A park micro-grid method, controller and system based on optical storage and direct flexible

Abstract

The application discloses a kind of park microgrid methods based on light storage direct flexible, controller and system, system includes microgrid operation control system, intelligent light storage direct flexible controller, the direct current bus connected with the direct current side of the controller and access the direct current bus of photovoltaic power generation unit, energy storage unit and at least one direct current load.The method is executed by the microgrid operation control system, including: real-time acquisition generation and load predicted power and grid state;Based on the information obtained for collaborative energy management collaborative control instruction is generated, the instruction includes operating mode instruction and associated power instruction;Instruction is issued to the intelligent light storage direct flexible controller, control its between direct current bus and alternating current grid bidirectional power exchange.The application realizes the efficient matching and optimized operation of park internal source, net, load, energy storage by constructing "direct current bus" energy platform and "centralized decision-making-unified execution" collaborative control architecture, effectively improves new energy on-site consumption rate, power supply reliability, operation economy and support ability to main grid.

Description

Technical Field

[0001] This invention relates to the fields of smart grid and distributed energy technology, and in particular to a method, controller and system for a campus microgrid based on photovoltaic-storage-DC-flexible energy storage. Background Technology

[0002] Currently, the power supply system in the industrial park faces a series of structural challenges. First, the main power grid is an AC system, while renewable energy sources such as photovoltaic and wind power are essentially DC. An increasing number of loads within the park, such as electric vehicle charging stations, LED lighting, and DC motors, are also DC loads. The existing system requires multiple AC-DC conversions, leading to system complexity, reduced efficiency, and decreased reliability. Second, the intermittency and volatility of renewable energy sources put pressure on grid stability, and traditional power consumption methods in the park lack flexible interaction with the grid, making it difficult to achieve demand-side response such as peak shaving and valley filling. Finally, the existing system lacks unified and coordinated control of power sources, grid, load, and energy storage. The local absorption rate of renewable energy needs improvement, and it is difficult to quickly form an independent microgrid during grid failures.

[0003] Therefore, there is an urgent need for a new campus-level power supply solution that can deeply integrate AC and DC characteristics, achieve efficient energy synergy, and possess flexibility and resilience. Summary of the Invention

[0004] In view of the technical defects and drawbacks existing in the prior art, the embodiments of the present invention provide a method, controller and system for a campus microgrid based on photovoltaic-storage-DC-flexible architecture to overcome the above problems or at least partially solve the above problems. The specific solution is as follows;

[0005] As a first aspect of the present invention, a collaborative control method for a park microgrid based on photovoltaic-storage-DC-flexible architecture is provided. The method is characterized by being executed by a microgrid operation control system, which is communicatively connected to an intelligent photovoltaic-storage-DC-flexible controller, a photovoltaic power generation unit, an energy storage unit, and at least one DC load. The intelligent photovoltaic-storage-DC-flexible controller is connected between the AC grid and the DC bus, and the photovoltaic power generation unit, the energy storage unit, and the at least one DC load are all connected to the DC bus. The method includes the following steps:

[0006] Data acquisition steps: Real-time acquisition of the predicted power generation of the photovoltaic power generation unit, the predicted power demand of the DC load, and the operating status information of the AC power grid;

[0007] Instruction generation step: Based on the information obtained in the data acquisition step, generate a collaborative control instruction for the coordinated energy management of the photovoltaic power generation unit, energy storage unit, DC load and AC grid. The collaborative control instruction is used to instruct the intelligent photovoltaic-storage DC-flexible controller to perform bidirectional power exchange between the DC bus and the AC grid.

[0008] Command execution steps: The coordinated control command is sent to the intelligent photovoltaic-storage DC-flexible controller to control it to perform the corresponding power conversion operation, thereby realizing the coordinated control of the source, grid, load and storage in the park microgrid.

[0009] In some embodiments, the coordinated control command includes an operating mode command and a power command; the operating mode command is used to set the intelligent photovoltaic-storage-DC-flexible controller to operate in grid-connected mode or off-grid mode; the power command is associated with the operating mode command, wherein:

[0010] When the operating mode command is set to grid-connected mode, the power command is the active power target value exchanged between the DC bus and the AC grid;

[0011] When the operating mode command is set to off-grid mode, the power command is the voltage reference value and frequency reference value output by the AC side of the intelligent photovoltaic-storage DC-flexible controller.

[0012] In some embodiments, when the operating mode instruction is set to grid-connected mode, the instruction generation step specifically includes:

[0013] Calculation steps: Based on the predicted power generation and the predicted power demand, calculate the net exchange power required on the DC bus side, where a positive value indicates that power needs to be absorbed from the outside and a negative value indicates that power can be output to the outside;

[0014] First control strategy step: In response to the AC grid being in a low-consumption period, the coordinated control command is generated, wherein the power command is set to add a positive charging power value to the net exchange power to control the intelligent photovoltaic-storage DC-flexible controller to charge the energy storage unit, thereby achieving valley filling;

[0015] The second control strategy step is as follows: In response to the AC grid being in a peak electricity consumption period, the coordinated control command is generated, wherein the power command is set to the larger of the net exchange power and a negative discharge power value, so as to control the intelligent photovoltaic-storage DC-flexible controller to prioritize the use of surplus power on the DC side, and call the energy storage unit to deliver power to the AC grid when necessary, so as to achieve peak shaving.

[0016] In some embodiments, the method further includes a black boot process in off-network mode, the black boot process comprising:

[0017] Off-grid triggering steps: When a fault is detected in the AC power grid or when it is necessary to actively disconnect from the power grid, the operating mode command is set to off-grid mode;

[0018] Black start control steps: Generate a collaborative control command corresponding to the off-grid mode, wherein the power command is set to establish a preset AC voltage and frequency reference value, and send the command to the intelligent photovoltaic-storage DC-flexible controller;

[0019] System setup steps: The intelligent photovoltaic-storage DC-flexible controller obtains electrical energy from the energy storage unit according to the received instructions, establishes and maintains an AC voltage and frequency that conforms to the preset reference value at its AC side output terminal, thereby forming an independent off-grid AC bus to supply power to the loads connected to it, and allows the photovoltaic power generation unit to resume power generation on the DC bus.

[0020] In some embodiments, during off-grid mode operation, the method further includes a virtual inertia support process, the virtual inertia support process comprising:

[0021] Frequency monitoring steps: Monitor the voltage frequency output from the AC side of the intelligent optical storage DC-flexible controller in real time;

[0022] Inertia determination steps: Calculate the rate of change of the voltage frequency. When the absolute value of the rate of change exceeds a preset threshold, it is determined that the system needs to provide virtual inertia support.

[0023] Power compensation step: Based on the rate of change of the voltage frequency, the active power compensation value is calculated according to the control algorithm of the rotor inertia of the simulated synchronous generator.

