each component of the photovoltaic-storage system and the node voltages of each subnet of the photovoltaic-storage system according to the network topology of the electromagnetic transient simulation decoupling model of the photovoltaic-storage system.

[0179] To reduce the computational burden on the CPU during simulation, the node admittance matrix and inverse matrix of each subnet under different conditions are listed based on the known component parameters and network topology of the photovoltaic-storage power station, and then pre-stored before the simulation begins. Furthermore, to ensure the system can quickly reach a stable state after the simulation starts, set values ​​are assigned to all components in the photovoltaic unit and initial values ​​are assigned to the voltages of the subnet nodes during simulation initialization.

[0180] Step S302: Determine the communication variables between subnets based on the state variables of each subnet.

[0181] In calculating the interconnection variables, because the decoupled subnets have values ​​that need to be exchanged with adjacent subnets at the split boundaries, the interconnection variables between different subnets need to be obtained before starting the parallel solution of the subnets. The solution method for the interconnection variables between each subnet is shown in Table 2. The interconnection variables within the collector system are obtained by using the single-step semi-implicit delay integral of the state variables and the natural delay characteristics of long-distance transmission lines. The interconnection variables include the three-phase interconnection current, the voltage value on the DC capacitor, the inductor current of the boost converter, and the capacitor voltage value.

[0182] Table 2. Solution method for internal interconnection variables of photovoltaic units

[0183]

[0184] Among them, subnets 4, 6, and 8, due to the characteristics of their decoupling method, will have their state variables presented in the form of connection variables during the solution process, and the solution of the subnet connection variables needs to be completed in this step. The remaining subnets will be solved in parallel in step 3.

[0185] Since the collector system has been divided into multiple subnets, the internal connection variables can be solved using the natural delay of long transmission lines. Meanwhile, subnet 7 is incorporated into the collector system; therefore, the connection variables between the photovoltaic storage system and the collector system are the same as the connection variables between subnet 5 and subnet 7, such as... Figure 15 As shown.

[0186] Step S303: Incorporate the connection variables between each subnet into the corresponding subnet in the form of controlled sources, and allocate each subnet to each thread in the multi-threaded CPU to perform multi-threaded parallel simulation and solution for each subnet.

[0187] After the connection variables are calculated, they are incorporated into the corresponding subnets as controlled sources. At this point, CPU parallel solution steps can be performed. During this process, because the calculations of different subnets are independent at this stage, the different subnets are decoupled. To achieve parallel solution of subnets and significantly improve simulation efficiency, the threads in the CPU can be numbered, and different subnets can be assigned to different threads. This allows the CPU's multi-threading advantage to perform parallel calculations on the decoupled subnets.

[0188] The electromagnetic transient simulation solution process for each subnet is completely consistent with that without subnetting, and the solution process is as follows: Figure 16 As shown. Figure 16 In the diagram, i represents the column vector of node injected current; G represents the improved node admittance matrix; u represents the node voltage; and ikm and ukm represent the branch current and branch voltage, respectively.

[0189] It is understood that the conflict-free computation process for decoupled subnets established in the embodiments of this application includes the initialization scheme, preprocessing scheme, and parallel solution scheme based on multi-threaded CPU of the simulation model. This can realize the parallel solution of the decoupled subnet based on multi-threaded CPU, which greatly improves the solution efficiency and the simulation accuracy.

[0190] It should be noted that the embodiments of this application construct an electromagnetic transient simulation model of the photovoltaic-storage system by performing electromagnetic transient simulation modeling on multiple components within the photovoltaic-storage system. The electromagnetic transient simulation model of the photovoltaic-storage system is then layered, and fine-grained decoupling and networking are performed after layering. Based on a multi-threaded CPU, the electromagnetic transient simulation decoupled model of the photovoltaic-storage system is solved by multi-threaded parallel simulation. This achieves flexible networking and reduces the computational load of large-scale photovoltaic-storage systems. Furthermore, by establishing a conflict-free parallel simulation scheme and simulation process for large-scale photovoltaic-storage systems, the simulation efficiency is improved while ensuring simulation accuracy. This method is suitable for solving simulations of large-scale photovoltaic-storage systems.

[0191] To verify the accuracy and solution efficiency of the proposed fine-grained decoupling simulation method for photovoltaic-storage systems, the proposed strategy was compared with a detailed photovoltaic-storage power station model built in Matlab / Simulink. The test system consisted of two photovoltaic power generation clusters, each containing three photovoltaic power generation units. The simulation step size was set to 5 μs, and the total simulation time was 10 s.

