An analysis method and device of a direct current microgrid, an electronic device, and a storage medium

Abstract

Embodiments of the present application provide a direct current microgrid analysis method and device, electronic equipment and storage medium, the method comprising: obtaining a comprehensive simulation model of a direct current microgrid, the comprehensive simulation model comprising a direct current microgrid model and a plurality of types of fault modules; controlling a target fault module connected with a target power device module to be in a conduction state to simulate a target fault occurring at the target power device; and performing simulation analysis through the comprehensive simulation model to obtain fault characteristic analysis and power flow analysis of the direct current microgrid under the target fault. The above technical solution can obtain fault characteristic analysis results and power flow analysis results of the direct current microgrid under the target fault by constructing a comprehensive simulation model comprising a direct current microgrid model and a plurality of types of fault modules, controlling a target fault module connected with a target power device module to be in a conduction state to simulate a target fault occurring at the target power device, and then performing simulation analysis through the comprehensive simulation model.

Description

Technical Field

[0001] This application relates to the field of microgrid simulation technology, and in particular to an analysis method, apparatus, electronic device and storage medium for DC microgrids. Background Technology

[0002] Multi-source low-voltage DC microgrids integrate various power devices such as photovoltaics, energy storage, and loads, and are interconnected with the AC power grid. They are increasingly being applied in new building applications, and their operational status directly impacts the reliability and safety of building power supply and distribution. Existing power flow and fault analysis for low-voltage DC microgrids largely relies on physical test platforms or measured data, which is costly and struggles to comprehensively cover various operating conditions and fault types. Therefore, how to achieve simulation analysis of multi-source low-voltage DC microgrids and accurately simulate the dynamic response process of the microgrid system is a pressing problem to be solved. Summary of the Invention

[0003] This application provides an analysis method, apparatus, electronic device, and storage medium for DC microgrids, which can accurately simulate the dynamic response process of microgrid systems and provide a safe and repeatable digital test environment for protection device setting and fault contingency planning.

[0004] The first aspect of this application provides an analysis method for a DC microgrid, the method comprising: A comprehensive simulation model of a DC microgrid is obtained. The comprehensive simulation model includes a DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault. The target fault module connected to the target power equipment module is in a conducting state to simulate a target fault occurring at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of a plurality of power equipment modules. The target fault module is a fault module of any one of a plurality of types. Through simulation analysis using the comprehensive simulation model, the fault characteristics and power flow analysis of the DC microgrid under the target fault are obtained.

[0005] In some embodiments, the plurality of fault modules include a plurality of fault modules corresponding to each power equipment module, each fault module being connected to the corresponding power equipment module and used to simulate a type of fault; or, The multiple types of fault modules include multiple fault modules, each fault module corresponding to a type of fault, and each fault module is used to simulate the corresponding type of fault occurring at each power equipment.

[0006] In some embodiments, the plurality of fault modules include a fault module for bipolar short circuit faults and a fault module for ground short circuit faults. The fault module for bipolar short circuit faults is connected between the positive and negative poles of the output bus of the target power equipment module, and the fault module for ground short circuit faults is connected between the positive pole of the output bus of the target power equipment module and a grounding reference point or between the negative pole of the output bus of the target power equipment module and a reference point.

[0007] In some embodiments, obtaining the comprehensive simulation model of the DC microgrid includes: Based on the network topology of the DC microgrid, multiple power equipment types are determined in the DC microgrid, and each power equipment type corresponds to at least one power equipment module; Based on the various types of power equipment, establish mathematical models for each power equipment module; Based on the mathematical models of each power equipment module and the network topology, the DC microgrid model is determined; By setting the various types of fault modules in the DC microgrid model, the comprehensive simulation model is obtained.

[0008] In some embodiments, determining the DC microgrid model based on the mathematical models of each power equipment module and the network topology includes: Based on the mathematical models of each power equipment module and the network topology, an initial simulation model is constructed. Determine the steady-state simulation parameters corresponding to each power equipment module to obtain the initial simulation model after steady-state calibration. The error between the output value and the reference value of the initial simulation model after steady-state calibration is less than a set threshold. When the equipment parameters of at least one of the multiple power equipment modules change, the dynamic simulation parameters of each power equipment module are adjusted until the dynamic response index of the initial simulation model after steady-state calibration meets the preset dynamic response index, thus obtaining the initial simulation model after dynamic calibration; the dynamic response index includes at least one of the transient drop of the bus voltage of each power equipment module, the rise of the bus voltage, and the voltage recovery time. For each of the various operating scenarios, the initial simulation model after steady-state calibration and the initial simulation model after dynamic calibration are verified to obtain the DC microgrid model.

[0009] In some embodiments, the device parameters include at least one of photovoltaic power, energy storage charging, energy storage discharging, and load.

[0010] In some embodiments, the plurality of power equipment types include at least one of power supply equipment, power transmission and distribution equipment, energy storage equipment, power consumption equipment, and power conversion equipment; The plurality of power equipment modules include at least one of the following types of equipment: At least one of the AC power grid module and photovoltaic power module corresponding to the power supply equipment. At least one of the transformer module, line module, and DC bus module corresponding to the power transmission and distribution equipment. At least one of the following: an energy storage module corresponding to the energy storage device, a DC load module corresponding to the electrical equipment, and an AC / DC converter module and a DC / DC converter module corresponding to the power conversion device.

[0011] A second aspect of this application provides an analysis apparatus for a DC microgrid, the apparatus comprising: The acquisition module is used to acquire a comprehensive simulation model of a DC microgrid. The comprehensive simulation model includes a DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault. The simulation module is used to control the target fault module connected to the target power equipment module to be in a conducting state in order to simulate the target fault occurring at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of a plurality of power equipment modules. The target fault module is a fault module of any one of a plurality of types. The analysis module is used to perform simulation analysis through the comprehensive simulation model to obtain the fault characteristic analysis and power flow analysis of the DC microgrid under the target fault.

[0012] A third aspect of this application provides an electronic device including a processor and a memory, the memory storing a computer program, wherein the processor executes the computer program to implement the steps of any of the methods described in the first aspect of this application.

[0013] A fourth aspect of this application provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the steps of any of the methods described in the first aspect of this application.