[0024] Instruction update steps: Based on the active power compensation value, update the power instruction in the collaborative control instruction, and send the updated collaborative control instruction to the intelligent photovoltaic-storage DC-flexible controller to control it to quickly adjust the active power obtained from the DC bus or output to the AC side load, thereby suppressing the fluctuation of the voltage frequency.

[0025] In some embodiments, the instruction generation step further includes a power quality management sub-step, which includes:

[0026] Power quality information acquisition steps: Acquire power quality information from the AC grid side, wherein the power quality information includes at least reactive power data and harmonic current data;

[0027] The steps for generating the governance instruction are as follows: Based on the reactive power data, calculate the reactive power value to be compensated; and / or, based on the harmonic current data, calculate the compensation current instruction for offsetting a specific harmonic.

[0028] In the instruction execution step, the coordinated control instruction issued to the intelligent photovoltaic-storage DC-flexible controller also includes a power adjustment component determined based on the required reactive power compensation value and / or the compensation current instruction, so as to control the intelligent photovoltaic-storage DC-flexible controller to perform reactive power compensation and / or harmonic suppression on the AC grid side while performing the bidirectional power exchange.

[0029] As a second aspect of the present invention, an intelligent optical storage DC-DC flexible controller for implementing the method described in any of the above claims is also provided, comprising a bidirectional AC / DC conversion main circuit, a control unit, and a communication unit;

[0030] The AC side of the bidirectional AC / DC converter main circuit is used to connect to the AC power grid, and the DC side is used to connect to the DC bus.

[0031] The control unit is connected to the bidirectional AC / DC converter main circuit and is configured to execute the instruction execution steps of the above-described photovoltaic-storage-DC-flexible campus microgrid collaborative control method, and control the working state of the bidirectional AC / DC converter main circuit according to the received collaborative control instructions.

[0032] The communication unit is connected to the control unit and is configured to perform the data acquisition step of the above-described photovoltaic-storage-DC-flexible campus microgrid collaborative control method, in order to receive the collaborative control command from the microgrid operation control system and upload the controller's operating status data.

[0033] In some embodiments, the control unit is configured to perform the steps of the method as described in any of the preceding embodiments, specifically including:

[0034] The mode switching module is configured to control the bidirectional AC / DC converter main circuit to automatically switch between grid-connected operation mode and off-grid operation mode according to the operation mode instruction in the coordinated control instruction, and to control the bidirectional AC / DC converter main circuit to work in constant voltage and constant frequency mode in the off-grid operation mode.

[0035] The power control module is configured to, in grid-connected operation mode, control the bidirectional AC / DC converter main circuit to realize a specified amount of bidirectional active power exchange between the DC bus and the AC grid according to the power command in the coordinated control command; and in off-grid operation mode, control the bidirectional AC / DC converter main circuit to establish and maintain a specified AC voltage and frequency at its AC side output terminal according to the power command.

[0036] The advanced functional module integrates a control algorithm for implementing virtual inertia support and damping control. The control algorithm is configured to dynamically calculate the active power compensation value based on the monitored AC voltage frequency changes in off-grid operation mode, and adjust the power command accordingly.

[0037] The protection and management module integrates overvoltage, undervoltage, overload, reverse current protection, islanding, and leakage protection logic, and also integrates reactive power compensation and harmonic suppression algorithms. The algorithms are configured to generate corresponding power regulation components based on the acquired power quality information, which are then superimposed on the execution logic of the power control module.

[0038] In some embodiments, the bidirectional AC / DC converter main circuit adopts a modular power unit parallel design;

[0039] The controller also includes a thermal management unit, which includes a temperature sensor and an intelligent air-cooled heat sink;

[0040] The control unit is also configured to: dynamically adjust the fan speed of the intelligent air-cooled heat sink according to the temperature of the modular power unit detected by the temperature sensor, and maintain the rated power output of the bidirectional AC / DC converter main circuit without derating when the detected temperature reaches 45°C.

[0041] As a third aspect of the present invention, a solar-storage-DC-flexible microgrid system for industrial parks is provided, comprising:

[0042] AC power grid branch lines are used to supply power to the AC loads in the park;

[0043] DC bus;

[0044] The photovoltaic power generation unit is connected to the DC bus via a first DC / DC converter;

[0045] The energy storage unit is connected to the DC bus via a second bidirectional DC / DC converter;

[0046] At least one DC load is connected to the DC bus, either directly or via a third DC / DC converter;

[0047] The intelligent photovoltaic-storage DC-flexible controller described in any of the above embodiments has its DC side connected to the DC bus and its AC side connected to the AC grid branch.

[0048] The microgrid operation control system is communicatively connected to the communication unit of the intelligent photovoltaic-storage-DC-flexible controller, the photovoltaic power generation unit, the energy storage unit, and the DC load, and is configured to execute the campus microgrid collaborative control method based on photovoltaic-storage-DC-flexible as described above.

[0049] The present invention has the following beneficial effects:

[0050] This invention provides a method for operating a solar-storage-DC-flexible microgrid in a park based on "cooperative control," achieving unified optimization and dynamic matching of energy sources, grid, loads, and storage. This fundamentally solves the problems of difficult renewable energy absorption and low energy efficiency in traditional park power grids. Specifically, this method uses a microgrid operation control system—a centralized decision-making brain—to acquire multi-dimensional information such as photovoltaic power generation, load demand, and grid status in real time. Based on this, it generates unified cooperative control commands and issues them to the intelligent solar-storage-DC-flexible controller, which acts as the energy hub. This "centralized decision-making-unified execution" architecture enables the system to dynamically and accurately schedule the energy from photovoltaic, energy storage, and DC loads on the DC bus according to real-time conditions. For example, during peak daytime photovoltaic power generation, the system can instruct the controller to prioritize the use of photovoltaic power to supply DC loads and charge energy storage batteries, maximizing local green energy absorption and reducing the purchase of electricity from the grid. During nighttime peak load periods, the controller can control energy storage discharge or optimize power exchange with the grid. This cooperative optimization significantly improves the overall energy self-sufficiency rate, operational economy, and grid friendliness of the park. Attached Figure Description

[0051] Figure 1 A flowchart illustrating a collaborative control method for a campus microgrid based on photovoltaic-storage-DC-flexible architecture, provided as an embodiment of the present invention;

[0052] Figure 2 This is a schematic diagram of a time-based peak shaving and valley filling control provided in an embodiment of the present invention;

[0053] Figure 3 This is a schematic diagram of the overall topology architecture of a collaborative control system for a solar-storage-DC-flexible microgrid in a park, provided as an embodiment of the present invention. Detailed Implementation

[0054] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0055] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0056] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0057] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0058] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0059] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0060] To address at least one of the technical problems existing in the aforementioned related technologies, this invention provides a collaborative control method for a campus microgrid based on photovoltaic-storage-DC-flexible architecture, which is executed by the microgrid operation control system. Figure 1 This is a flowchart illustrating a collaborative control method for a park microgrid based on photovoltaic-storage-DC-flexible architecture, provided by an embodiment of the present invention. The microgrid operation control system is communicatively connected to an intelligent photovoltaic-storage-DC-flexible controller, a photovoltaic power generation unit, an energy storage unit, and at least one DC load. The intelligent photovoltaic-storage-DC-flexible controller is connected between the AC grid and the DC bus. The photovoltaic power generation unit, the energy storage unit, and the at least one DC load are all connected to the DC bus. The method includes the following steps:

[0061] Data acquisition steps: Real-time acquisition of the predicted power generation of the photovoltaic power generation unit, the predicted power demand of the DC load, and the operating status information of the AC power grid;

[0062] Instruction generation step: Based on the information obtained in the data acquisition step, generate a collaborative control instruction for the coordinated energy management of the photovoltaic power generation unit, energy storage unit, DC load and AC grid. The collaborative control instruction is used to instruct the intelligent photovoltaic-storage DC-flexible controller to perform bidirectional power exchange between the DC bus and the AC grid.

