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

Abstract

The invention relates to the technical field of electromagnetic simulation, and discloses an optical storage system fine-grained decoupling simulation solving method, system and device and a medium. According to the method, electromagnetic transient simulation modeling is carried out on a plurality of elements in an optical storage system, and an electromagnetic transient simulation model of the optical storage system is constructed; according to the method, an electromagnetic transient simulation model of the optical storage system is layered, fine-grained decoupling network division is carried out after layering, and multi-thread parallel simulation solving is carried out on the electromagnetic transient simulation decoupling model of the optical storage system based on a multi-thread CPU, so that flexible network division is realized, the calculated amount of the large-scale optical storage system is reduced, and the calculation efficiency of the large-scale optical storage system is improved. And by establishing a conflict-free parallel simulation scheme and a simulation process of the large-scale optical storage system, the simulation efficiency is improved on the premise of ensuring the simulation precision, and the method is suitable for solving the simulated large-scale optical storage system.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic simulation technology, and in particular to a method, system, device and medium for solving fine-grained decoupling simulation of a photovoltaic storage system. Background Art

[0002] The development of science and technology in today's society has led to a continuous increase in energy demand, and the widespread grid connection of photovoltaic power generation units is a future development trend. However, the fluctuation of photovoltaic unit output power has gradually reduced the stability of the power grid. In order to cope with the unstable output power of photovoltaic power generation units, photovoltaic storage systems have emerged.

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

[0004] Since there are many power electronic devices in the photovoltaic storage system and the switching frequency of the converter is gradually increasing, if you want to accurately simulate the photovoltaic storage system, you need to use a smaller simulation step size. However, the reduction of the step size will lead to a significant reduction in simulation efficiency. This makes it a challenge to simulate large-scale photovoltaic storage systems with high efficiency and accuracy, and puts higher requirements on the simulation platform based on limited computing resources.

[0005] To this end, existing solutions can be mainly divided into two aspects: research on efficient and high-precision optical storage system modeling and research on hardware acceleration solutions.

[0006] In terms of photovoltaic storage system modeling, some studies take simplified modeling of photovoltaic power generation units as a starting point, greatly simplifying the parameter calculation of photovoltaic cells. However, the simplified model has low accuracy and cannot reflect the detailed information of photovoltaic arrays, so it cannot meet the accuracy standards of some engineering projects. Other studies use traditional mature modeling methods for typical modular equipment such as power electronic components and transformers to model photovoltaic storage systems, including average value model, decoupled sub-grid model, and Thevenin equivalent model. Among them, the average value model improves the solution efficiency by averaging the trigger signal. However, the average value model cannot reflect the action state of the switch tube, resulting in low simulation accuracy and narrow application range. Thevenin model eliminates model nodes and pre-processes the model to be solved, reducing the amount of calculation in the solution process. However, there are many power electronic devices in photovoltaic storage power stations. If the Thevenin modeling method is used, massive data needs to be pre-stored, which puts high requirements on the storage resources of the hardware. The decoupled sub-grid modeling method can improve the solution efficiency of the model while ensuring the simulation accuracy. However, there are few studies on the decoupled sub-grid simulation methods for photovoltaic storage systems.

[0007] In terms of hardware acceleration solution algorithms, relevant researchers and manufacturers have explored from multiple angles. In order to complete the simulation of small-scale renewable energy stations on a single FPGA, relevant scholars proposed a time-space parallel simulation architecture, which realized the real-time simulation of 13 renewable energy power generation units. On the manufacturer side, RTDS, which developed a commercial real-time simulator, developed a synchronous multi-rate algorithm based on the Superstep and Substep strategies, which improved the simulation capabilities of large-scale power systems. In order to realize electromagnetic transient simulation of large-scale systems, researchers used the Linux operating system and ultra-high-speed networks to combine multiple CPUs and FPGAs into a computing cluster. However, this solution is costly and inflexible. However, due to the large number of power electronic components in large-scale photovoltaic storage systems, more processors are required for simulation using this method, resulting in a high price for the simulation platform. At the same time, relying solely on the support of technologies such as parallel simulation architecture may not be enough to achieve efficient simulation of large-scale photovoltaic storage systems at microsecond steps, nor is it enough to accurately reproduce detailed information inside the unit.