[0014] The technical solutions provided in this application have at least the following beneficial effects: This application proposes an analysis method, apparatus, electronic device, and storage medium for DC microgrids. The method constructs a comprehensive simulation model comprising a DC microgrid model and multiple types of fault modules. It controls the target fault modules connected to the target power equipment module to be in a conducting state to simulate a target fault occurring at the target power equipment. Simulation analysis is then performed using this comprehensive simulation model, simultaneously obtaining fault characteristic analysis results and power flow analysis results for the DC microgrid under the target fault. Specifically, by controlling the conducting state, any type of fault occurring at any device can be flexibly simulated without remodeling for each fault scenario, significantly improving the flexibility and repeatability of fault simulation. More importantly, this method simultaneously performs power flow analysis and fault characteristic analysis under the same comprehensive simulation model, achieving integrated design of power flow analysis and fault characteristic analysis. This can simultaneously support the comprehensive needs of microgrid operation optimization, fault diagnosis, and protection strategy formulation. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating an analysis method for a DC microgrid proposed in an embodiment of this application. Figure 2 This is a schematic diagram of the process for obtaining a comprehensive simulation model in an analysis method for a DC microgrid proposed in an embodiment of this application; Figure 3 This is a schematic diagram of a DC microgrid network topology proposed in an embodiment of this application; Figure 4 This is a schematic diagram of the simulation model of the DC microgrid AC power supply grid module, transformer module, AC line module and AC / DC converter module proposed in the embodiments of this application; Figure 5 This is a schematic diagram of the DC bus simulation model of the DC microgrid proposed in the embodiments of this application; Figure 6 This is a schematic diagram of the simulation model of the DC / DC converter module (Boost converter) and photovoltaic module of the DC microgrid proposed in the embodiments of this application; Figure 7 This is a schematic diagram of the simulation model of the DC / DC converter module (Buck-Boost converter) and energy storage module of the DC microgrid proposed in the embodiments of this application; Figure 8 This is a schematic diagram of the simulation model of the DC / DC converter module (Busk converter) of the DC microgrid proposed in the embodiments of this application; Figure 9 This is a schematic diagram of the simulation model of the DC load module of the DC microgrid proposed in the embodiments of this application; Figure 10 This is a schematic flowchart illustrating the process of obtaining a DC microgrid model using an analysis method for a DC microgrid proposed in an embodiment of this application. Figure 11 This is a flowchart illustrating another DC microgrid analysis method proposed in an embodiment of this application; Figure 12 This is a schematic diagram of the simulation results of the DC bus voltage during normal operation of the microgrid proposed in this application embodiment; Figure 13 This is a schematic diagram of the simulation results of the DC bus bipolar short-circuit fault proposed in the embodiments of this application; Figure 14 This is a schematic diagram of the simulation results of the DC bus grounding short-circuit fault proposed in the embodiments of this application; Figure 15 This is a schematic diagram of the simulation results of the photovoltaic bus bipolar short-circuit fault proposed in the embodiments of this application; Figure 16 This is a schematic diagram of the simulation results of the photovoltaic bus grounding short-circuit fault proposed in the embodiments of this application; Figure 17 This is a schematic diagram of the simulation results of the bipolar short-circuit fault of the energy storage bus proposed in the embodiments of this application; Figure 18 This is a schematic diagram of the simulation results of the energy storage bus grounding short circuit fault proposed in the embodiments of this application; Figure 19 This is a schematic diagram of the simulation results of the bipolar short-circuit fault on the load bus proposed in the embodiments of this application; Figure 20 This is a schematic diagram of the simulation results of the load bus grounding short-circuit fault proposed in the embodiments of this application; Figure 21 This is a schematic diagram of the structure of an analysis device for a DC microgrid according to an embodiment of this application; Figure 22 This is a schematic diagram of the structure of the electronic device proposed in the embodiments of this application. Detailed Implementation

[0016] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0017] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, "first instruction" and "second instruction" are used to distinguish different user instructions, but do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" are not necessarily different.

[0018] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0019] Furthermore, "at least one" refers to one or more, while "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0020] It should be noted that, in the embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0021] Multi-source low-voltage DC microgrids integrate various power devices such as photovoltaics, energy storage, and loads, and are interconnected with the AC power grid. They are increasingly being applied in new building applications, and their operational status directly impacts the reliability and safety of building power supply and distribution. Existing power flow and fault analysis for low-voltage DC microgrids largely relies on physical test platforms or measured data, which is costly and struggles to comprehensively cover various operating conditions and fault types. Therefore, how to achieve simulation analysis of multi-source low-voltage DC microgrids and accurately simulate the dynamic response process of the microgrid system is a pressing problem to be solved.

[0022] In view of this, embodiments of this application propose an analysis method, apparatus, electronic device, and storage medium for a DC microgrid. The method includes: acquiring a comprehensive simulation model of the DC microgrid, the comprehensive simulation model including a DC microgrid model and multiple types of fault modules, the DC microgrid model being used to simulate the DC microgrid, the DC microgrid model including multiple power equipment modules for simulating multiple power devices in the DC microgrid, each type of fault module being used to simulate a corresponding type of fault; controlling a target fault module connected to a target power equipment module to be in a conducting state to simulate a target fault occurring at the target power equipment, the target power equipment corresponding to the target power equipment module, the target fault module being used to simulate the target fault, the target power equipment module being any one of the multiple power equipment modules, and the target fault module being a fault module of any type among the multiple types; performing simulation analysis through the comprehensive simulation model to obtain fault characteristic analysis and power flow analysis of the DC microgrid under the target fault. The above technical solution constructs a comprehensive simulation model that includes a DC microgrid model and multiple types of fault modules. It controls the target fault modules connected to the target power equipment module to be in a conducting state to simulate the target fault occurring at the target power equipment. Simulation analysis is then performed using this comprehensive simulation model, simultaneously obtaining fault characteristic analysis results and power flow analysis results for the DC microgrid under the target fault. Specifically, by controlling the conducting state, any type of fault occurring at any device can be flexibly simulated without remodeling for each fault scenario, significantly improving the flexibility and repeatability of fault simulation. More importantly, this method simultaneously completes power flow analysis and fault characteristic analysis under the same comprehensive simulation model, achieving integrated design of power flow analysis and fault characteristic analysis. This can simultaneously support the comprehensive needs of microgrid operation optimization, fault diagnosis, and protection strategy formulation.

[0023] The following embodiments detail an analysis method for DC microgrids proposed in this application, such as... Figure 1 As shown, the method includes: Step 101: Obtain the comprehensive simulation model of the DC microgrid. The comprehensive simulation model includes the DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault.

[0024] Obtain a comprehensive simulation model of the DC microgrid.

[0025] For example, the DC microgrid can be a multi-source low-voltage DC microgrid. The integrated simulation model includes two parts: a DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the normal operating conditions of the DC microgrid. It contains multiple power equipment modules, which are used to simulate multiple power devices in the DC microgrid, such as AC power grid, photovoltaic power source, energy storage unit, DC load, and various power converters.

[0026] For example, multiple types of fault modules are used to simulate different types of faults that may occur in a DC microgrid, such as bipolar short-circuit faults and ground short-circuit faults. Each type of fault module can correspond to a specific fault simulation function, providing a standardized injection interface for subsequent fault simulation.

[0027] Step 102: Control the target fault module connected to the target power equipment module to be in the on state to simulate the target fault occurring at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of multiple power equipment modules. The target fault module is any one of multiple types of fault modules.

[0028] For example, the target power equipment module can be any one of a plurality of power equipment modules.

[0029] Based on the simulation requirements, the target power equipment and the type of fault to be simulated are determined, i.e., the target fault.

[0030] For example, a power equipment module (i.e., target power equipment module) corresponding to the target power equipment is selected from the comprehensive simulation model, and a fault module (i.e., target fault module) corresponding to the target fault is selected from multiple types of fault modules.

[0031] After electrically connecting the target fault module to the target power equipment module, the target fault module is controlled to be in a conducting state. Once conducting, the fault module will simulate the electrical characteristics of the target fault at its connection point (e.g., shorting the positive and negative poles to form a bipolar short circuit, or shorting the positive / negative poles to ground to form a ground short circuit), thereby reproducing the physical scenario of the target fault occurring at the target power equipment in the simulation environment.

[0032] In the actual simulation analysis, a photovoltaic power supply device is used as the target device for fault simulation. From the constructed integrated simulation model, the photovoltaic power module corresponding to the photovoltaic power supply device is identified. A target fault module for simulating a bipolar short-circuit fault is connected at the output bus of this photovoltaic power module (i.e., the electrical connection point where the photovoltaic power supply connects to the DC microgrid). This target fault module belongs to the bipolar short-circuit fault type among multiple fault module types, and its connection method is to bridging the positive and negative terminals of the output bus. Subsequently, the target fault module is placed in the conducting state through simulation control commands. At this time, the positive and negative buses of the photovoltaic power module are directly short-circuited, thereby simulating the scenario of a bipolar short-circuit fault occurring at the photovoltaic power supply output in the simulation environment.

[0033] For example, controlling the target fault module connected to the target power equipment module to be in a conducting state can be achieved by changing the state of the switching element inside the fault module. The action time of the switching element inside the fault module is preset in the simulation model. When the simulation runs to the preset time, the switch switches from the open state to the closed state, connecting the fault circuit and thus realizing the conduction of the fault module.