[0063] Command execution steps: The coordinated control command is sent to the intelligent photovoltaic-storage DC-flexible controller to control it to perform the corresponding power conversion operation, thereby realizing the coordinated control of the source, grid, load and storage in the park microgrid.

[0064] This invention provides a method for operating a solar-storage-DC-flexible microgrid in a park based on "cooperative control," achieving unified optimization and dynamic matching of energy sources, grid, loads, and storage. This fundamentally solves the problems of difficult renewable energy absorption and low energy efficiency in traditional park power grids. Specifically, this method uses a microgrid operation control system—a centralized decision-making brain—to acquire multi-dimensional information such as photovoltaic power generation, load demand, and grid status in real time. Based on this, it generates unified cooperative control commands and issues them to the intelligent solar-storage-DC-flexible controller, which acts as the energy hub. This "centralized decision-making-unified execution" architecture enables the system to dynamically and accurately schedule the energy from photovoltaic, energy storage, and DC loads on the DC bus according to real-time conditions. For example, during peak daytime photovoltaic power generation, the system can instruct the controller to prioritize the use of photovoltaic power to supply DC loads and charge energy storage batteries, maximizing local green energy absorption and reducing the purchase of electricity from the grid. During nighttime peak load periods, the controller can control energy storage discharge or optimize power exchange with the grid. This cooperative optimization significantly improves the overall energy self-sufficiency rate, operational economy, and grid friendliness of the park.

[0065] In some embodiments, the coordinated control command includes an operating mode command and a power command; the operating mode command is used to set the intelligent photovoltaic-storage-DC-flexible controller to operate in grid-connected mode or off-grid mode; the power command is associated with the operating mode command, wherein:

[0066] When the operating mode command is set to grid-connected mode, the power command is the active power target value exchanged between the DC bus and the AC grid;

[0067] When the operating mode command is set to off-grid mode, the power command is the voltage reference value and frequency reference value output by the AC side of the intelligent photovoltaic-storage DC-flexible controller.

[0068] The above embodiments further specify and structure the "cooperative control command." Specifically, this embodiment defines the cooperative control command as consisting of two core elements: an operating mode command and a power command, and establishes a strong logical correlation between the two. This structured design allows advanced energy management strategies (such as peak shaving and valley filling, and black start) to be decomposed into combinations of these two basic parameters. For example, when the system needs to switch from grid-connected to off-grid operation, simply setting the operating mode command to "off-grid" and the power command to a preset voltage / frequency reference value allows the controller to automatically execute a complex off-grid voltage build-up and power supply process. This "mode + target" command system efficiently decouples the control logic from the execution actions of the underlying power electronic converter, making the development of upper-level energy management algorithms simpler, while also ensuring the accuracy and consistency of the controller's actions under different operating conditions.

[0069] In some embodiments, when the operating mode instruction is set to grid-connected mode, the instruction generation step specifically includes:

[0070] Calculation steps: Based on the predicted power generation and the predicted power demand, calculate the net exchange power required on the DC bus side, where a positive value indicates that power needs to be absorbed from the outside and a negative value indicates that power can be output to the outside;

[0071] First control strategy step: In response to the AC grid being in a low-consumption period, the coordinated control command is generated, wherein the power command is set to add a positive charging power value to the net exchange power to control the intelligent photovoltaic-storage DC-flexible controller to charge the energy storage unit, thereby achieving valley filling;

[0072] The second control strategy step is as follows: In response to the AC grid being in a peak electricity consumption period, the coordinated control command is generated, wherein the power command is set to the larger of the net exchange power and a negative discharge power value, so as to control the intelligent photovoltaic-storage DC-flexible controller to prioritize the use of surplus power on the DC side, and call the energy storage unit to deliver power to the AC grid when necessary, so as to achieve peak shaving.

[0073] The above embodiments specifically define an economically optimized operation strategy for "peak shaving and valley filling" under grid-connected mode. Through time-based optimized control logic, energy is guided to shift between low-price and high-price periods. Specifically, during low-price periods (typically when electricity prices are low), the system generates instructions for the controller to draw power from the grid to charge the energy storage unit, completing "valley filling." During high-price periods (typically when electricity prices are high or the grid is strained), the system generates instructions for the energy storage unit (and surplus photovoltaic power) to discharge back to the grid through the controller, achieving "peak shaving." For example, the industrial park can purchase and store electricity at a low price during the off-peak period from midnight to 8 am; during the peak period from 10 am to 12 pm, the stored electricity can be released for its own use or fed back to the grid, thus avoiding purchasing electricity at high prices and even generating revenue through electricity sales or demand response subsidies. This automated economic dispatch not only saves the industrial park considerable electricity costs but also smooths the grid load curve by peak shaving and valley filling, alleviating the power supply pressure on the grid.

[0074] Reference for control algorithms for intelligent peak shaving and valley filling in grid-connected mode Figure 2 As shown.

[0075] The following is an example of peak shaving and valley filling operation of a collaborative control system for photovoltaic-storage-direct-flexible microgrids in a park.

[0076] Assume the system hardware and parameter configuration in this embodiment are as follows:

[0077] Intelligent photovoltaic-storage DC-flexible controller: One unit, whose DC side is connected to a ±375V DC bus, and whose AC side is connected to the 380V / 50Hz AC distribution network of the park.

[0078] Photovoltaic power generation unit: 500kW installed capacity, connected to the DC bus via a DC / DC converter.

[0079] Energy storage unit: Lithium battery energy storage system with a capacity of 1MWh and a rated power of 500kW, connected to the DC bus through a bidirectional DC / DC converter.

[0080] DC loads: mainly include DC charging piles (total power 200kW), LED lighting (50kW), and some DC process equipment (150kW), with a total power of approximately 400kW. They are connected to the DC bus directly or through DC / DC converters.

[0081] Microgrid operation and control system: Deployed on a local server, it communicates with the controller, photovoltaic inverter, energy storage converter and load management system via Modbus TCP / IP protocol.