[0008] In summary, the existing electromagnetic transient simulation schemes for large-scale photovoltaic storage systems still have the disadvantages of 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 method, system, device and medium for solving fine-grained decoupling simulation of a photovoltaic storage system, which solves the technical problems that the 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] A first aspect of the present invention provides a method for solving a fine-grained decoupling simulation of a photovoltaic storage system, comprising:

[0011] Performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and topologically connecting the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system;

[0012] The electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are respectively fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system;

[0013] Based on a multi-threaded CPU, a multi-threaded parallel simulation solution is performed on the electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[0014] Preferably, the element comprises a plurality of basic node elements, wherein the basic node elements comprise a resistor, an inductor and a capacitor;

[0015] The electromagnetic transient simulation modeling of multiple components in 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 the nodes in the photovoltaic storage system are differentiated by using the backward 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 comprises a core assembly, the core assembly comprising a photovoltaic array;

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

[0020] Using a single diode equivalent model to perform electromagnetic transient simulation modeling on multiple photovoltaic cells in the photovoltaic array, to obtain an electromagnetic transient simulation model of each photovoltaic cell;

[0021] According to the topological structure of the plurality of photovoltaic cells in the photovoltaic array, the electromagnetic transient simulation models of the respective photovoltaic cells are topologically connected to construct the electromagnetic transient simulation model of the photovoltaic array.

[0022] Preferably, the element comprises a core component, and the core component comprises a transformer;

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

[0024] Using a T-type equivalent circuit to perform equivalent modeling on the transformer to obtain an equivalent model of the transformer;

[0025] Determine an electromagnetic transient simulation equivalent calculation circuit of an equivalent model of the transformer according to the type of the transformer;

[0026] Wherein, if the type of 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 an equivalent calculation circuit for electromagnetic transient simulation of the single-phase two-winding transformer;

[0027] If the type of the transformer is a three-phase transformer, then determining the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer of the three-phase transformer, and connecting the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer to form the equivalent calculation circuit of the electromagnetic transient simulation of the three-phase transformer;

[0028] The electromagnetic transient simulation of the transformer is performed according to the electromagnetic transient simulation equivalent calculation circuit of the equivalent model of the transformer.

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

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

[0031] Using a switch function model to perform equivalent modeling on the converter;

[0032] The energy storage battery is equivalently modeled by adopting a simplified model in the form of a voltage source and a resistor in parallel;

[0033] Using a π-type LCL branch to perform equivalent modeling on the filter;

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

[0035] Preferably, the electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are respectively fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system, including:

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

[0037] Decoupling the decoupling nodes of the outer structure, wherein the decoupling nodes include a common connection node connecting the photovoltaic storage system and the collection line, and a connection node between the collection line and a transformer on a long-distance transmission line;

[0038] Decoupling and networking each element of the inner structure based on a controlled source decoupling method and a one-step delay decoupling method;

[0039] The decoupled inner structure and the decoupled outer structure are connected to obtain an electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[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] Initializing the parameters of each component of the photovoltaic storage system and the node voltage 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;

[0042] Determine the communication variables between the subnets according to the state quantity of each subnet;

[0043] The communication variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is respectively allocated to each thread in the multi-threaded CPU, and multi-threaded parallel simulation is performed on each subnet.

[0044] In a second aspect, the present invention further provides a fine-grained decoupling simulation solution system for a photovoltaic storage system, comprising:

[0045] A simulation modeling module, used to perform electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and to perform topological connection based on the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system;

[0046] A hierarchical decoupling module is used to hierarchize the electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system, and to perform fine-grained decoupling and networking of the inner layer structure and the outer layer structure obtained by the hierarchical decoupling 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 solution on the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

[0048] In a third aspect, the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the fine-grained decoupling simulation solution method for the photovoltaic storage system as described in the first aspect.

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

[0050] It can be seen from the above technical scheme that the present invention constructs an electromagnetic transient simulation model of the photovoltaic storage system by performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and layers the electromagnetic transient simulation model of the photovoltaic storage system, and performs fine-grained decoupling and networking after stratification. Based on a multi-threaded CPU, multi-threaded parallel simulation and solution are performed on the electromagnetic transient simulation decoupling model of the photovoltaic storage system, which realizes flexible networking and reduces the computational complexity of large-scale photovoltaic storage systems. By establishing a conflict-free parallel simulation scheme and simulation process for large-scale photovoltaic storage systems, the simulation efficiency is improved while ensuring the simulation accuracy. The present invention is suitable for solving simulations of large-scale photovoltaic storage systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0052] Figure 1 An application environment for a fine-grained decoupling simulation solution method for a photovoltaic storage system provided by an embodiment of the present invention;

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

[0054] Figure 3 Schematic diagram of the topological structure of a large-scale photovoltaic storage system;

[0055] Figure 4a Simulate inductive branches for electromagnetic transients;

[0056] Figure 4b is the equivalent circuit;

[0057] Figure 5 It 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 It is a schematic diagram of a single-phase topology of a T-type equivalent circuit;

[0060] Figure 8 It is a simplified equivalent circuit diagram of the energy storage battery;

[0061] Fig. 9 It is a schematic diagram of the decoupling model of the level VSC converter;

[0062] Fig.10 It is the schematic diagram of the decoupling model of Boost converter;