[0034] For example, an ideal switch model can be used, and conduction control can be achieved by setting a time-series control signal: for example, the switch is set to switch from the open state to the closed state at a preset time after the start of the simulation (e.g., t=1.0 seconds), thereby realizing the conduction of the fault module; if a permanent fault needs to be simulated, the switch can be kept closed until the end of the simulation; if a transient fault needs to be simulated, the switch can be set to open again after being closed for a preset duration (e.g., 0.1 seconds).

[0035] For example, control logic signals can also be generated by the control module to directly drive the switching on and off of the internal switches of the fault module.

[0036] Step 103: Perform simulation analysis using a comprehensive simulation model to obtain the fault characteristics analysis and power flow analysis of the DC microgrid under the target fault.

[0037] With the target fault module in the on-state, a comprehensive simulation model is run for simulation analysis. This simulation analysis includes two aspects: fault characteristic analysis and power flow analysis. Fault characteristic analysis focuses on transient processes. By recording the voltage and current waveforms at the moment of fault occurrence and in the subsequent period, fault characteristic quantities (such as short-circuit current peak value, voltage drop depth, transient recovery time, etc.) are extracted to assess the impact of the fault on the system and verify the operating logic of the protection device. Power flow analysis focuses on the steady-state or quasi-steady-state electrical quantity distribution under fault conditions, calculating the current situation of each node in the DC microgrid to determine whether the system can maintain stable operation after the fault. Through the above comprehensive analysis, a complete simulation result of the DC microgrid under the target fault condition can be obtained, providing data support for the formulation of microgrid protection strategies, equipment parameter selection, and operation optimization.

[0038] The above technical solution constructs a comprehensive simulation model that includes a DC microgrid model and multiple types of fault modules. It controls the target fault modules connected to the target power equipment module to be in a conducting state to simulate the target fault occurring at the target power equipment. Simulation analysis is then performed using this comprehensive simulation model, simultaneously obtaining fault characteristic analysis results and power flow analysis results for the DC microgrid under the target fault. Specifically, by controlling the conducting state, any type of fault occurring at any device can be flexibly simulated without remodeling for each fault scenario, significantly improving the flexibility and repeatability of fault simulation. More importantly, this method simultaneously completes power flow analysis and fault characteristic analysis under the same comprehensive simulation model, achieving integrated design of power flow analysis and fault characteristic analysis. This can simultaneously support the comprehensive needs of microgrid operation optimization, fault diagnosis, and protection strategy formulation.

[0039] In some embodiments, the multiple types of fault modules include multiple fault modules corresponding to each power equipment module. Each fault module is connected to the corresponding power equipment module and is used to simulate a type of fault, that is, each power equipment module is configured with multiple fault modules.

[0040] In this embodiment, multiple types of fault modules are configured in a one-to-one correspondence with each power equipment module. That is, for each power equipment module in the DC microgrid model, multiple fault modules are set up to connect to it. Although the power equipment module is connected to the fault module, the connection here does not refer to the conducting state. Without fault analysis, the fault module is in a disconnected state. These fault modules correspond to different types of faults.

[0041] For example, for a photovoltaic power module, a bipolar short-circuit fault module and a ground short-circuit fault module are connected to its output bus. The two fault modules are independent and do not interfere with each other, and are used to simulate bipolar short-circuit faults and ground short-circuit faults that occur at the output of the photovoltaic power module. Similarly, for energy storage modules, DC load modules and AC grid modules, multiple types of fault modules are configured at the output bus of each power equipment module.

[0042] The above technical solution provides each power equipment module with complete and independent fault injection capabilities, allowing for flexible selection of any device and any fault type for simulation during the simulation process. Furthermore, the fault modules of each device do not affect each other, facilitating comparative analysis of the system response after different device faults.

[0043] In another embodiment, the multiple types of fault modules include multiple fault modules, each fault module corresponding to a type of fault, and each fault module is used to simulate the corresponding type of fault occurring at various power devices, that is, each fault module corresponds to a fault type and is reused for multiple power devices.

[0044] In this embodiment, each fault module corresponds to a specific fault type. However, the fault module is not fixedly connected to a certain power equipment module. Instead, it is designed as a movable or switchable general fault injection unit to simulate the corresponding type of fault occurring at various power equipment.

[0045] In detail, the system is equipped with only one bipolar short-circuit fault module and one ground short-circuit fault module, and these two fault modules are not pre-connected to any specific device.

[0046] When simulating a bipolar short-circuit fault at the photovoltaic power module, the bipolar short-circuit fault module is dynamically connected to the corresponding node of the photovoltaic power module's output bus and its conduction is controlled; when simulating a ground short-circuit fault at the energy storage module, the ground short-circuit fault module is switched to the corresponding node of the energy storage module's output bus.

[0047] In addition, standardized fault access interfaces can be reserved in advance at the output bus of all power equipment modules, and controllable switching between a single fault module and different devices can be achieved through a multi-way selection switch.

[0048] The above technical solution requires fewer fault modules, has a simpler system structure, and facilitates automated batch simulation of various fault scenarios through switching logic.

[0049] In some embodiments, the multiple types of fault modules include a fault module for bipolar short circuit faults and a fault module for ground short circuit faults. The fault module for bipolar short circuit faults is connected between the positive and negative poles of the output bus of the target power equipment module, and the fault module for ground short circuit faults is connected between the positive pole of the output bus of the target power equipment module and the grounding reference point or between the negative pole of the output bus of the target power equipment module and the reference point.

[0050] In this embodiment, the multiple types of fault modules specifically include a fault module for simulating a bipolar short-circuit fault and a fault module for simulating a ground fault. The bipolar short-circuit fault module is connected as follows: it is connected across the positive and negative poles of the output busbar of the target power equipment module. When the fault module is turned on, the positive and negative poles are directly short-circuited, forming an inter-pole short-circuit loop, thereby simulating a bipolar short-circuit fault occurring at the equipment's output.

[0051] There are two connection methods for the ground fault module: one is to connect the fault module between the positive terminal of the output busbar of the target power equipment module and the grounding reference point to simulate a positive-to-ground short-circuit fault; the other is to connect the fault module between the negative terminal of the output busbar of the target power equipment module and the grounding reference point to simulate a negative-to-ground short-circuit fault. By selecting one of the above two connection methods or configuring both simultaneously, different types (positive-to-ground or negative-to-ground) of ground faults can be flexibly simulated. The above bipolar short-circuit fault module and the ground fault module are set independently, and their on / off states can be controlled separately according to simulation requirements, thereby achieving flexible simulation of different fault types and severity levels in the same simulation model.

[0052] In some embodiments, the fault module mentioned in this application can not only adjust the on / off state, but also further adjust the fault impedance value when a specific fault is connected, thereby performing more refined fault analysis and power flow analysis.

[0053] The on / off state of the fault module controls the timing and duration of the fault: when the fault module is off, the system operates normally, allowing for steady-state power flow analysis; when the fault module switches to on, a fault occurs, and the system enters a transient fault state. Furthermore, the fault module has independent adjustment capabilities for its fault impedance value. After the fault module is on, the resistance value of the adjustable resistor connected in series within the module can be modified to simulate fault scenarios of varying severity: lower impedance values ​​result in larger short-circuit currents and more severe faults, suitable for simulating extreme conditions such as metallic short circuits; higher impedance values ​​result in smaller short-circuit currents, suitable for simulating minor fault scenarios such as short circuits through transition resistors or high-resistance grounding faults. By independently adjusting the on / off state and fault impedance value, the occurrence and severity of faults can be controlled separately within the same simulation model. This comprehensively covers various fault types, from metallic short circuits to high-resistance faults, and obtains transient fault characteristics and power flow distribution changes under different fault impedance conditions, providing more comprehensive and refined simulation data support for microgrid operation strategy optimization.