[0082] The specific implementation process is as follows:

[0083] (1) Operational scenarios and data acquisition:

[0084] Assume the system operates on a certain afternoon. The microgrid operation and control system, using historical data and weather forecast models, obtains the following predictive information (for the next control cycle, such as the next 15 minutes):

[0085] Predicted power generation (P_pv) of photovoltaic power generation unit: 300 kW (cloudy conditions during this period, not at full capacity).

[0086] Forecasted power demand for DC load (P_load): 380 kW.

[0087] AC power grid operation status information: The current time is 14:00, which is within the "peak electricity consumption period" stipulated by the power grid (e.g., 10:00-15:00); the real-time electricity price is 1.2 yuan / kWh (peak electricity price).

[0088] (2) Instruction generation and execution process

[0089] Step A: Calculate the net exchange power

[0090] The microgrid operation and control system performs the following calculations:

[0091] Net switching power P_net = P_load - P_pv = 380 kW - 300 kW = +80 kW

[0092] The calculation result of +80 kW is positive, indicating that according to the prediction, the power on the DC bus side is insufficient, and 80 kW of power needs to be absorbed from the outside (i.e., from the AC grid through the controller) to meet the DC load demand.

[0093] Step B: Determine the operating mode and power grid time period, and generate coordinated control commands.

[0094] Mode determination: Since the power grid is normal, the system is operating in grid-connected mode. Therefore, the operating mode command is set to "grid-connected mode".

[0095] Time period judgment and strategy selection: The current period is the "peak electricity consumption period", and the system triggers the "second control strategy step".

[0096] Generate specific power commands:

[0097] Strategic objective: During peak hours, the objective is to "peak shaving," which means minimizing power consumption from the grid and even feeding power back into the grid to save on electricity costs and support the grid.

[0098] Instruction calculation logic:

[0099] The system presets a "peak shaving target discharge power value" of P_discharge_target = -100 kW (a negative value indicates the expected power output to the grid during this peak period).

[0100] The calculated net exchange power P_net = +80 kW (power needs to be drawn from the grid) is compared with the target discharge power -100 kW (power is expected to be sent to the grid).

[0101] According to the formula: Power command = max(P_net, P_discharge_target) = max(+80 kW, -100kW) = +80 kW.

[0102] Since the current DC-side power is insufficient (+80 kW) to directly supply power to the grid, the system decides not to force the energy storage to discharge to -100 kW to supply power to the grid (as that would exacerbate the DC-side power shortage), but instead prioritizes ensuring power supply to the DC-side load. Therefore, the final power command is set to +80 kW. This means that the controller is commanded to absorb 80 kW of power from the grid, precisely making up for the DC-side power deficit. At this time, the energy storage unit is in standby mode.

[0103] The composition of the cooperative control instruction: The final generated instruction is a structure containing:

[0104] Operating mode command: "Grid-connected mode"

[0105] Power command: +80 kW (active power target value)

[0106] Step C: Issuance and Execution of Instructions

[0107] The microgrid operation control system sends the aforementioned coordinated control commands to the intelligent photovoltaic-storage-DC-flexible controller via the communication network.

[0108] After the controller receives the instruction:

[0109] The operating mode was determined to be "grid-connected mode", and the corresponding phase-locked loop and control logic were maintained.

[0110] The power command is determined to be +80 kW. The controller controls its internal bidirectional AC / DC converter circuit to precisely absorb 80 kW of active power from the 380V AC grid side, and after high-efficiency conversion, output it to the DC bus.

[0111] With the DC bus voltage remaining stable, the system power flow is as follows:

[0112] Photovoltaic power generation: provides 300 kW.

[0113] DC load: Consumption 380 kW.

[0114] Power deficit: 80 kW, provided by the controller drawing power from the AC grid.

[0115] Energy storage unit: Not in operation.

[0116] (3) Implementation examples after scene changes (display strategy switching)

[0117] Assume it's 11 PM that night (off-peak electricity time, with an electricity price of 0.3 yuan / kWh).

[0118] Forecast data: P_pv = 0 kW, P_load = 100 kW (lighting and basic maintenance load only).

[0119] Calculation: P_net = 100 kW - 0 kW = +100 kW (power needs to be drawn from the grid).

[0120] Instruction generation:

[0121] The operating mode command remains "grid-connected mode".

[0122] Trigger the "first control strategy step" (during off-peak hours).

[0123] The system presets a "valley filling target charging power value" P_charge_target = +150 kW (a positive value indicates charging by drawing power from the grid).

[0124] According to the formula: Power command = P_net + P_charge_target = +100 kW + (+150 kW) = +250 kW.

[0125] In addition to meeting the DC load demand of 100 kW, an extra 150 kW of electricity is drawn from the low-cost grid to charge the energy storage battery, thus achieving "valley filling".

[0126] Command execution: The controller receives the command (grid-connected mode, +250 kW) and draws 250 kW of power from the grid. Of this, 100 kW is supplied to the DC load, and the remaining 150 kW is used to charge the battery via the DC / DC converter of the energy storage unit through the DC bus.

[0127] In some embodiments, the method further includes a black boot process in off-network mode, the black boot process comprising:

[0128] Off-grid triggering steps: When a fault is detected in the AC power grid or when it is necessary to actively disconnect from the power grid, the operating mode command is set to off-grid mode;

[0129] Black start control steps: Generate a collaborative control command corresponding to the off-grid mode, wherein the power command is set to establish a preset AC voltage and frequency reference value, and send the command to the intelligent photovoltaic-storage DC-flexible controller;

[0130] System setup steps: The intelligent photovoltaic-storage DC-flexible controller obtains electrical energy from the energy storage unit according to the received instructions, establishes and maintains an AC voltage and frequency that conforms to the preset reference value at its AC side output terminal, thereby forming an independent off-grid AC bus to supply power to the loads connected to it, and allows the photovoltaic power generation unit to resume power generation on the DC bus.

[0131] The above embodiments specifically define the "black start" process of the system in off-grid mode. The scheme defines black start as a standardized and automated process consisting of "detection-command-establishment". When a grid fault is detected, the system does not passively shut down, but automatically triggers the black start process: First, the operating mode is switched to off-grid, and corresponding voltage / frequency establishment commands are generated; the controller then uses the electrical energy stored in the energy storage unit as a "start-up power source" to quickly establish a stable and reliable independent AC voltage source (i.e., off-grid microgrid) on its AC side. For example, in the instant of a sudden grid power outage, this system can establish a stable 380V / 50Hz AC bus through the energy storage battery and intelligent controller within a few hundred milliseconds, prioritizing the restoration of power to loads such as data centers, emergency lighting, and critical process equipment, and then allowing the photovoltaic system to resume power generation on the DC side to provide energy for the continuous operation of the system. This process requires no manual intervention, achieving a "seamless" switch from a large grid fault to stable island operation, significantly enhancing the park's ability to cope with power outages.