[0063] Fig.11a It is a schematic diagram of a T-type LLL branch;

[0064] Fig.11b It is the equivalent circuit of T-type LLL branch;

[0065] Fig.12 is the equivalent circuit of a three-phase transformer;

[0066] Fig.13a It is a schematic diagram of the LCL filter structure;

[0067] Fig.13bis the equivalent circuit of the LCL filter;

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

[0069] Fig.15 It is a schematic diagram of the structure after the power collection system is decoupled;

[0070] Fig.16 Parallel computation flow charts for subsystem state variables;

[0071] Fig.17a It is the simulation waveform of phase A current on the stator side;

[0072] Fig.17b It is the DC side simulation waveform diagram;

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

[0074] Fig.19 The figure is a schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0075] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0076] The fine-grained decoupling simulation solution method for the photovoltaic storage system provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, each node of the photovoltaic storage system communicates with the server 102 through the network. The data storage system can store the data that the server 102 needs to process. The data storage system can be integrated on the server 102, or it can be placed on the cloud or other network servers. The server 102 constructs an electromagnetic transient simulation model of the photovoltaic storage system by performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and topologically connecting the electromagnetic transient simulation models of multiple components; the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding power collection system of the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are fine-grained decoupling and networking, respectively, to obtain 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 by multi-threaded parallel simulation. The server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0077] like Figure 2 As shown, the embodiment of the present application provides a fine-grained decoupling simulation solution method for a photovoltaic storage system, and the method is applied to Figure 1 The server 102 in the example is used as an example to illustrate the method, which includes the following steps S1 to S3. Among them:

[0078] Step S1, performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and topologically connecting the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system.

[0079] It is understandable that the electromagnetic transient simulation model of the photovoltaic storage system is established, such as Figure 3 The photovoltaic storage system shown includes electromagnetic transient simulation models of basic elements and electromagnetic transient simulation models of core components. The basic elements include resistors, inductors, capacitors, etc., and the 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 the embodiment of the present application can reflect the detailed internal state information of the photovoltaic storage system, eliminate the errors caused by the average value model in the simulation of the photovoltaic storage system, and establish a detailed model of the photovoltaic storage system with high precision and wide application range.

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

[0082] In some embodiments, the element includes a plurality of basic node elements, and the basic node elements include resistors, inductors, and capacitors.

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

[0084] Step S101 : Based on preset modeling parameters of basic node elements, the backward Euler method is used to perform difference processing on the voltage and current equations of basic node elements between nodes in the photovoltaic storage system to obtain the equivalent current of the basic node elements.

[0085] Among them, when the elements between nodes are different, their coefficients and transient value-added resistance are also different. The preset modeling parameters of the basic node elements are shown in Table 1.

[0086] Table 1

[0087]

[0088] Among them, R is resistance, L is inductance, C is capacitance, RL is resistive inductance, RC is capacitive capacitance, G is eq is the transient value-added resistance of the component, and A1 and A2 are coefficients.

[0089] Among them, taking the inductor branch as an example, its equivalent circuit is as follows Figure 4a ~b shown.

[0090] The backward Euler method is used to differentiate the voltage and current equations of the basic node elements between the nodes in the photovoltaic storage system, and the equivalent current of the basic node elements is obtained as follows:

[0091] In the formula, is the equivalent current of the basic node element at time t, is the voltage across the basic node element at time t, is the historical current source current value, , 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, and the core component includes a photovoltaic array. Wherein, the photovoltaic array includes a plurality of photovoltaic cells.

[0094] The electromagnetic transient simulation modeling of multiple components in 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 an electromagnetic transient simulation model of each photovoltaic cell.

[0096] The basic unit of the photovoltaic array electromagnetic transient modeling is the photovoltaic cell. In order to achieve accurate simulation of the photovoltaic cell and consider the internal loss of the cell, a single diode equivalent model is used for modeling, that is, a series resistor R is added to the ideal model. s And the parallel resistor R sh like Figure 5 As shown, the output current can be expressed as:

[0097]

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

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

[0100] Among them, the photocurrent I ph The reverse saturation current Is of the diode is not only strongly related to the irradiance of the environment, but also to the temperature. Its expression is:

[0101]

[0102] Where, S is the light irradiance; S ref is the irradiance under standard working conditions; I phref is the photocurrent corresponding to the standard working condition; I sref is the diode saturation current under standard working conditions; T ref is the working temperature under standard working conditions, using a Kelvin thermometer; C T is the temperature coefficient; E g is the bandgap width.

[0103] Step S112: topologically connect the electromagnetic transient simulation models of the photovoltaic cells according to the topological structures of the plurality of photovoltaic cells in the photovoltaic array, and construct the electromagnetic transient simulation model of the photovoltaic array.