[0054] The following examples illustrate how to obtain a comprehensive simulation model of a DC microgrid.

[0055] In some embodiments, a comprehensive simulation model of the DC microgrid is obtained, such as... Figure 2 As shown, it includes: Step 201: Based on the network topology of the DC microgrid, determine the multiple power equipment types in the DC microgrid, with each power equipment type corresponding to at least one power equipment module.

[0056] For example, the network topology includes at least: the physical connection relationship of each power device in the microgrid, access node information, and branch transmission parameters.

[0057] The physical connections of the various power devices—how they are interconnected via lines or converters—determine the power flow path. Access node information, the specific connection location of each device module on the DC bus, is used to locate nodes and fault injection points. Branch transmission parameters, such as the resistance and inductance of the connecting lines, directly affect power flow calculations and fault transient characteristics. These three types of information collectively constitute the topological foundation of the DC microgrid simulation model.

[0058] After obtaining the network topology of the DC microgrid, the types of multiple power equipment in the DC microgrid are determined through topology analysis and identification. Specifically, the physical connections in the topology are analyzed, and the characteristics of the equipment connected to each branch end and the converter configuration are identified. Through this method, the connections in the topology are mapped to equipment function classifications, thereby determining the multiple types of power equipment included in the DC microgrid.

[0059] For example, the multiple power equipment types include at least one of power supply equipment, power transmission and distribution equipment, energy storage equipment, power consumption equipment, and power conversion equipment. Each power equipment type corresponds to at least one power equipment module.

[0060] In some embodiments, the plurality of power equipment modules include devices corresponding to at least one of the following types: At least one of an AC power grid module and a photovoltaic power module corresponding to power supply equipment; at least one of a transformer module, a line module, and a DC bus module corresponding to power transmission and distribution equipment; at least one of an energy storage module corresponding to energy storage equipment, a DC load module corresponding to power consumption equipment, and an AC / DC converter module and a DC / DC converter module corresponding to power conversion equipment.

[0061] Existing technical solutions mostly focus on modeling single power sources or simplified topologies, lacking sufficient integration for differentiated control strategies of multi-source units such as AC power grids, photovoltaics, energy storage, and loads. The aforementioned technical solution, by encompassing multiple equipment modules including AC power grids, photovoltaics, energy storage, loads, converters, transformers, lines, and buses, achieves full-process coverage of multi-source low-voltage DC microgrids, solving the problem of insufficient multi-source integration in existing technologies. This allows subsequent models to accurately reproduce the collaborative operation characteristics between multi-source devices.

[0062] For example, such as Figure 3 As shown, Figure 3 This is a schematic diagram of a multi-source low-voltage DC microgrid topology proposed in an embodiment of this application.

[0063] This network topology includes AC power grid modules corresponding to power supply equipment, transformer modules and DC bus modules corresponding to power transmission and distribution equipment, energy storage modules corresponding to energy storage equipment, DC load modules corresponding to power consumption equipment, and photovoltaic modules.

[0064] Step 202: Establish mathematical models for each power equipment module based on multiple power equipment types.

[0065] Each type of power equipment corresponds to at least one power equipment module. Based on multiple power equipment types, a mathematical model for each power equipment module is established.

[0066] For each type of power equipment module, corresponding time-domain mathematical equations are established based on its physical operating principle. For example, the DC bus module can use an equivalent capacitance model. Each mathematical model includes interface parameters that match the node information in the network topology, providing a unified electrical interface for module interconnection in the subsequent simulation platform.

[0067] Each power equipment module includes, for example: Figure 3The mathematical models of each power equipment module are obtained from the various modules shown.

[0068] Step 203: Determine the DC microgrid model based on the mathematical models of each power equipment module and the network topology.

[0069] Based on the mathematical model of the power equipment module, the corresponding connection of the power equipment module is selected in the simulation platform to construct the initial simulation model of the multi-source low-voltage DC microgrid.

[0070] For example, the network topology and the mathematical models of each power equipment module are mapped one by one to the simulation platform, wherein the DC-side power equipment module is interconnected with the DC bus module through the DC / DC converter module, and the AC-side power equipment module is isolated from the DC side through the AC / DC converter module.

[0071] For example, the DC / DC converter module includes three types of sub-converters: Buck, Boost, and Buck-Boost. The Buck converter is a buck converter, whose output voltage is lower than the input voltage, and its voltage gain is equal to the duty cycle D (D<1). The Boost converter is a boost converter, whose output voltage is higher than the input voltage, and its voltage gain is equal to 1 / (1-D) (D is the duty cycle). The Buck-Boost converter is a buck-boost converter, whose output voltage can be lower or higher than the input voltage, its voltage gain is equal to D / (1-D), and its output voltage polarity is opposite to the input voltage (anti-polarity topology) or the same as the input voltage (four-switch non-inverting topology). The Buck-Boost converter can achieve stable bidirectional power flow across the entire SOC range. By selecting an appropriate topology from these three types of converters, flexible interconnection and power matching between DC power supplies, energy storage units, and loads of different voltage levels and the common DC bus can be achieved.

[0072] For example, the input and output voltage levels and current ranges of each power equipment module are matched with the parameters of the corresponding connection nodes to ensure that there are no electrical parameter conflicts after interconnection; after interconnection, the topology connectivity is checked to confirm that there are no short circuits or misconnections.

[0073] For example, based on the mathematical model of the power equipment module, simulation elements corresponding to each power equipment module are selected in the simulation platform, and the modules are electrically connected according to the network topology to construct the initial simulation model of the multi-source low-voltage DC microgrid.

[0074] For example, such as Figure 4 As shown, Figure 4This is a schematic diagram of the simulation model of the multi-source low-voltage DC microgrid AC power supply grid module, transformer module, AC line module and AC / DC converter module in the embodiments of this application. The AC power supply grid is stepped down by the transformer and then connected to the AC side of the AC / DC converter through the AC line. The DC side of the AC / DC converter is connected to the DC bus.

[0075] For example, such as Figure 5 As shown, Figure 5 This is a schematic diagram of the simulation model of the DC bus of the multi-source low-voltage DC microgrid in the embodiments of this application. The DC bus adopts the equivalent capacitance model.

[0076] For example, such as Figure 6 As shown, Figure 6 This is a schematic diagram of the simulation model of the multi-source low-voltage DC microgrid DC / DC converter module (Boost converter) and photovoltaic module in the embodiments of this application. The photovoltaic module is connected to the DC bus after being boosted by the Boost converter. The duty cycle of the Boost converter is adjusted by the maximum power point tracking control signal.

[0077] For example, such as Figure 7 As shown, Figure 7 This is a schematic diagram of the simulation model of the multi-source low-voltage DC microgrid DC / DC converter module (Buck-Boost converter) and energy storage module in the embodiments of this application. The energy storage module is connected to the DC bus via the bidirectional Buck-Boost converter, supporting bidirectional energy flow.

[0078] For example, such as Figure 8 As shown, Figure 8 This is a schematic diagram of a simulation model of a multi-source low-voltage DC microgrid DC / DC converter module (Buck converter) in an embodiment of the present invention. The Buck converter is used to step down the DC bus voltage to supply power to a specific DC load.

[0079] For example, such as Figure 9 As shown, Figure 9 This is a schematic diagram of the simulation model of the DC load module of the multi-source low-voltage DC microgrid in an embodiment of the present invention. The DC load module adopts a brushless direct current motor (BLDC) model, which is constructed based on the power supply characteristics of the DC microgrid and the BLDC electronic switching mechanism. It includes three parts: DC input, three-phase inverter and motor body.