[0132] In some embodiments, during off-grid mode operation, the method further includes a virtual inertia support process, the virtual inertia support process comprising:

[0133] Frequency monitoring steps: Monitor the voltage frequency output from the AC side of the intelligent optical storage DC-flexible controller in real time;

[0134] Inertia determination steps: Calculate the rate of change of the voltage frequency. When the absolute value of the rate of change exceeds a preset threshold, it is determined that the system needs to provide virtual inertia support.

[0135] Power compensation step: Based on the rate of change of the voltage frequency, the active power compensation value is calculated according to the control algorithm of the rotor inertia of the simulated synchronous generator.

[0136] Instruction update steps: Based on the active power compensation value, update the power instruction in the collaborative control instruction, and send the updated collaborative control instruction to the intelligent photovoltaic-storage DC-flexible controller to control it to quickly adjust the active power obtained from the DC bus or output to the AC side load, thereby suppressing the fluctuation of the voltage frequency.

[0137] The above embodiments, based on off-grid operation, add the "virtual inertia support" function, which effectively solves the core technical problems of low inertia and poor anti-disturbance capability of microgrid systems with a high proportion of power electronic interfaces, and significantly improves the frequency stability and power quality of the system during off-grid operation.

[0138] In traditional microgrids, the lack of large-inertia rotating equipment like synchronous generators leads to drastic frequency changes during load surges, threatening stable operation. This solution simulates the rotor motion equations of a synchronous generator through a controller, enabling it to exhibit "virtual inertia." Specifically, when a rapid change in the off-grid system frequency is detected, the system can calculate the required active power compensation value in real time and dynamically update the power command to the controller. For example, when a high-power motor suddenly starts, causing a frequency drop, the controller instantly increases the active power extracted from the energy storage unit, like a giant flywheel releasing kinetic energy, quickly preventing the frequency drop. When a large load is suddenly disconnected, causing a frequency spike, the controller instantly reduces power output or absorbs excess power to suppress the frequency rise. This dynamic inertia support enables the "photovoltaic-storage-DC-flexible" microgrid to achieve frequency stability comparable to traditional power grids, accommodating a wider range of load fluctuations and intermittent power sources.

[0139] The following is an example of off-grid operation and disturbance rejection of a solar-storage-DC-flexible microgrid in a park, provided by an embodiment of the present invention.

[0140] Assume the initial system state and hardware configuration are as follows:

[0141] System status: The microgrid in the park is initially operating in grid-connected mode. The intelligent photovoltaic-storage-DC-flexible controller is exchanging power between the AC grid and the DC bus according to the instructions of the microgrid operation control system.

[0142] Status of critical equipment:

[0143] Energy storage unit: The lithium battery has a state of charge (SOC) of 80% and is in standby mode.

[0144] Photovoltaic power generation unit: Output is 0 kW due to nighttime.

[0145] DC load: Total power is approximately 200 kW (mainly for lighting and security).

[0146] Intelligent optical storage DC-flexible controller: The "virtual inertia support" algorithm module in its control unit is loaded and is in an activated state.

[0147] The specific implementation process is as follows:

[0148] (1) Offline Triggering and Black Boot Process

[0149] Step A: Offline Triggering Step

[0150] Event: At 8:00 PM, the external AC power grid experienced a sudden voltage drop and ultimately power outage due to a line fault. The protection module of the intelligent photovoltaic-storage DC-flexible controller monitored in real time that the AC side voltage remained below 80% of the normal value for more than two cycles.

[0151] Judgment and Command Generation: The controller immediately reports this fault information to the microgrid operation control system. Based on preset logic, the system determines that the system needs to disconnect from the main grid to ensure power supply to critical loads in the area, and immediately generates a new coordinated control command. The core of this command is:

[0152] Operating mode command: Switch from "grid-connected mode" to "off-grid mode".

[0153] Power command: Set to establish reference values ​​for preset AC voltage and frequency, for example, voltage reference value = 380V (phase voltage 220V), frequency reference value = 50.0 Hz.

[0154] Step B: Black Start Control Steps and System Setup Steps

[0155] Command Issuance and Execution: The microgrid operation control system issues the aforementioned coordinated control commands within hundreds of milliseconds. Upon receiving the commands, the control unit of the intelligent photovoltaic-storage-DC-flexible controller:

[0156] Mode switching: Immediately block the original grid-connected control strategy and switch to the off-grid voltage source control mode.

[0157] Establishing a voltage source: The controller uses its DC side as input to obtain electrical energy from the energy storage unit. Its internal bidirectional AC / DC conversion main circuit starts working, strictly tracking the new power command (i.e., voltage / frequency reference value), and quickly establishes a stable and independent 380V / 50Hz AC voltage at its AC side output.

[0158] Result: Within approximately 100-200 milliseconds, a stable "off-grid AC bus" was established by the system itself at the original grid connection point. The controller then restored power supply to the critical AC loads in the park connected to this bus.

[0159] Photovoltaic recovery: As the DC bus voltage is stabilized at ±375V by the controller and energy storage unit, the photovoltaic power generation unit detects that the DC bus voltage is normal, and its DC / DC converter starts automatically, beginning to generate electricity on the DC bus (although the output is 0 at night, the equipment is already in a ready state). At this point, the system has successfully completed a black start and entered a stable off-grid operation state.

[0160] (3) Virtual inertia support during off-grid operation

[0161] After the system has been running stably in off-network mode for about half an hour, an important test scenario occurs.

[0162] Step A: Frequency Monitoring and Inertia Judgment Steps

[0163] Major disturbance: A critical process motor with a power of 50kW (as a load) was suddenly switched on and started. This was a huge step load shock.

[0164] Frequency monitoring: The frequency monitoring module of the intelligent optical-storage DC-flexible controller samples the frequency of its AC side output voltage in real time. At the moment the motor is switched on, the frequency begins to drop rapidly due to the small total inertia of the system.

[0165] Calculation and Judgment: The controller's inertia judgment module calculates the rate of frequency change (df / dt) in real time. Assuming the frequency drops from 50.0Hz to 49.7Hz in 0.1 seconds, the rate of change is -3.0 Hz / s. This absolute value far exceeds the preset threshold (e.g., 0.5 Hz / s) within the module.

[0166] Step B: Power Compensation and Command Update Steps

[0167] Algorithm calculation: The controller's advanced function module (virtual inertia algorithm) is immediately triggered. This algorithm simulates the rotor motion equation of the synchronous generator ΔP = -K * (df / dt) (where K is the virtual inertia coefficient, for example, set to 500 kW / (Hz / s)).

[0168] Substituting the data: ΔP = -500 * (-3.0) = +1500 kW.

[0169] The algorithm calculates that, in order to suppress this sudden frequency drop, an instantaneous active power compensation of +1500 kW is required (the positive sign indicates that an increase in active power output to the system is needed).