[0104] Among them, multiple photovoltaic cell modules are connected in parallel and in series to form a complete photovoltaic array. In general, the characteristic parameters of each photovoltaic cell module in a photovoltaic array can be regarded as the same. The accuracy of the single diode equivalent model can meet the standards of most simulation scenarios in electromagnetic transient simulation. Therefore, the photovoltaic array model of the present invention is also established based on the single diode equivalent model. When the connection loss between photovoltaic cell modules is ignored, the equivalent circuit can be obtained as follows: Figure 6 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 body resistance of the metal electrode, as well as the resistance caused by surface contamination of the photovoltaic cell, edge leakage, etc.

[0106] Among them, the corresponding volt-ampere characteristic relationship is:

[0107]

[0108] Where N s N is the number of photovoltaic cells connected in series; p is the number of photovoltaic cells connected in parallel.

[0109] In some embodiments, the element includes a core assembly, and the core assembly includes a transformer.

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

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

[0112] When 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, determining an electromagnetic transient simulation equivalent calculation circuit of an equivalent model of the transformer according to the type of the transformer;

[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 an equivalent calculation circuit for electromagnetic transient simulation of the single-phase two-winding transformer.

[0115] If the transformer type is a three-phase transformer, the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer of the three-phase transformer is determined, and the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer is connected to form the equivalent calculation circuit of the electromagnetic transient simulation of the three-phase transformer.

[0116] The process of acquiring the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer is performed according to the equivalent calculation circuit of the single-phase two-winding transformer.

[0117] Step S123: performing electromagnetic transient simulation on the transformer according to the electromagnetic transient simulation equivalent calculation circuit of the equivalent model of the transformer.

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

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

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

[0121] When modeling the converter, the switch function model is used for equivalent. For the 2-level VSC converter, a single bridge arm is equivalent to a resistor in series with a controlled voltage source, where the equivalent resistor is used to represent the conduction loss of the switch tube, and S is set. i (i = a, b, c) represents the switching function, S i =1 indicates that the upper bridge arm switch is turned on, S i =0 indicates that the lower bridge arm switch is turned on, and the value of the controlled voltage source is S iud1 +(S i-1 ) d2 , where u d1 is the DC side upper bridge arm clamping capacitor voltage, u d1 is the voltage of the clamp capacitor of the lower bridge arm on the DC side. For the Boost converter, its switch tube is also equivalent to a resistor in series with a controlled voltage source, where the equivalent resistance is used to represent the conduction loss of the switch tube, and S is set Boost (i = a, b, c) represents the switching function, S Boost =1 indicates that the switch is turned on, S Boost =0 indicates that the switch is turned off, and 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 on the energy storage battery.

[0123] When 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. Among them, the voltage source voltage is related to the battery temperature and charge state, which can be expressed as

[0124]

[0125] Where E is the battery voltage, is the battery state of charge per unit value, θ is the battery temperature, is the nominal voltage, K E is the polarization constant.

[0126] Among them, the resistor R is used to simulate the ohmic resistance R0 and polarization resistance R1 in the actual battery, and its expression is

[0127]

[0128] Where k is the battery factor, which can be determined from the battery description chart. is the per unit value of the state of charge based on the battery capacity, and k is the battery coefficient.

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

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

[0131] Step S2, the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding power collection system of the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[0132] Specifically, in step S2, the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding power collection system of the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are respectively fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system, including:

[0133] Step S201, layering the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding power collection system of the photovoltaic storage system to obtain an inner structure and an outer structure, wherein the inner structure includes various components of the photovoltaic storage system and the outer structure includes the power collection system.

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

[0135] Step S202, decoupling the decoupling nodes of the outer structure, the decoupling nodes including the common connection nodes connecting the photovoltaic storage system and the collection line, and the connection nodes between the collection line and the transformer on the long-distance transmission line.

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

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

[0138] Among them, the various components of the photovoltaic storage system include converters, transformers, filters, and inductor branches.

[0139] The converter is usually a Boost converter and a three-phase inverter. The working state of the three-phase inverter can be divided into two types: a blocking state and a non-blocking state. In the blocking state, the three-phase inverter and the adjacent branches can be regarded as being in an open circuit state, thereby achieving natural decoupling of the converter.

[0140] When decoupling the converter, the method of assuming that the DC side voltage and the AC side current remain unchanged within a single step is adopted. The converters in the photovoltaic storage system are mainly Boost converters and three-phase two-level VSC converters. For the three-phase two-level VSC converter, decoupling can be automatically achieved when the converter is in a locked state. When the converter is in a non-locked state, since the DC side of the photovoltaic storage system contains large capacitors and the AC side contains large inductors, it can be assumed that the DC side voltage and the AC side current remain unchanged within a single step. The one-step delayed decoupling method can be used to decouple the converter, that is, it is assumed that the adjacent steps of the inductor current and capacitor voltage on both sides of the converter remain unchanged, and the differential equation of the three-phase two-level VSC converter is obtained as:

[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 Respectively represent the voltage values ​​on the two DC capacitors; R on Represents the on-state resistance of the IGBT. The superscript n represents the value at time n, and n+1 represents the value at time n+1. Among them, the decoupling of the subnets on both sides of the three-phase inverter can be completed through the differential equation of the three-phase two-level VSC converter. Its equivalent circuit diagram is shown in Fig. 9 shown.