[0080] Through the interconnection of the above modules, an initial simulation model of a multi-source low-voltage DC microgrid, including AC power grid, photovoltaic, energy storage, and DC load, is formed. The initial simulation model is then tested and optimized under preset typical operating conditions to obtain a multi-source low-voltage DC microgrid model.

[0081] Step 204: Set multiple types of fault modules in the DC microgrid model to obtain a comprehensive simulation model.

[0082] Determine the location of the fault modules. Fault modules are selectively located at key electrical nodes in the DC microgrid model based on fault simulation requirements. Specifically, the locations can include two categories: first, DC bus nodes, i.e., the connections between the positive and negative terminals of the DC bus, which serves as the common connection point for all power equipment modules, and between the positive / negative terminals and the grounding reference point; second, the output bus nodes of each power equipment module, i.e., the connection point between each power equipment module (such as photovoltaic power modules, energy storage modules, DC load modules, AC power grid modules, etc.) and its own DC / DC converter or AC / DC converter and the DC bus.

[0083] For each type of fault module, its electrical connection method corresponds to the type of fault it is simulating.

[0084] For example, a bipolar short-circuit fault can be simulated by controlling the closure of a fault module connected between the positive and negative poles of the DC bus or the output bus of each unit, which is connected to the DC bus or the output bus of each unit. This simulates an inter-pole short-circuit fault caused by a preset short-circuit impedance.

[0085] For example, a bipolar short-circuit fault at the DC bus module, photovoltaic power module, and energy storage module is taken as an example.

[0086] A DC bus two-stage short-circuit fault can be simulated by controlling the closure of a fault module connected between the positive and negative poles of the DC bus, thus mimicking an inter-pole short-circuit fault caused by a preset short-circuit impedance.

[0087] A bipolar short-circuit fault on a photovoltaic bus can be simulated by controlling the closure of a fault module connected between the positive and negative poles of the photovoltaic power module's output bus, thus mimicking a short-circuit fault occurring through a preset short-circuit impedance.

[0088] A bipolar short-circuit fault on the energy storage bus can be simulated by controlling the closure of the fault module connected between the positive and negative poles of the energy storage module's outlet bus, thus mimicking an inter-pole short-circuit fault caused by a preset short-circuit impedance.

[0089] For example, a ground short circuit fault can be simulated by controlling the closure of a fault module connected between the positive or negative terminal of the DC bus or the output bus of each unit and the ground reference point.

[0090] For example, a grounding short-circuit fault at the DC bus module, photovoltaic power module, and energy storage module is taken as an example.

[0091] A DC bus grounding short circuit fault can be simulated by controlling the closure of a fault module connected between the positive or negative terminal of the DC bus and the grounding reference point.

[0092] A photovoltaic bus grounding short circuit fault can be simulated by controlling the closure of the fault module connected between the positive or negative poles of the photovoltaic power module's output bus, thus mimicking an inter-pole short circuit fault caused by a preset short circuit impedance.

[0093] A ground fault in the energy storage bus can be simulated by controlling the closure of the fault module connected between the positive or negative poles of the energy storage module's outlet bus, thus mimicking an inter-pole short-circuit fault caused by a preset short-circuit impedance.

[0094] In the following embodiments, exemplary mathematical models of various power equipment modules are presented.

[0095] For example, the power grid module is represented by a three-phase voltage source with internal resistance, and the time-domain mathematical model is as follows:

[0096] In the formula, This represents three phases: A, B, and C. ; This refers to the voltage output of each phase of the three-phase voltage source module with internal resistance. Let the voltage of each phase of an ideal three-phase voltage source be expressed as: , For ideal phase voltage peak value, The angular frequency of the power grid; The current flowing through the equivalent internal resistance of each phase; This is the equivalent internal resistance of each phase.

[0097] For example, a photovoltaic power module can employ a nonlinear power supply model affected by light and temperature, and its time-domain mathematical model is expressed as follows:

[0098] Among them, photocurrent It is positively correlated with light intensity and temperature; reverse saturation current It increases exponentially with increasing temperature; where, This refers to the photocurrent under standard operating conditions. This represents the actual light intensity. For standard reference illumination intensity; This refers to the actual battery temperature. Standard reference temperature; The temperature coefficient of photocurrent; This refers to the reverse saturation current under standard operating conditions. It represents the electron charge. The bandgap width of photovoltaic cells; Ideal factor; Boltzmann's constant; This refers to the output voltage of the photovoltaic power module. For photovoltaic power supply series resistance; This is the parallel resistor for the photovoltaic power supply.

[0099] For example, the time-domain mathematical model of the transformer module is as follows:

[0100]

[0101]

[0102] In the formula, For the primary side of the transformer Phase input voltage; For the primary side of the transformer The instantaneous current of the phase; For the secondary side of the transformer Phase output voltage; For the secondary side of the transformer The instantaneous current of the phase; For transformer The excitation current of the phase; This refers to the resistance of the primary winding of the transformer. This refers to the resistance of the secondary winding of the transformer. This refers to the leakage inductance on the primary side of the transformer. For leakage inductance on the secondary side of the transformer; For transformer magnetizing inductance; This refers to the transformer turns ratio.

[0103] For example, the line module may include an AC line module and a DC line module. The line module is constructed as an impedance series on the AC side and as a pure resistor on the DC side. The time-domain mathematical model of the AC line module is as follows:

[0104] In the formula, For the communication side Voltage per phase at the output terminal of the phase line; For the communication side Voltage per phase at the input terminal of the phase line; For flow through the AC side The current in the phase line; The equivalent resistance of each phase line on the AC side; This is the equivalent inductance of each phase line on the AC side.

[0105] For example, the time-domain mathematical model of the DC line module is as follows:

[0106] In the formula, This refers to the output voltage of the DC-side line. This refers to the input voltage of the DC-side line. This refers to the current flowing through the DC side of the circuit. This is the equivalent resistance value of the DC side line.

[0107] For example, the DC bus module adopts an equivalent capacitance model, and its time-domain mathematical model is expressed as follows:

[0108] in, This is the equivalent capacitance value of the DC bus. This is the instantaneous voltage of the DC bus, i.e., the output voltage of the DC bus; This represents the total instantaneous current flowing into the DC bus; This is the total instantaneous current flowing out of the DC bus.

[0109] For example, the energy storage module is represented by a lithium-ion battery model, and its time-domain mathematical model is expressed as follows: Battery terminal voltage equation:

[0110] Among them, the polarization voltage equation is: ,

[0111] Equation for calculating State of Charge (SOC):

[0112] In the formula, This refers to the terminal voltage of the lithium-ion battery. The open-circuit voltages at different SOCs; This refers to the current of a lithium-ion battery. The internal resistance is ohmic; Polarization voltage; The polarization time constant; Polarization resistor; Polarizing capacitor; For the initial ; This refers to the battery's rated capacity. This refers to the charge / discharge efficiency.

[0113] For example, the DC load model is established as a brushless DC motor (BLDC) model, constructed based on the power supply characteristics of DC microgrids and the BLDC electronic switching mechanism. It adopts an integrated model of DC input, three-phase inverter, and motor body, and its time-domain mathematical model is expressed as follows: 1) Stator voltage balance equation:

[0114] 2) Back electromotive force equation of trapezoidal wave:

[0115]

[0116] 3) Equations of mechanical motion:

[0117]

[0118] In the above formula, For symbolic functions, , It is a trapezoidal wave function with an amplitude of 1 in the flat-top region; , , For the instantaneous three-phase stator voltage of BLDC, , , For the instantaneous three-phase stator current of the BLDC, , , The back electromotive force of the BLDC stator three-phase trapezoidal wave; The equivalent resistance per phase of the stator winding. The equivalent inductance per phase of the stator winding, This represents the peak value of the back electromotive force of the phase winding. This represents the number of pole pairs of the motor. The moment of inertia of the motor rotor. The coefficient of viscous friction, For mechanical angular velocity, For mechanical angles, Electric angular velocity, It is an electrical angle; For electromagnetic torque, This is the load resistance torque.