[0170] Command Update: This "active power compensation value" (+1500 kW) is not a sustainable command, but an instantaneous adjustment. The algorithm translates this compensation value into an instantaneous adjustment to the current "power command".

[0171] In the current off-grid mode, the core of the power command is to maintain the voltage / frequency reference value. The virtual inertia algorithm superimposes a strong instantaneous power boost signal in the voltage / frequency control loop through the internal loop.

[0172] Implementation and Results:

[0173] Controller action: The control unit drives the bidirectional AC / DC converter main circuit to significantly increase the active power it draws from the DC bus in a very short time (within tens of milliseconds) in response to the superimposed compensation signal.

[0174] Energy storage response: The DC bus voltage shows a slight downward trend due to the controller instantly absorbing a large amount of power. The bidirectional DC / DC converter of the energy storage unit detects the drop in bus voltage and immediately increases the discharge power according to its own control law to support the DC bus voltage.

[0175] System stability: By rapidly increasing the active power output through the controller, the downward trend of the system frequency was quickly curbed. After the frequency dropped to 49.7Hz, it was quickly pulled back and stabilized at around 49.9Hz after several small oscillations. This avoided the serious consequences of load loss caused by triggering the low-frequency load shedding protection due to excessively low frequency.

[0176] In some embodiments, the instruction generation step further includes a power quality management sub-step, which includes:

[0177] Power quality information acquisition steps: Acquire power quality information from the AC grid side, wherein the power quality information includes at least reactive power data and harmonic current data;

[0178] The steps for generating the governance instruction are as follows: Based on the reactive power data, calculate the reactive power value to be compensated; and / or, based on the harmonic current data, calculate the compensation current instruction for offsetting a specific harmonic.

[0179] In the instruction execution step, the coordinated control instruction issued to the intelligent photovoltaic-storage DC-flexible controller also includes a power adjustment component determined based on the required reactive power compensation value and / or the compensation current instruction, so as to control the intelligent photovoltaic-storage DC-flexible controller to perform reactive power compensation and / or harmonic suppression on the AC grid side while performing the bidirectional power exchange.

[0180] The above embodiments integrate the "power quality management" function on the basis of collaborative control, so that the intelligent photovoltaic-storage DC-flexible controller can transform into an active power quality regulation device while completing basic energy management tasks. It is a multi-functional device that can not only ensure the power quality of the park itself, but also improve the power quality of the public power grid.

[0181] This solution transforms the needs for reactive power compensation and harmonic suppression into a "power regulation component" that can be superimposed on the main power command. During command generation, the system acquires reactive power and harmonic data from the grid side in real time and calculates the required compensation. For example, when it detects that equipment such as frequency converters and LED power supplies within the park are causing the power factor at the grid connection point to be too low, the system will instruct the controller to output corresponding capacitive or inductive reactive current to compensate the power factor to meet the requirements, avoiding fines from the power company. Simultaneously, if specific 5th or 7th harmonic currents exceed the standard, the controller can generate a compensation current with the opposite phase to actively cancel the harmonics, preventing harmonic pollution of the grid, transformer overheating, and relay protection malfunctions. This "open source and cost-saving" approach—managing its own energy flow while purifying the power quality flow interacting with the grid—not only improves the operating efficiency and lifespan of electrical equipment within the park but also makes it a highly grid-friendly "high-quality load," or even a "supporting power source."

[0182] This embodiment also provides an intelligent photovoltaic-storage-DC-flexible controller for implementing the above-described photovoltaic-storage-DC-flexible collaborative control method for a park microgrid, comprising a bidirectional AC / DC converter main circuit, a control unit, and a communication unit;

[0183] The AC side of the bidirectional AC / DC converter main circuit is used to connect to the AC power grid, and the DC side is used to connect to the DC bus.

[0184] The control unit is connected to the bidirectional AC / DC converter main circuit and is configured to execute the instruction execution steps of the above-described photovoltaic-storage-DC-flexible campus microgrid collaborative control method, and control the working state of the bidirectional AC / DC converter main circuit according to the received collaborative control instructions.

[0185] The communication unit is connected to the control unit and is configured to perform the data acquisition step of the above-described photovoltaic-storage-DC-flexible campus microgrid collaborative control method, in order to receive the collaborative control command from the microgrid operation control system and upload the controller's operating status data.

[0186] The above embodiments provide a smart photovoltaic-storage-DC-flexible controller hardware device for implementing the aforementioned collaborative control method. This device solidifies a series of advanced and complex control strategies into a standardized, plug-and-play physical product, significantly reducing the technical threshold and engineering complexity of integrating the "photovoltaic-storage-DC-flexible" system. Specifically, the controller highly integrates the bidirectional AC / DC converter main circuit, control unit, and communication unit. The control unit is specifically configured to execute the instruction execution steps of the aforementioned photovoltaic-storage-DC-flexible campus microgrid collaborative control method. It embeds a complete algorithm from basic power conversion to advanced functions (such as virtual inertia and power quality management). The communication unit is responsible for information interaction with the upper-level system. For example, during engineering implementation, there is no need to separately purchase and coordinate AC / DC converters, energy storage converters, power quality management devices, and complex central controllers. Only this defined "smart photovoltaic-storage-DC-flexible controller" needs to be deployed as the core hub. Through configuration and communication, it can quickly connect with photovoltaic, energy storage, and DC loads and execute a full set of advanced functions from peak shaving and valley filling to off-grid black start.

[0187] In some embodiments, the control unit is configured to perform the steps of the photovoltaic-storage-DC-flexible campus microgrid collaborative control method as described in any of the preceding embodiments, specifically including:

[0188] The mode switching module is configured to control the bidirectional AC / DC converter main circuit to automatically switch between grid-connected operation mode and off-grid operation mode according to the operation mode instruction in the coordinated control instruction, and to control the bidirectional AC / DC converter main circuit to work in constant voltage and constant frequency mode in the off-grid operation mode.

[0189] The power control module is configured to, in grid-connected operation mode, control the bidirectional AC / DC converter main circuit to realize a specified amount of bidirectional active power exchange between the DC bus and the AC grid according to the power command in the coordinated control command; and in off-grid operation mode, control the bidirectional AC / DC converter main circuit to establish and maintain a specified AC voltage and frequency at its AC side output terminal according to the power command.

[0190] The advanced functional module integrates a control algorithm for implementing virtual inertia support and damping control. The control algorithm is configured to dynamically calculate the active power compensation value based on the monitored AC voltage frequency changes in off-grid operation mode, and adjust the power command accordingly.

[0191] The protection and management module integrates overvoltage, undervoltage, overload, reverse current protection, islanding, and leakage protection logic, and also integrates reactive power compensation and harmonic suppression algorithms. The algorithms are configured to generate corresponding power regulation components based on the acquired power quality information, which are then superimposed on the execution logic of the power control module.