[0143] The same method is used to decouple the Boost converter. It is assumed that the single step length of the slowly changing variables on both sides of the converter remains unchanged, and the differential equation is obtained as follows:

[0144]

[0145] In the formula, S Boost represents the switching function, u C is the DC side capacitor voltage, i L is the boost converter inductor current, u eq 、i eq are the voltage and current of the boost converter switch tube respectively. The decoupling of the photovoltaic array and the three-phase inverter on both sides of the boost converter is completed. The equivalent circuit diagram is as follows Fig.10 shown.

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

[0147]

[0148]

[0149]

[0150] The state space equation is discretized at the time (n, n+1) by combining the trapezoidal integral method and the explicit Euler method. At the same time, 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] Where, L A , R A are the transformer primary side self-inductance and resistance, L B , R B are the transformer secondary side self-inductance and resistance, L m is the leakage inductance, i A 、i B 、u m They are primary current, secondary current and node voltage respectively.

[0155] Based on the discretization equation of the transformer, the transformer can be divided into three subnets, among which the voltage and current values ​​of the three inductor branches at the current time n+1 are independent of other branches and only related to the values ​​at time n. Therefore, it can be divided into three subnets. Among them, subnet A and subnet B are the left and right circuits connected to the transformer. After decoupling, each subnet can list some node voltage equations separately, and then use the improved node voltage method to solve them.

[0156] Specifically, the specific steps of dividing the transformer into three subnetworks for parallel solving 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 , The solution.

[0159] Again, 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, realizing the decoupling of the subsystems on both sides, 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] In photovoltaic power generation units, three-phase transformers generally use the D / yn1 connection method. For this type of transformer, in order to achieve parallel solution of the transformer and the electrical systems on both sides, the high-voltage side winding impedance can be converted to the low-voltage side and then decoupled using the LLL branch method. The equivalent circuit is as follows: Fig.12 shown.

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

[0163] When decoupling the filter, a decoupling method combining explicit and implicit integration is used. After discretizing the inductor branch using the explicit integration method and the capacitor branch using the backward Euler method, the discretization equation of the filter is:

[0164]

[0165]

[0166]

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

[0168] The inductor branch is processed by explicit integration method, while the capacitor branch is processed by implicit integration method.

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

[0170] Among them, the remaining short transmission lines can be modeled using a lumped parameter model.

[0171] Based on the above decoupling method, the PV storage system can be decoupled into 8 subnets, such as Fig.14 shown.

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

[0173] Among them, for the connection point between the photovoltaic storage system and the collection system, since the aforementioned decoupling of each component in the photovoltaic storage system is carried out, a one-step delayed decoupling method is adopted. After decoupling, each subsystem is independent of each other within a single simulation step, that is, 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, and the connection between the systems on both sides and the transformer is transformed into a connection with a controlled current source. The controlled current source is incorporated into the collection system, that is, the subsystem is incorporated into the collection system. The connection method is the same as the connection method between the transformer and the collection system before the grid is divided. Therefore, it is only necessary to incorporate the subsystem after the transformer is decoupled into the collection system to realize the decoupling of the collection system and the photovoltaic storage system.

[0174] It can be understood that the network is segmented, and the embodiment of the present application implements a double-layer segmentation, that is, the inner and outer layers use different segmentation methods, the outer layer is the decoupling of the collection system, and the inner layer is the decoupling of the direct-drive wind turbines. The outer layer uses a controlled source decoupling method, and the inner layer uses a MATE decoupling method.

[0175] This embodiment proposes a double-layer network simulation method, which has the advantages of high flexibility, high simulation accuracy, and easy implementation compared to a single network algorithm, and can significantly improve simulation efficiency.

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

[0177] Specifically, the multi-threaded parallel simulation solution of the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on the multi-threaded CPU in step S3 includes:

[0178] Step S301 : initializing the parameters of each component of the photovoltaic storage system and the node voltage 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] Among them, in order to reduce the CPU's solving pressure during the simulation process, the node admittance matrix and inverse matrix of each subnet under different conditions are listed according to the known component parameters and network topology in the photovoltaic power station, and then pre-stored before the simulation starts. In addition, in order to enable the system to quickly achieve a stable state after the simulation starts, all components in the photovoltaic unit will be assigned set values ​​and the voltage of the subnet node will be assigned initial values ​​during the simulation initialization process.