[0192] Simulation waveforms of DC-side voltage and stator-side current during the startup and steady-state operation phases of a photovoltaic-storage power station are shown below. Figure 17a As shown in ~b, the comparison shows that the strategy proposed in this invention is highly consistent with the detailed model.

[0193] Calculations show that the maximum relative error of the 2-norm of the A-phase voltage at the PCC point is 7.6 during the startup and steady-state phases of the photovoltaic-storage power station. 10 -4 All of them meet the generally accepted requirement of less than 1 in real-time simulation research. 10 -3 The indicator requirements.

[0194] Regarding simulation efficiency, a simulation model of a photovoltaic-storage power station was built to verify the acceleration effect of the proposed fine-grained optimization allocation strategy. The simulation time of photovoltaic-storage power stations with different numbers of units was tested using both a traditional detailed model and the multi-threaded CPU simulation platform included in this invention. The simulation step size was 5μs, and the total simulation time was 1s. The test results are shown in Table 3.

[0195] Table 3 Simulation time required for photovoltaic-storage power stations of different scales (total simulation time 1s)

[0196]

[0197] As the test results show, the fine-grained decoupled simulation solution method for photovoltaic and energy storage systems proposed in this application gradually increases the simulation speedup as the number of photovoltaic units increases. When the number of photovoltaic units increases to 200, the speedup of the designed simulation platform reaches 524 times, effectively solving the computational efficiency problem brought about by the scaling up and large-scale development of photovoltaic and energy storage power plants.

[0198] Based on the same inventive concept, this application also provides a fine-grained decoupling simulation solution system for photovoltaic-storage systems to implement the fine-grained decoupling simulation solution method for photovoltaic-storage systems mentioned above.

[0199] The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the fine-grained decoupling simulation solution system for photovoltaic and energy storage systems provided below can be found in the limitations of the fine-grained decoupling simulation solution method for photovoltaic and energy storage systems described above, and will not be repeated here.

[0200] like Figure 18 As shown in the embodiments of this application, a fine-grained decoupling simulation solution system for a photovoltaic-storage system is also provided, including:

[0201] The simulation modeling module 100 is used to perform electromagnetic transient simulation modeling on multiple components in the photovoltaic-storage system, and to construct the electromagnetic transient simulation model of the photovoltaic-storage system by performing topological connections based on the electromagnetic transient simulation models of multiple components.

[0202] The layered decoupling module 200 is used to layer the electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system of the photovoltaic-storage system, and to perform fine-grained decoupling and networking on the inner and outer structures obtained by layering, so as to obtain the electromagnetic transient simulation decoupling model of the photovoltaic-storage system.

[0203] The simulation solution module 300 is used to perform multi-threaded parallel simulation solutions for the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

[0204] In some embodiments, the component includes a plurality of basic node components, the basic node components including resistors, inductors and capacitors;

[0205] Electromagnetic transient simulation modeling was performed on multiple components within the photovoltaic-energy storage system, including:

[0206] Based on the preset modeling parameters of the basic node elements, the voltage and current equations of the basic node elements between each node in the photovoltaic-storage system are differentially processed using the back Euler method to obtain the equivalent current of the basic node elements.

[0207] Electromagnetic transient simulation modeling of basic node elements is performed based on the equivalent current of the basic node elements.

[0208] In some embodiments, the element includes a core component, and the core component includes a photovoltaic array;

[0209] Electromagnetic transient simulation modeling was performed on multiple components within the photovoltaic-energy storage system, including:

[0210] Electromagnetic transient simulation models of multiple photovoltaic cells in a photovoltaic array are obtained by using a single diode equivalent model.

[0211] Based on the topology of multiple photovoltaic cells in the photovoltaic array, the electromagnetic transient simulation models of each photovoltaic cell are topologically connected to construct the electromagnetic transient simulation model of the photovoltaic array.

[0212] In some embodiments, the element includes a core component, which includes a transformer;

[0213] Electromagnetic transient simulation modeling was performed on multiple components within the photovoltaic-energy storage system, including:

[0214] The transformer is modeled using a T-type equivalent circuit to obtain the equivalent model of the transformer;

[0215] The equivalent electromagnetic transient simulation circuit of the transformer is determined based on the type of transformer.

[0216] If the transformer is a single-phase two-winding transformer, the voltage and current equations of the basic node elements in the equivalent model of the transformer are discretized to obtain the equivalent calculation circuit for the electromagnetic transient simulation of the single-phase two-winding transformer.

[0217] If the transformer type is a three-phase transformer, then determine the equivalent calculation circuit for the electromagnetic transient simulation of each phase transformer of the three-phase transformer, and connect the equivalent calculation circuits for the electromagnetic transient simulation of each phase transformer to form the equivalent calculation circuit for the electromagnetic transient simulation of the three-phase transformer.