[0119] For example, the mathematical model of the AC / DC converter module is as follows:

[0120] In the formula, This refers to the DC-side output voltage of the AC / DC converter. This represents the effective value of the line voltage input to the AC side of the AC / DC converter. The equivalent duty cycle of the switching devices in the AC / DC converter; This refers to the voltage drop caused by losses in the AC / DC converter.

[0121] For example, the DC / DC converter module includes three types of sub-converters: Buck, Boost, and Buck-Boost, whose mathematical models are expressed as follows: 1) Mathematical model of Buck converter

[0122] 2) Mathematical model of Boost converter

[0123] 3) Mathematical model of Buck-Boost converter

[0124] In the formula, This refers to the output voltage of the DC / DC converter. Input voltage for the DC / DC converter; Duty cycle of the switching devices in the DC / DC converter; This refers to the voltage drop caused by losses in the DC / DC converter.

[0125] After obtaining the mathematical models of each power equipment module, the following examples illustrate how to determine the DC microgrid model based on the mathematical models of each power equipment module and the network topology.

[0126] In some embodiments, a DC microgrid model is determined based on the mathematical models of each power equipment module and the network topology, such as... Figure 10 As shown, it includes: Step 1001: Based on the mathematical models of each power equipment module and the network topology, construct the initial simulation model.

[0127] The mathematical models of each power equipment module established in step 202 are used as the basic components for simulation. Then, based on the determined network topology, the simulation components corresponding to each power equipment module are interconnected in the simulation platform according to their electrical connections. After interconnection, a topology connectivity check is performed to confirm the absence of short circuits, misconnections, or floating nodes, thereby constructing an initial simulation model that reflects the actual electrical characteristics of the DC microgrid. The execution process of this step has been discussed in detail in step 203 and will not be repeated here.

[0128] Step 1002: Determine the steady-state simulation parameters corresponding to each power equipment module, and obtain the initial simulation model after steady-state calibration. The error between the output value of the initial simulation model after steady-state calibration and the benchmark value is less than the set threshold.

[0129] Based on actual microgrid design values ​​or typical microgrid operating data, a benchmark value is set, which includes at least the rated DC bus voltage, the maximum output power of the photovoltaic unit, and the rated capacity of the energy storage unit.

[0130] The steady-state simulation parameters for each power equipment module are determined to obtain a steady-state calibrated initial simulation model. The error between the output value and the reference value of the steady-state calibrated initial simulation model is less than a set threshold. Specifically, standard test conditions are set, and the steady-state simulation parameters for each power equipment module are determined under these conditions. Then, the initial simulation model is run to steady state, and the output values ​​are measured. These output values ​​are compared with pre-set reference values, and the error is calculated. If the error exceeds the set threshold, the steady-state simulation parameters for each power equipment module are adjusted, and the simulation is repeated until the error between all output values ​​and the reference value is less than the set threshold, thus obtaining the steady-state calibrated initial simulation model.

[0131] For example, steady-state simulation parameters may include the photovoltaic power module's photocurrent coefficient and series resistance value, the energy storage module's open-circuit voltage-SOC curve parameters and ohmic internal resistance value, the converter module's initial duty cycle value, and the proportional-integral parameters of the voltage / current control loop, etc.

[0132] Step 1003: When the equipment parameters of at least one of the multiple power equipment modules change, adjust the dynamic simulation parameters of each power equipment module until the dynamic response index of the initial simulation model after steady-state calibration meets the preset dynamic response index, and obtain the dynamic calibration initial simulation model; the dynamic response index includes at least one of the following: transient voltage drop of the bus voltage, voltage rise of the bus voltage, and voltage recovery time of each power equipment module.

[0133] This step is for the dynamic performance calibration of the initial simulation model, clarifying the dynamic response indicators of the DC microgrid from unstable to stable. The dynamic response indicators include at least one of the following: transient voltage drop of the bus voltage of each power equipment module, the magnitude of the bus voltage rise, and the voltage recovery time.

[0134] In the initial simulation model, the equipment parameters of at least one power equipment module are changed, which means that the initial simulation model that has been calibrated in steady state is disturbed. The dynamic simulation parameters of each power equipment module are adjusted until the dynamic response index of the initial simulation model meets the preset dynamic response index, and the dynamic calibrated initial simulation model is obtained.

[0135] For example, the equipment parameters include at least one of photovoltaic power, energy storage charging, energy storage discharging, and load. Changes in these equipment parameters cause disturbances to the initial simulation model, which has already undergone steady-state calibration. For example, changing the equipment parameters can cause various disturbances such as photovoltaic power fluctuations, energy storage charging / discharging switching disturbances, and sudden load changes.

[0136] For example, dynamic simulation parameters may include the power response limit of the energy storage module, the equivalent capacitance of the DC bus, and so on.

[0137] Step 1004: For each of the various operating scenarios, verify the initial simulation model after steady-state calibration and the initial simulation model after dynamic calibration to obtain the DC microgrid model.

[0138] The simulation model was set up to include a combined operation scenario that includes random photovoltaic power output, energy storage charging and discharging switching, and random starting of motor loads. The simulation model calibrated by the above two steps was verified to show that its overall power flow distribution and dynamic process conform to physical laws.

[0139] For each operating scenario, both the initial simulation model after steady-state calibration and the initial simulation model after dynamic calibration are run. For the model after steady-state calibration, it is verified whether the steady-state power flow distribution under different scenarios conforms to physical laws. For example, verifying node power balance, verifying that the bus voltage remains within the allowable range under different scenarios, and verifying that the current of each branch does not exceed the rated value of the equipment. For the model after dynamic calibration, it is verified whether the dynamic process during scenario switching or disturbances conforms to physical laws. For example, verifying that the voltage change trajectory is continuous without jumps, verifying that the change in energy storage SOC is consistent with the integral of the charging and discharging current, and verifying that the response timing of each controller is reasonable (e.g., after a disturbance, the energy storage converter starts power response after a reasonable delay). If abnormal model output is found in some scenarios (e.g., divergent oscillation, voltage exceeding limits, power imbalance), return to step 1002 or step 1003 to further adjust the steady-state or dynamic parameters until all operating scenarios are verified, thus obtaining the final usable DC microgrid model.

[0140] The above technical solution, through joint verification of multiple operating scenarios following steady-state parameter simulation and dynamic parameter simulation, ensures the robustness and accuracy of the simulation model under real-world complex operating environments. It solves the problem in existing technologies where model verification relies only on a single or a few typical operating conditions and lacks sufficient coverage of multi-factor coupled scenarios, significantly improving the model's reliability under complex conditions. Furthermore, by verifying the model separately after steady-state and dynamic calibration, the steady-state accuracy and dynamic response capability of the model can be independently evaluated, facilitating the location and correction of model defects and ensuring that the model output fully conforms to the laws of electrical physics. In particular, through multi-scenario iterative calibration, the final DC microgrid model exhibits excellent generalization ability, adapting to different operating conditions and control strategies, providing a high-fidelity simulation platform for subsequent power flow analysis, fault simulation, and protection strategy formulation.

[0141] After obtaining the DC microgrid model, multiple types of fault modules are set in the DC microgrid model to obtain a comprehensive simulation model. Through simulation analysis using the comprehensive simulation model, the fault characteristics and power flow analysis of the DC microgrid under the target fault are obtained.

[0142] The following embodiments illustrate the overall process of the self-retained microgrid proposed in this application. For example... Figure 11 As shown.