[0180] Step S302: Determine the communication variables between the subnets according to the state quantity of each subnet.

[0181] Among them, in terms of the calculation of the connection variables, because the decoupled subnet has values ​​that need to interact with the adjacent subnet at the segmentation boundary, the connection variables between different subnets must be obtained before starting the subnet parallel solution. The solution method for the connection variables between each subnet is shown in Table 2. The internal connection variables of the collection system are obtained through the single-step semi-implicit delay integration of the state quantity and the natural delay characteristics of the long-distance transmission line. The connection variables include the three-phase connection current, the voltage value on the DC capacitor, the boost converter inductor current and the capacitor voltage value.

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

[0183]

[0184] Among them, due to the characteristics of the decoupling method, the state quantities of subnets 4, 6 and 8 will be presented in the form of connection variables in 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 power collection system has been divided into multiple subnetworks, the internal communication variables can be solved by the natural delay of the long transmission line. At the same time, subnetwork 7 is incorporated into the power collection system, and then the communication variables between the photovoltaic storage system and the power collection system are the communication variables between subnetwork 5 and subnetwork 7, such as Fig.15 shown.

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

[0187] Among them, after the connection variables are calculated, they will be incorporated into the corresponding subnets in the form of controlled sources. At this time, the CPU parallel solution step can be performed. In this process, because the calculations of different subnets are not related to each other at this moment, the different subnets are decoupled from each other. At this time, in order to achieve parallel solution of subnets and maximize the efficiency of simulation, the threads in the CPU can be numbered and different subnets can be assigned to different threads, so that the advantages of CPU multi-threading can be used to perform parallel calculations on the decoupled subnets.

[0188] The electromagnetic transient simulation solution process of each subnet is exactly the same as that of the non-subnet. The solution process is as follows: Fig.16 shown. Fig.16 In the above, i represents the node injection current column vector; G represents the improved node admittance matrix; u represents the node voltage; ikm and ukm are the branch current and branch voltage respectively.

[0189] It can be understood that the conflict-free calculation process of the decoupled subnet established in the embodiment of the present application, including the initialization scheme, preprocessing scheme and parallel solution scheme based on multi-threaded CPU of the simulation model, can realize parallel solution of the decoupled subnet based on multi-threaded CPU, which greatly improves the solution efficiency and has higher simulation accuracy.

[0190] It should be noted that the embodiment of the present application constructs an electromagnetic transient simulation model of the photovoltaic storage system by performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and layers the electromagnetic transient simulation model of the photovoltaic storage system, and performs fine-grained decoupling and networking after stratification. The electromagnetic transient simulation decoupling model of the photovoltaic storage system is simulated and solved in parallel by a multi-threaded CPU, thereby achieving flexible networking and reducing the computational complexity of large-scale photovoltaic storage systems. By establishing a conflict-free parallel simulation scheme and simulation process for large-scale photovoltaic storage systems, the simulation efficiency is improved while ensuring the simulation accuracy. The present application is suitable for solving the simulation of large-scale photovoltaic storage systems.

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

[0192] The simulated waveforms of the DC side voltage and stator side current of the photovoltaic power station in the startup stage and steady-state operation stage are shown in the figure below: Fig.17a As shown in Figure 2, by comparison, it can be seen that the strategy proposed in the present invention is highly consistent with the detailed model.

[0193] According to calculations, the maximum relative error of the 2-norm of the A-phase voltage at the PCC when the photovoltaic power station is in the startup stage and the steady-state stage is 7.6 10 -4 , which meets the generally accepted value of less than 1 in real-time simulation research. 10 -3 indicator requirements.

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

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

[0196]

[0197] As shown in the test results, the fine-grained decoupling simulation solution method for the photovoltaic storage system proposed in the embodiment of the present application gradually improves the simulation acceleration ratio as the number of photovoltaic units increases. When the number of photovoltaic units increases to 200, the acceleration ratio of the designed simulation platform reaches 524 times, which effectively solves the computing efficiency problem brought about by the scale and large-scale photovoltaic storage power stations.

[0198] Based on the same inventive concept, an embodiment of the present application also provides a photovoltaic storage system fine-grained decoupling simulation solution system for implementing the photovoltaic storage system fine-grained decoupling simulation solution method mentioned above.

[0199] The implementation solution for solving the problem provided by the system is similar to the implementation solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the fine-grained decoupling simulation solution system for photovoltaic storage systems provided below can be referred to the limitations on the fine-grained decoupling simulation solution method for photovoltaic storage systems in the above text and will not be repeated here.