[0218] Electromagnetic transient simulation of the transformer is performed based on the equivalent circuit of the transformer's equivalent model.

[0219] In some embodiments, the component includes a core component, which includes a converter, a storage battery, a filter, and a transmission line;

[0220] Electromagnetic transient simulation modeling was performed on multiple components within the photovoltaic-energy storage system, including:

[0221] The converter is modeled using a switching function model;

[0222] A simplified model of a voltage source and a resistor in parallel is used to perform equivalent modeling of the energy storage battery.

[0223] The filter is modeled using a π-type LCL branch;

[0224] The transmission line is modeled using a lumped parameter line model.

[0225] In some embodiments, the layered decoupling module 200 is used to layer the electromagnetic transient simulation model of the photovoltaic energy storage system and the corresponding current collection system of the photovoltaic energy storage system to obtain an inner layer structure and an outer layer structure, wherein the inner layer structure includes various components of the photovoltaic energy storage system and the outer layer structure includes the current collection system.

[0226] Decouple the decoupling nodes of the outer structure. The decoupling nodes include the common connection node connecting the photovoltaic storage system and the collection line, as well as the connection node between the collection line and the transformer on the long-distance transmission line.

[0227] The controlled source decoupling method and the one-step delay decoupling method are used to decouple and network each element of the inner structure;

[0228] By connecting the decoupled inner and outer structures, an electromagnetic transient simulation decoupling model of the photovoltaic energy storage system is obtained.

[0229] In some embodiments, the simulation solution module 300 is used to initialize the parameters of each component of the photovoltaic storage system and the node voltages of each subnet of the photovoltaic storage system according to the network topology of the electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[0230] Determine the communication variables between subnets based on the state variables of each subnet;

[0231] The connection variables between each subnet are incorporated into the corresponding subnet in the form of controlled sources, and each subnet is assigned to a thread in a multi-threaded CPU to perform multi-threaded parallel simulation and solution for each subnet.

[0232] like Figure 19 As shown, this application embodiment also provides an electronic device. The electronic device 10 includes a memory 20 and a processor 30. The memory 20 stores a computer program. When the computer program is executed by the processor 30, the processor 30 performs the steps of the fine-grained decoupling simulation solution method for the optical storage system as described in any of the above embodiments.

[0233] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed, implements the steps of the fine-grained decoupling simulation solution method for the optical storage system as described in any of the above embodiments.

[0234] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, electronic devices, and computer storage media described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0235] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such processes, methods, products or devices.

[0236] In the several embodiments provided by this invention, it will be understood that each block in the flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the figures. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.

[0237] In the embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer storage media, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0238] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0239] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0240] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods described in the various embodiments of the present invention through a computer device (which may be a personal computer, a server, or a network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0241] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fine-grained decoupling simulation solution method for a photovoltaic-storage system, characterized in that, include: Electromagnetic transient simulation modeling is performed on multiple components in the photovoltaic-storage system, and topological connections are made based on the electromagnetic transient simulation models of the multiple components to construct the electromagnetic transient simulation model of the photovoltaic-storage system. The electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system are layered, and the inner and outer structures obtained from the layering are decoupled and networked with fine granularity to obtain the electromagnetic transient simulation decoupled model of the photovoltaic-storage system, including: The electromagnetic transient simulation model of the photovoltaic energy storage system and the corresponding current collection system are layered to obtain an inner structure and an outer structure. The inner structure includes the various components of the photovoltaic energy storage system, and the outer structure includes the current collection system. The decoupling nodes of the outer structure are decoupled, including the common connection node connecting the optical storage system and the collection line, and the connection node between the collection line and the transformer on the long-distance transmission line. The controlled source decoupling method and the one-step delay decoupling method are used to decouple and network each element of the inner structure; By connecting the decoupled inner structure and the decoupled outer structure, an electromagnetic transient simulation decoupling model of the photovoltaic energy storage system is obtained. The electromagnetic transient simulation decoupling model of the photovoltaic-storage system is solved using a multi-threaded CPU, including: The parameters of each component of the photovoltaic storage system and the node voltages of each subnet of the photovoltaic storage system are initialized based on the network topology of the electromagnetic transient simulation decoupling model of the photovoltaic storage system. Determine the communication variables between subnets based on the state variables of each subnet; The connection variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is assigned to a thread in a multi-threaded CPU to perform multi-threaded parallel simulation and solution for each subnet.