[0143] Step 1101: Based on the network topology of the DC microgrid, determine the multiple power equipment types in the DC microgrid, with each power equipment type corresponding to at least one power equipment module. Step 1102: Establish mathematical models for each power equipment module based on the multiple power equipment types. Step 1103: Construct an initial simulation model based on the mathematical models of each power equipment module and the network topology. Step 1104: Test and optimize the initial simulation model to obtain the DC microgrid model. Step 1105: Set multiple types of fault modules in the DC microgrid model to obtain a comprehensive simulation model. Step 1106: Control the target fault module connected to the target power equipment module to be in a conducting state to simulate the target fault occurring at the target power equipment. Step 1107: Perform simulation analysis through the comprehensive simulation model to obtain the fault characteristic analysis and power flow analysis of the DC microgrid under the target fault.

[0144] It should be understood that the above steps have been discussed in detail in the above embodiments, and will not be repeated here.

[0145] In some implementations, the method provided in the above embodiments is adopted. It is assumed that an AC power grid is connected to the low-voltage DC microgrid, with one photovoltaic (PV) unit, one energy storage unit, and two BLDC motor loads configured. The PV unit has a rated power of 5.3kW, and the energy storage unit is in a charging state with a charging power of 3kW. The simulation process is assumed to last 2 or 3 seconds. At t0=0s, the microgrid starts operating; at t1=0.3s, the motor starts; at t2=0.6s, the load suddenly changes; at t3=1.2s, a short-circuit fault occurs in the microgrid, lasting Δt=0.05s. The fault is either a bipolar short-circuit fault or a ground fault, and the fault location is either the DC bus, the PV bus, the energy storage bus, or a certain load bus.

[0146] During the normal startup and operation phase of the microgrid, at the initial startup stage (t0=0s), the DC bus voltage rapidly jumps from 0, then quickly converges and stabilizes near the 750V reference voltage. During this phase, voltage fluctuations are minimal, maintaining a stable operating state. When t2=0.6s, a sudden load change occurs, and this disturbance is gradually transferred to the DC bus, causing dynamic fluctuations in the DC bus voltage. At t4=0.84s, the DC bus voltage experiences a significant drop of 9.3%. Subsequently, the system enters a voltage regulation process. At t5=0.86s, the DC bus voltage experiences a 3% overshoot, after which the voltage stabilizes again, returning to near the 750V reference voltage. This completes the dynamic response process of the DC bus voltage after a sudden load change: "drop-overshoot-recovery." Figure 12 The process is shown.

[0147] After a bipolar short-circuit fault occurred on the DC bus side at t3=1.2s, the DC bus voltage collapsed, plummeting to a low voltage range of 0V, and then remained in this low voltage state, demonstrating the destructive impact of the fault on the voltage. The short-circuit current experienced an instantaneous peak, surged sharply, and then quickly fell back, eventually stabilizing at a low current level with small fluctuations, reflecting the current surge characteristics at the moment of the short circuit. The AC side current exhibited a large-amplitude periodic sinusoidal oscillation, maintaining a continuous AC fluctuation state, i.e. Figure 13 The process is shown.

[0148] After a ground fault occurs on the DC bus side at t3=1.2s, the DC bus voltage initially drops briefly, then enters a sustained oscillating upward process, eventually exhibiting periodic fluctuations in the range above the initial voltage, reflecting the DC bus voltage response characteristics during a ground fault. The short-circuit current experiences an instantaneous surge, followed by continuous oscillations in a high-amplitude range, maintaining a large current level. The AC current immediately exhibits large-amplitude periodic oscillations, with a significantly increased amplitude and continuous fluctuations. Figure 14 The process is shown.

[0149] After a short-circuit fault occurred on the photovoltaic bus side at t3=1.2s, the DC voltage bus was minimally affected by the photovoltaic bus short circuit and remained stable near its original voltage level without significant drops or surges, demonstrating the system's voltage regulation capability in the face of photovoltaic bus short circuits. The short-circuit current instantaneously generated a large, impactful current peak; the photovoltaic unit voltage dropped sharply, rapidly decreasing to a low voltage state close to 0V; the photovoltaic unit current initially dropped briefly, then transitioned to a stepped, segmented, stable fluctuation pattern, with both amplitude and fluctuation characteristics significantly altered. Figure 15 The process is shown.

[0150] After a ground fault occurred on the photovoltaic bus side at t3=1.2s, the DC bus voltage experienced a brief, small fluctuation due to the impact of the photovoltaic bus ground fault, but quickly recovered and maintained its original voltage level, indicating that the DC bus has strong resistance to disturbances from the photovoltaic side ground fault. The short-circuit current instantaneously generated an impactful spike current, but the peak duration was extremely short, and it quickly dropped back to near 0. The photovoltaic unit voltage experienced a sharp transient drop and oscillation, followed by a rapid recovery, eventually returning to a range close to its original voltage, exhibiting a dynamic response characteristic of "transient disturbance - rapid recovery". The photovoltaic unit current first experienced a brief jump disturbance, followed by a slight change in the fluctuation pattern, but the amplitude remained near the original range without a sustained large deviation, eventually recovering to the state of periodic small fluctuations and stable amplitude before the fault. Figure 16 The process is shown.

[0151] After a short-circuit fault occurred on the energy storage bus side at t3=1.2s, the DC voltage bus was minimally affected by the short circuit and remained stable near its original voltage level without significant drops or surges, demonstrating the system's voltage regulation capability in the face of an inter-electrode short circuit. The instantaneous generation of a large, impulsive short-circuit current reflects the rapid rise in fault current after a low-resistance path is formed by the inter-electrode short circuit. The energy storage unit voltage experienced a sharp drop, rapidly falling to near 0V. The energy storage unit current instantaneously generated a large negative inrush current, subsequently fluctuating at a high current level, demonstrating the characteristic of high-current discharge from inter-electrode short-circuit energy storage to the short-circuit point. Figure 17 The process is shown.

[0152] After a ground fault occurs on the energy storage bus side at t3=1.2s, the DC bus voltage rapidly generates a transient voltage spike approximately 1.4 times its original voltage, then slowly declines and stabilizes in a range close to its original voltage, demonstrating the DC bus's transient immunity to ground faults on the energy storage side. The short-circuit current experiences a sudden, large surge, then oscillates within a relatively high amplitude range. The energy storage unit voltage drops sharply, then rapidly climbs to a lower range of 400-500V and oscillates continuously. The energy storage unit current experiences a sudden, large negative surge, then oscillates continuously in a high-current range, demonstrating the characteristics of high-current discharge from the ground fault energy storage to the short-circuit point. Figure 18 The process is shown.

[0153] After a bipolar short-circuit fault occurred on the load bus side at t3=1.2s, the DC bus voltage remained within its original voltage range, demonstrating the strong anti-disturbance capability of the DC bus against the load bipolar short circuit. The load bus short-circuit current instantaneously generated a large, impactful current peak. The load unit voltage dropped sharply to a low voltage state close to 0V. The load unit current fluctuation amplitude significantly increased, exhibiting chaotic and irregular disturbance waveforms, subsequently trending towards 0A. The actual motor speed dropped rapidly, significantly deviating from the reference speed, eventually reaching a lower value. This indicates that the load bus short-circuit fault affected the normal operation of the motor, leading to speed instability. Figure 19 The process is shown.