[0200] like Fig.18 As shown, the embodiment of the present application also provides a fine-grained decoupling simulation solution system for a photovoltaic storage system, 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 perform topological connection according to the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system;

[0202] The hierarchical decoupling module 200 is used to hierarchically analyze the electromagnetic transient simulation model of the photovoltaic storage system and the corresponding power collection system of the photovoltaic storage system, and to perform fine-grained decoupling and networking of the inner layer structure and the outer layer structure obtained by the hierarchical analysis, 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 solution on the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

[0204] In some embodiments, the element includes a plurality of basic node elements, the basic node elements including a resistor, an inductor, and a capacitor;

[0205] Conduct electromagnetic transient simulation modeling for multiple components in the solar energy storage system, including:

[0206] Based on the preset modeling parameters of the basic node elements, the backward Euler method is used to perform difference processing on the voltage and current equations of the basic node elements between the nodes in the photovoltaic storage system to obtain the equivalent current of the basic node elements;

[0207] Electromagnetic transient simulation modeling of basic node components is carried out based on the equivalent current of basic node components.

[0208] In some embodiments, the element includes a core assembly, the core assembly including a photovoltaic array;

[0209] Conduct electromagnetic transient simulation modeling for multiple components in the solar energy storage system, including:

[0210] A single diode equivalent model is used to perform electromagnetic transient simulation modeling on multiple photovoltaic cells in a photovoltaic array, and an electromagnetic transient simulation model of each photovoltaic cell is obtained;

[0211] According to the topological structure 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 assembly, the core assembly including a transformer;

[0213] Conduct electromagnetic transient simulation modeling for multiple components in the solar energy storage system, including:

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

[0215] Determine the electromagnetic transient simulation equivalent calculation circuit of the equivalent model of the transformer according to the type of the 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 an equivalent calculation circuit for electromagnetic transient simulation of the single-phase two-winding transformer.

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

[0218] The electromagnetic transient simulation of the transformer is performed according to the electromagnetic transient simulation equivalent calculation circuit of the equivalent model of the transformer.

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

[0220] Conduct electromagnetic transient simulation modeling for multiple components in the solar energy storage system, including:

[0221] The switch function model is used to perform equivalent modeling of the converter;

[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 equivalently modeled using a π-type LCL branch;

[0224] The lumped parameter line model is used to perform equivalent modeling of the transmission line.

[0225] In some embodiments, the hierarchical decoupling module 200 is used to hierarchically analyze the electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system to obtain an inner layer structure and an outer layer structure, wherein the inner layer structure includes various components of the photovoltaic storage system, and the outer layer structure includes the power collection system;

[0226] Decoupling the decoupling nodes of the outer structure, including the common connection nodes connecting the photovoltaic storage system and the collection line, and the connection nodes between the collection line and the transformer on the long-distance transmission line;

[0227] Based on the controlled source decoupling method and the one-step delay decoupling method, each element of the inner structure is decoupled and networked.

[0228] The decoupled inner structure and the decoupled outer structure are connected to obtain an electromagnetic transient simulation decoupling model of the photovoltaic storage system.

[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 voltage 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 the subnets according to the state quantity of each subnet;

[0231] The communication variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is respectively assigned to each thread in the multi-threaded CPU, and multi-threaded parallel simulation is performed on each subnet.

[0232] like Fig.19 As shown, an embodiment of the present application also provides an electronic device, the electronic device 10 includes a memory 20 and a processor 30, the memory 20 stores a computer program, and when the computer program is executed by the processor 30, the processor 30 executes the steps of the fine-grained decoupling simulation solution method of the photovoltaic storage system as in any of the above embodiments.

[0233] The embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the method for solving the fine-grained decoupling simulation of the photovoltaic storage system in any of the above embodiments.

[0234] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described system, electronic device and computer storage medium can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0235] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or apparatus.

[0236] In several embodiments provided by the present invention, it is understood that each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and a part of a module, a program segment or a code includes one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved.

[0237] In the several embodiments provided by the present 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 only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

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

[0239] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0240] If the integrated unit is implemented in the form of 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 is essentially 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. The computer software product is stored in a storage medium, including several instructions for executing all or part of the steps of the method described in each embodiment of the present invention through a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (full name in English: Read-Only Memory, English abbreviation: ROM), random access memory (full name in English: Random Access Memory, English abbreviation: RAM), disk or optical disk and other media that can store program codes.

[0241] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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: Performing electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and topologically connecting the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system; The electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are respectively fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system; Based on a multi-threaded CPU, a multi-threaded parallel simulation solution is performed on the electromagnetic transient simulation decoupling model of the photovoltaic storage system.