[0192] The above embodiments further specify the internal functional modules of the controller. This scheme divides the controller's "brain"—the control unit—into four major professional modules: mode switching, power control, advanced functions, and protection and governance. Each module performs its own function while working closely together: the mode switching module is responsible for top-level state machine management; the power control module is the core actuator, accurately tracking active / reactive power commands; advanced function modules (such as the virtual inertia algorithm) dynamically intervene when needed to adjust power commands; and the protection and governance module always runs in the background to ensure safety and purify power quality. For example, when the system needs to switch from grid-connected to off-grid, the mode switching module issues a command, and the power control module immediately switches the control strategy from power tracking mode to voltage source mode; at the same time, the virtual inertia algorithm in the advanced function module is activated, ready to deal with frequency disturbances under off-grid conditions; and the protection and governance module monitors the entire process to ensure that there is no overcurrent or overvoltage during the switching process.

[0193] In some embodiments, the bidirectional AC / DC converter main circuit adopts a modular power unit parallel design;

[0194] The controller also includes a thermal management unit, which includes a temperature sensor and an intelligent air-cooled heat sink;

[0195] The control unit is also configured to: dynamically adjust the fan speed of the intelligent air-cooled heat sink according to the temperature of the modular power unit detected by the temperature sensor, and maintain the rated power output of the bidirectional AC / DC converter main circuit without derating when the detected temperature reaches 45°C.

[0196] The above embodiments optimize and limit the hardware architecture and thermal management of the controller. This solution includes two key hardware improvements: a modular power unit parallel design and an intelligent temperature-controlled air-cooling system. The modular parallel design allows the power capacity to be flexibly expanded like an "expanded hard drive," and the failure of a single unit will not cause the entire system to crash, improving the system's scalability and availability. Intelligent thermal management directly addresses the core pain point of power electronic equipment—heat dissipation. For example, in hot summer weather, the internal temperature of the controller rises sharply when running at full load. Traditional cooling solutions may begin to derating at 40°C, leading to a decrease in output power and affecting system performance. However, the control unit of this solution can dynamically adjust the fan speed based on temperature sensor data to achieve precise heat dissipation. Its core advantage is that even when the heatsink temperature reaches the critical threshold of 45°C, the controller can still maintain rated power output without derating through optimized airflow and intelligent speed regulation.

[0197] This invention also provides a campus photovoltaic-storage-DC-flexible microgrid system, comprising:

[0198] AC power grid branch lines are used to supply power to the AC loads in the park;

[0199] DC bus;

[0200] The photovoltaic power generation unit is connected to the DC bus via a first DC / DC converter;

[0201] The energy storage unit is connected to the DC bus via a second bidirectional DC / DC converter;

[0202] At least one DC load is connected to the DC bus, either directly or via a third DC / DC converter;

[0203] The intelligent photovoltaic-storage DC-flexible controller as described in any one of the above-mentioned embodiments has its DC side connected to the DC bus and its AC side connected to the AC grid branch.

[0204] The microgrid operation control system is communicatively connected to the communication unit of the intelligent photovoltaic-storage-DC-flexible controller, the photovoltaic power generation unit, the energy storage unit, and the DC load, and is configured to execute the campus microgrid collaborative control method based on photovoltaic-storage-DC-flexible as described in any one of the above.

[0205] The above embodiments provide a complete "Park-based Photovoltaic-Storage DC-Flexible Microgrid System" solution. This solution is not simply a list of equipment, but rather defines a standard system architecture with a DC bus as the energy integration platform, an intelligent photovoltaic-storage DC-flexible controller as the control and conversion core, and a microgrid operation control system as the decision-making brain. All power generation units (photovoltaics), energy storage units, and DC loads are connected to the DC bus through standardized DC / DC converters, forming a natural "plug-and-play" interface. For example, when a park is being built, the DC bus, controller, and brain system can be deployed first. Subsequently, whether adding photovoltaic installations, expanding energy storage power stations, or connecting new DC charging piles or DC air conditioners, it is only necessary to "connect" them to the DC bus through the corresponding DC / DC converters and configure them in the upper-level system. There is no need to change the main electrical structure, which greatly facilitates the phased construction and flexible expansion of the system.

[0206] refer to Figure 3 As shown, this is an embodiment of the present invention providing an overall topology architecture for a collaborative control system of a solar-storage-DC-flexible microgrid in a park. The microgrid system adopts a DC bus architecture, specifically including:

[0207] Source side: The photovoltaic power generation unit is connected to the 750V DC bus via a DC / DC converter; the energy storage unit is also connected to the same bus.

[0208] Load side: Includes high-power, medium-power, and low-power DC equipment, which are powered efficiently through corresponding DC / DC converters or directly connected to the DC bus.

[0209] Grid connection interface: Enables bidirectional energy exchange between the DC bus and the 380V AC grid through an AC / DC converter, supporting both grid-connected and off-grid operation.

[0210] The system is equipped with a microgrid operation control system and an intelligent photovoltaic-storage DC-flexible controller to achieve coordinated control of power generation, storage, and load.

[0211] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A collaborative control method for a campus microgrid based on photovoltaic, energy storage, direct current, and flexible energy transmission, characterized in that: The method is executed by a microgrid operation control system, which is communicatively connected to an intelligent photovoltaic-storage DC-flexible controller, a photovoltaic power generation unit, an energy storage unit, and at least one DC load. The intelligent photovoltaic-storage DC-flexible controller is connected between the AC grid and the DC bus, and the photovoltaic power generation unit, the energy storage unit, and the at least one DC load are all connected to the DC bus. The method includes the following steps: Data acquisition steps: Real-time acquisition of the predicted power generation of the photovoltaic power generation unit, the predicted power demand of the DC load, and the operating status information of the AC power grid; Instruction generation step: Based on the information obtained in the data acquisition step, generate a collaborative control instruction for the coordinated energy management of the photovoltaic power generation unit, energy storage unit, DC load and AC grid. The collaborative control instruction is used to instruct the intelligent photovoltaic-storage DC-flexible controller to perform bidirectional power exchange between the DC bus and the AC grid. Command execution steps: The coordinated control command is sent to the intelligent photovoltaic-storage DC-flexible controller to control it to perform the corresponding power conversion operation, thereby realizing the coordinated control of the source, grid, load and storage in the park microgrid.

2. The method according to claim 1, characterized in that, The coordinated control commands include operating mode commands and power commands; the operating mode commands are used to set the intelligent photovoltaic-storage-DC-flexible controller to operate in grid-connected mode or off-grid mode; the power commands are associated with the operating mode commands, wherein: When the operating mode command is set to grid-connected mode, the power command is the active power target value exchanged between the DC bus and the AC grid; When the operating mode command is set to off-grid mode, the power command is the voltage reference value and frequency reference value output by the AC side of the intelligent photovoltaic-storage DC-flexible controller.