[0154] After a ground fault occurred on the load bus side at t3=1.2s, the DC bus voltage only showed a brief, small spike, then quickly recovered to its original stable range, demonstrating the strong immunity of the DC bus to ground faults on the load side. The load bus short-circuit current instantaneously generated an impactful current peak, but the peak duration was short, followed by brief fluctuations and a rapid decline. The load unit voltage dropped sharply, then oscillated in a lower voltage range of approximately 400V for about 0.05s, finally slowly decreasing to 0V. The load unit current amplitude decreased slightly, and the oscillation frequency increased. At t6=1.4s, the amplitude suddenly increased and decreased, then returned to its state before t6, eventually slowly decreasing to around 0A. The actual motor speed slightly overshooted at t6=1.4s, indicating that it was affected by a short circuit. The control system triggered the adjustment mechanism. After the overshoot, the feedback correction mechanism of the control system quickly intervened, pulling the speed back to the original stable value. As the impact of the fault continued to accumulate, the actual disturbance exceeded the system's adjustment capability. At t7=2.3s, the motor speed gradually dropped, significantly deviating from the reference speed, and eventually fluctuated around 0A. This indicates that the short circuit to the load bus ground caused the motor to become unstable. Figure 20 The process is shown.

[0155] It should be understood that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart above may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0156] In some embodiments, such as Figure 21 As shown, an analysis device for a DC microgrid is provided, comprising: an acquisition module 2101, a simulation module 2102, and an analysis module 2103, wherein: The acquisition module 2101 is used to acquire the comprehensive simulation model of the DC microgrid. The comprehensive simulation model includes the DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault.

[0157] The simulation module 2102 is used to control the target fault module connected to the target power equipment module to be in a conducting state in order to simulate the target fault that occurs at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of multiple power equipment modules. The target fault module is a fault module of any type among multiple types.

[0158] Analysis module 2103 is used to perform simulation analysis through a comprehensive simulation model to obtain the fault characteristics analysis and power flow analysis of the DC microgrid under the target fault.

[0159] Further limitations on the analysis device for DC microgrids can be found in the above description of the analysis of a DC microgrid, and will not be repeated here. Each module in the aforementioned analysis device for DC microgrids can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the terminal device, or stored in software in the memory of the terminal device, so that the processor can call and execute the operations corresponding to each module.

[0160] Another embodiment provides a computer-readable storage medium for storing a computer program. This computer program contains instructions for implementing the methods described in the embodiments of this application. By installing this computer program on a computer, the computer can execute the corresponding methods.

[0161] Another embodiment proposes a computer program product that includes computer program code. When this computer program code is run on a computer, it causes the computer to implement the methods proposed in the embodiments of this application. Thus, a user can implement these methods by using this computer program product.

[0162] In some embodiments, Figure 22 This is a schematic block diagram of the electronic device provided in the embodiments of this application.

[0163] Electronic device 2200 may include: a memory 2201 storing executable program code and a processor 2202 coupled to the memory 2201.

[0164] Specifically, processor 2202 calls executable program code stored in memory to execute any of the methods disclosed in the embodiments of this application. Those skilled in the art will understand that... Figure 22 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0165] The processor 2202 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory, and by calling data stored in the memory, thereby providing overall monitoring of the electronic device. Optionally, the processor may include one or more processing units; preferably, the processor may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor.

[0166] The memory 2201 can be used to store software programs and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0167] It should be understood that, in the embodiments of this application, the processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0168] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or as a combination of hardware and software modules within the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor executes the instructions in the memory, combining them with its hardware to complete the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0169] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this application.

[0170] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0171] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus 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 displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0172] 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.

[0173] In addition, the functional units in the various embodiments of this application 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.

[0174] If the aforementioned function 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 this application embodiment, essentially, or the part that contributes to the prior art, or a 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0175] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be included within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the claims.

Claims

1. An analysis method for DC microgrids, characterized in that, The method includes: A comprehensive simulation model of a DC microgrid is obtained. The comprehensive simulation model includes a DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault. The target fault module connected to the target power equipment module is in a conducting state to simulate a target fault occurring at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of a plurality of power equipment modules. The target fault module is a fault module of any one of a plurality of types. Through simulation analysis using the comprehensive simulation model, the fault characteristics and power flow analysis of the DC microgrid under the target fault are obtained.

2. The method according to claim 1, characterized in that, The multiple types of fault modules include multiple fault modules corresponding to each power equipment module, each fault module being connected to its corresponding power equipment module and used to simulate a type of fault; or, The multiple types of fault modules include multiple fault modules, each fault module corresponding to a type of fault, and each fault module is used to simulate the corresponding type of fault occurring at each power equipment.

3. The method according to claim 1, characterized in that, The multiple types of fault modules include a fault module for bipolar short circuit faults and a fault module for ground short circuit faults. The fault module for bipolar short circuit faults is connected between the positive and negative poles of the output bus of the target power equipment module, and the fault module for ground short circuit faults is connected between the positive pole of the output bus of the target power equipment module and the grounding reference point or between the negative pole of the output bus of the target power equipment module and the reference point.

4. The method according to claim 1, characterized in that, The process of obtaining the comprehensive simulation model of the DC microgrid includes: Based on the network topology of the DC microgrid, multiple power equipment types are determined in the DC microgrid, and each power equipment type corresponds to at least one power equipment module; Based on the various types of power equipment, establish mathematical models for each power equipment module; Based on the mathematical models of each power equipment module and the network topology, the DC microgrid model is determined; By setting the various types of fault modules in the DC microgrid model, the comprehensive simulation model is obtained.

5. The method according to claim 4, characterized in that, The determination of the DC microgrid model based on the mathematical models of each power equipment module and the network topology includes: Based on the mathematical models of each power equipment module and the network topology, an initial simulation model is constructed. Determine the steady-state simulation parameters corresponding to each power equipment module to obtain the initial simulation model after steady-state calibration. The error between the output value and the reference value of the initial simulation model after steady-state calibration is less than a set threshold. When the equipment parameters of at least one of the multiple power equipment modules change, the dynamic simulation parameters of each power equipment module are adjusted until the dynamic response index of the initial simulation model after steady-state calibration meets the preset dynamic response index, thus obtaining the initial simulation model after dynamic calibration; the dynamic response index includes at least one of the transient drop of the bus voltage of each power equipment module, the rise of the bus voltage, and the voltage recovery time. For each of the various operating scenarios, the initial simulation model after steady-state calibration and the initial simulation model after dynamic calibration are verified to obtain the DC microgrid model.

6. The method according to claim 5, characterized in that, The equipment parameters include at least one of photovoltaic power, energy storage charging, energy storage discharging, and load.

7. The method according to claim 4, characterized in that, The plurality of power equipment types include at least one of the following: power supply equipment, power transmission and distribution equipment, energy storage equipment, power consumption equipment, and power conversion equipment; The plurality of power equipment modules include at least one of the following types of equipment: At least one of the AC power grid module and photovoltaic power module corresponding to the power supply equipment. At least one of the transformer module, line module, and DC bus module corresponding to the power transmission and distribution equipment. At least one of the following: an energy storage module corresponding to the energy storage device, a DC load module corresponding to the electrical equipment, and an AC / DC converter module and a DC / DC converter module corresponding to the power conversion device.

8. An analysis device for a DC microgrid, characterized in that, The device includes: The acquisition module is used to acquire a comprehensive simulation model of a DC microgrid. The comprehensive simulation model includes a DC microgrid model and multiple types of fault modules. The DC microgrid model is used to simulate the DC microgrid. The DC microgrid model includes multiple power equipment modules for simulating multiple power devices in the DC microgrid. Each type of fault module is used to simulate the corresponding type of fault. The simulation module is used to control the target fault module connected to the target power equipment module to be in a conducting state in order to simulate the target fault occurring at the target power equipment. The target power equipment corresponds to the target power equipment module. The target fault module is used to simulate the target fault. The target power equipment module is any one of a plurality of power equipment modules. The target fault module is a fault module of any one of a plurality of types. The analysis module is used to perform simulation analysis through the comprehensive simulation model to obtain the fault characteristic analysis and power flow analysis of the DC microgrid under the target fault.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The device stores computer instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1-7.

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