2. The fine-grained decoupling simulation solution method for a photovoltaic storage system according to claim 1 is characterized in that: The element comprises a plurality of basic node elements, wherein the basic node elements comprise resistance, inductance and capacitance; The electromagnetic transient simulation modeling of multiple components in 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 the nodes in the photovoltaic storage system are differentiated by using the backward 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 a photovoltaic storage system according to claim 1 is characterized in that: The element includes a core component, and the core component includes a photovoltaic array; The electromagnetic transient simulation modeling of multiple components in the photovoltaic storage system includes: Using a single diode equivalent model to perform electromagnetic transient simulation modeling on multiple photovoltaic cells in the photovoltaic array, to obtain an electromagnetic transient simulation model of each photovoltaic cell; According to the topological structure of the plurality of photovoltaic cells in the photovoltaic array, the electromagnetic transient simulation models of the respective photovoltaic cells are topologically connected to construct the electromagnetic transient simulation model of the photovoltaic array.

4. The fine-grained decoupling simulation solution method for a photovoltaic storage system according to claim 1 is characterized in that: The element includes a core component, and the core component includes a transformer; The electromagnetic transient simulation modeling of multiple components in the photovoltaic storage system includes: Using a T-type equivalent circuit to perform equivalent modeling on the transformer to obtain an equivalent model of the transformer; Determine an electromagnetic transient simulation equivalent calculation circuit of an equivalent model of the transformer according to the type of the transformer; Wherein, if the type of 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 an equivalent calculation circuit for electromagnetic transient simulation of the single-phase two-winding transformer; If the type of the transformer is a three-phase transformer, then determining the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer of the three-phase transformer, and connecting the equivalent calculation circuit of the electromagnetic transient simulation of each phase transformer to form the equivalent calculation circuit of the electromagnetic transient simulation of the three-phase transformer; The electromagnetic transient simulation of the transformer is performed according to the electromagnetic transient simulation equivalent calculation circuit of the equivalent model of the transformer.

5. The fine-grained decoupling simulation solution method for a photovoltaic storage system according to claim 1 is characterized in that: The element includes core components, and the core components include converters, energy storage batteries, filters and transmission lines; The electromagnetic transient simulation modeling of multiple components in the photovoltaic storage system includes: Using a switch function model to perform equivalent modeling on the converter; The energy storage battery is equivalently modeled by using a simplified model in the form of a voltage source and a resistor in parallel; Using a π-type LCL branch to perform equivalent modeling on the filter; The transmission line is equivalently modeled using a lumped parameter line model.

6. The fine-grained decoupling simulation solution method for a photovoltaic storage system according to claim 1 is characterized in that: The electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system are layered, and the inner layer structure and the outer layer structure obtained by the layering are respectively fine-grained decoupled and networked to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system, including: The electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system are layered to obtain an inner layer structure and an outer layer structure, wherein the inner layer structure includes various components of the photovoltaic storage system, and the outer layer structure includes the power collection system; Decoupling the decoupling nodes of the outer structure, wherein the decoupling nodes include a common connection node connecting the photovoltaic storage system and the collection line, and a connection node between the collection line and the transformer on the long-distance transmission line; Decoupling and networking each element of the inner structure based on a controlled source decoupling method and a one-step delay decoupling method; The decoupled inner structure and the decoupled outer structure are connected to obtain an electromagnetic transient simulation decoupling model of the photovoltaic storage system.

7. The fine-grained decoupling simulation solution method for a photovoltaic storage system according to claim 1 is characterized in that: The multi-threaded parallel simulation solution of the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on the multi-threaded CPU includes: Initializing the parameters of each component of the photovoltaic storage system and the node voltage 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; Determine the communication variables between the subnets according to the state quantity of each subnet; The communication variables between the subnets are incorporated into the corresponding subnets in the form of controlled sources, and each subnet is respectively allocated to each thread in the multi-threaded CPU, and multi-threaded parallel simulation is performed on each subnet.

8. A fine-grained decoupling simulation solution system for a photovoltaic storage system, characterized in that: include: A simulation modeling module, used to perform electromagnetic transient simulation modeling on multiple components in the photovoltaic storage system, and to perform topological connection based on the electromagnetic transient simulation models of the multiple components to construct an electromagnetic transient simulation model of the photovoltaic storage system; A hierarchical decoupling module is used to hierarchize the electromagnetic transient simulation model of the photovoltaic storage system and the power collection system corresponding to the photovoltaic storage system, and to perform fine-grained decoupling and networking of the inner layer structure and the outer layer structure obtained by the hierarchical decoupling to obtain the electromagnetic transient simulation decoupling model of the photovoltaic storage system; The simulation solution module is used to perform multi-threaded parallel simulation solution on the electromagnetic transient simulation decoupling model of the photovoltaic storage system based on a multi-threaded CPU.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the fine-grained decoupling simulation solution method for the photovoltaic storage system as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the steps of the fine-grained decoupling simulation solution method for the photovoltaic storage system as described in any one of claims 1 to 7 are implemented.

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