3. The method according to claim 2, characterized in that, When the operating mode instruction is set to grid-connected mode, the instruction generation step specifically includes: Calculation steps: Based on the predicted power generation and the predicted power demand, calculate the net exchange power required on the DC bus side, where a positive value indicates that power needs to be absorbed from the outside and a negative value indicates that power can be output to the outside; First control strategy step: In response to the AC grid being in a low-consumption period, the coordinated control command is generated, wherein the power command is set to add a positive charging power value to the net exchange power to control the intelligent photovoltaic-storage DC-flexible controller to charge the energy storage unit, thereby achieving valley filling; The second control strategy step is as follows: In response to the AC grid being in a peak electricity consumption period, the coordinated control command is generated, wherein the power command is set to the larger of the net exchange power and a negative discharge power value, so as to control the intelligent photovoltaic-storage DC-flexible controller to prioritize the use of surplus power on the DC side, and call the energy storage unit to deliver power to the AC grid when necessary, so as to achieve peak shaving.

4. The method according to claim 2, characterized in that, The method also includes a black boot process in off-network mode, the black boot process comprising: Off-grid triggering steps: When a fault is detected in the AC power grid or when it is necessary to actively disconnect from the power grid, the operating mode command is set to off-grid mode; Black start control steps: Generate a collaborative control command corresponding to the off-grid mode, wherein the power command is set to establish a preset AC voltage and frequency reference value, and send the command to the intelligent photovoltaic-storage DC-flexible controller; System setup steps: The intelligent photovoltaic-storage DC-flexible controller obtains electrical energy from the energy storage unit according to the received instructions, establishes and maintains an AC voltage and frequency that conforms to the preset reference value at its AC side output terminal, thereby forming an independent off-grid AC bus to supply power to the loads connected to it, and allows the photovoltaic power generation unit to resume power generation on the DC bus.

5. The method according to claim 4, characterized in that, During off-grid operation, the method further includes a virtual inertia support process, which includes: Frequency monitoring steps: Monitor the voltage frequency output from the AC side of the intelligent optical storage DC-flexible controller in real time; Inertia determination steps: Calculate the rate of change of the voltage frequency. When the absolute value of the rate of change exceeds a preset threshold, it is determined that the system needs to provide virtual inertia support. Power compensation step: Based on the rate of change of the voltage frequency, the active power compensation value is calculated according to the control algorithm of the rotor inertia of the simulated synchronous generator. Instruction update steps: Based on the active power compensation value, update the power instruction in the collaborative control instruction, and send the updated collaborative control instruction to the intelligent photovoltaic-storage DC-flexible controller to control it to quickly adjust the active power obtained from the DC bus or output to the AC side load, thereby suppressing the fluctuation of the voltage frequency.

6. The method according to claim 1, characterized in that, The instruction generation step further includes a power quality management sub-step, which includes: Power quality information acquisition steps: Acquire power quality information from the AC grid side, wherein the power quality information includes at least reactive power data and harmonic current data; The steps for generating the governance instruction are as follows: Based on the reactive power data, calculate the reactive power value to be compensated; and / or, based on the harmonic current data, calculate the compensation current instruction for offsetting a specific harmonic. In the instruction execution step, the coordinated control instruction issued to the intelligent photovoltaic-storage DC-flexible controller also includes a power adjustment component determined based on the required reactive power compensation value and / or the compensation current instruction, so as to control the intelligent photovoltaic-storage DC-flexible controller to perform reactive power compensation and / or harmonic suppression on the AC grid side while performing the bidirectional power exchange.

7. An intelligent optical storage DC-flexible controller for implementing the method of any one of claims 1-6, characterized in that, Includes a bidirectional AC / DC converter main circuit, a control unit, and a communication unit; The AC side of the bidirectional AC / DC converter main circuit is used to connect to the AC power grid, and the DC side is used to connect to the DC bus. The control unit is connected to the bidirectional AC / DC converter main circuit and is configured to execute the instruction execution steps of the method according to any one of claims 1-6, and control the working state of the bidirectional AC / DC converter main circuit according to the received cooperative control instructions. The communication unit is connected to the control unit and is configured to perform the data acquisition step of the method according to any one of claims 1-6, so as to receive the cooperative control command from the microgrid operation control system and upload the operating status data of the controller.

8. The controller according to claim 7, characterized in that, The control unit is configured to perform the method steps as described in any one of claims 1-6, specifically including: The mode switching module is configured to control the bidirectional AC / DC converter main circuit to automatically switch between grid-connected operation mode and off-grid operation mode according to the operation mode instruction in the coordinated control instruction, and to control the bidirectional AC / DC converter main circuit to work in constant voltage and constant frequency mode in the off-grid operation mode. The power control module is configured to, in grid-connected operation mode, control the bidirectional AC / DC converter main circuit to realize a specified amount of bidirectional active power exchange between the DC bus and the AC grid according to the power command in the coordinated control command; and in off-grid operation mode, control the bidirectional AC / DC converter main circuit to establish and maintain a specified AC voltage and frequency at its AC side output terminal according to the power command. The advanced functional module integrates a control algorithm for implementing virtual inertia support and damping control. The control algorithm is configured to dynamically calculate the active power compensation value based on the monitored AC voltage frequency changes in off-grid operation mode, and adjust the power command accordingly. The protection and management module integrates overvoltage, undervoltage, overload, reverse current protection, islanding, and leakage protection logic, and also integrates reactive power compensation and harmonic suppression algorithms. The algorithms are configured to generate corresponding power regulation components based on the acquired power quality information, which are then superimposed on the execution logic of the power control module.

9. The controller according to claim 7, characterized in that, The bidirectional AC / DC converter main circuit adopts a modular power unit parallel design; The controller also includes a thermal management unit, which includes a temperature sensor and an intelligent air-cooled heat sink; The control unit is also configured to: dynamically adjust the fan speed of the intelligent air-cooled heat sink according to the temperature of the modular power unit detected by the temperature sensor, and maintain the rated power output of the bidirectional AC / DC converter main circuit without derating when the detected temperature reaches 45°C.

10. A solar-storage-DC-flexible microgrid system for industrial parks, characterized in that: include: AC power grid branch lines are used to supply power to the AC loads in the park; DC bus; The photovoltaic power generation unit is connected to the DC bus via a first DC / DC converter; The energy storage unit is connected to the DC bus via a second bidirectional DC / DC converter; At least one DC load is connected to the DC bus, either directly or via a third DC / DC converter; The intelligent photovoltaic-storage DC-flexible controller as described in any one of claims 7-9 has its DC side connected to the DC bus and its AC side connected to the AC grid branch. The microgrid operation control system is communicatively connected to the communication unit of the intelligent photovoltaic-storage-DC-flexible controller, the photovoltaic power generation unit, the energy storage unit, and the DC load, and is configured to execute the campus microgrid collaborative control method based on photovoltaic-storage-DC-flexible as described in any one of claims 1-6.

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