2. The fine-grained decoupling simulation solution method for photovoltaic-storage systems according to claim 1, characterized in that, The component includes multiple basic node components, which include resistors, inductors, and capacitors; The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes: Based on the preset modeling parameters of the basic node elements, the voltage and current equations of the basic node elements between each node in the photovoltaic energy storage system are differentially processed using the back Euler method to obtain the equivalent current of the basic node elements. Electromagnetic transient simulation modeling is performed on the basic node element based on the equivalent current of the basic node element.

3. The fine-grained decoupling simulation solution method for photovoltaic-storage systems according to claim 1, characterized in that, The component includes a core component, which includes a photovoltaic array; The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes: Electromagnetic transient simulation models of multiple photovoltaic cells in the photovoltaic array are performed using a single diode equivalent model to obtain the electromagnetic transient simulation models of each photovoltaic cell. Based on the topology of the multiple photovoltaic cells in the photovoltaic array, the electromagnetic transient simulation models of each photovoltaic cell are topologically connected to construct the electromagnetic transient simulation model of the photovoltaic array.

4. The fine-grained decoupling simulation solution method for photovoltaic-storage systems according to claim 1, characterized in that, The component includes a core component, which includes a transformer; The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes: The transformer is modeled using a T-type equivalent circuit to obtain an equivalent model of the transformer. Determine the equivalent electromagnetic transient simulation circuit of the transformer based on the type of transformer; If the transformer is a single-phase two-winding transformer, the voltage and current equations of the basic node elements in the equivalent model of the transformer are discretized to obtain the equivalent calculation circuit for the electromagnetic transient simulation of the single-phase two-winding transformer. If the transformer is a three-phase transformer, then the equivalent calculation circuit for the electromagnetic transient simulation of each phase of the three-phase transformer is determined, and the equivalent calculation circuit for the electromagnetic transient simulation of each phase of the transformer is connected to form the equivalent calculation circuit for the electromagnetic transient simulation of the three-phase transformer. Electromagnetic transient simulation of the transformer is performed based on the equivalent calculation circuit of the equivalent model of the transformer.

5. The fine-grained decoupling simulation solution method for photovoltaic-storage systems according to claim 1, characterized in that, The component includes a core component, which includes a converter, an energy storage battery, a filter, and a transmission line; The electromagnetic transient simulation modeling of multiple components within the photovoltaic-storage system includes: The converter is modeled using a switching function model; A simplified model of a voltage source and a resistor in parallel is used to perform an equivalent modeling of the energy storage battery. The filter is modeled using a π-type LCL branch; The transmission line is modeled using a lumped parameter line model.

6. A fine-grained decoupled simulation solution system for a photovoltaic-storage system, characterized in that, include: The simulation modeling module is used to perform electromagnetic transient simulation modeling on multiple components in the photovoltaic-storage system, and to construct the electromagnetic transient simulation model of the photovoltaic-storage system by performing topological connections based on the electromagnetic transient simulation models of the multiple components. The layered decoupling module is used to layer the electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system of the photovoltaic-storage system, and to perform fine-grained decoupling and networking on the inner and outer structures obtained by layering, so as to obtain the electromagnetic transient simulation decoupling model of the photovoltaic-storage system. The electromagnetic transient simulation model of the photovoltaic-storage system and the corresponding current collection system are layered, and the inner and outer structures obtained from the layering are decoupled and networked with fine granularity to obtain the electromagnetic transient simulation decoupled model of the photovoltaic-storage system, including: The electromagnetic transient simulation model of the photovoltaic energy storage system and the corresponding current collection system are layered to obtain an inner structure and an outer structure. The inner structure includes the various components of the photovoltaic energy storage system, and the outer structure includes the current collection system. The decoupling nodes of the outer structure are decoupled, including the common connection node connecting the optical storage system and the collection line, and the connection node between the collection line and the transformer on the long-distance transmission line. The controlled source decoupling method and the one-step delay decoupling method are used to decouple and network each element of the inner structure; By connecting the decoupled inner structure and the decoupled outer structure, an electromagnetic transient simulation decoupling model of the photovoltaic energy storage system is obtained. The simulation solution module is used to perform multi-threaded parallel simulation solution of the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU. The electromagnetic transient simulation decoupling model of the photovoltaic-storage system is solved using a multi-threaded CPU, including: The parameters of each component of the photovoltaic storage system and the node voltages of each subnet of the photovoltaic storage system are initialized based on the network topology of the electromagnetic transient simulation decoupling model of the photovoltaic storage system. Determine the communication variables between subnets based on the state variables of each subnet; The connection variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is assigned to a thread in a multi-threaded CPU to perform multi-threaded parallel simulation and solution for each subnet.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the fine-grained decoupling simulation solution method for the optical storage system as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the steps of the fine-grained decoupling simulation solution method for the photovoltaic-storage system as described in any one of claims 1-5.

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