Distributed control method and system for hybrid energy storage networking converter

Abstract

The invention relates to the field of electrical engineering, is used for solving the problems that high-frequency and low-frequency power components are difficult to effectively distinguish, power sharing is not uniform, and the service life loss of a battery is aggravated, and particularly relates to a distributed control method and system for a hybrid energy storage network-building converter. According to the method, energy type energy storage and power type energy storage of an alternating current power grid are accessed through a network construction type converter, transient virtual impedance control is added on the basis of VSG control, so that response of the energy type energy storage to transient power is restrained, high and low frequency power dynamic decoupling needed by HESS is achieved, and then according to a distributed control strategy based on the multi-agent consistency theory, a multi-agent distributed control strategy based on the multi-agent consistency theory is obtained. Therefore, each network-forming converter only needs to carry out sparse communication with adjacent nodes to cooperatively realize indifference adjustment of system frequency and accurate distribution of steady-state power according to needs, and an event triggering mechanism is combined to reduce communication burden and adjust power reference values of each unit.

Description

Technical Field

[0001] This invention relates to the field of electrical engineering, specifically to a distributed control method and system for hybrid energy storage grid-connected converters. Background Technology

[0002] With the increasing penetration rate of renewable energy, the demand for energy storage systems in the power system is growing. Based on their characteristics, energy storage systems can be divided into energy storage and power storage. Energy storage is represented by lithium batteries with large capacity and slow response, while power storage is represented by supercapacitors with small capacity and fast response. Hybrid energy storage systems are coordinated control systems that simultaneously deploy power storage and energy storage. When power fluctuates, power storage takes the lead in handling rapid transient impacts, while energy storage provides stable long-term support, thereby effectively achieving power smoothing and significantly delaying the lifespan degradation of energy storage caused by high-frequency stress.

[0003] However, most traditional hybrid energy storage solutions rely on a common DC bus architecture, where different types of energy storage units are connected to a centralized DC bus through their respective DC-DC converters. Power is distributed between the two by controlling the DC-DC converters. However, this centralized DC bus architecture severely limits the application of HESS in AC microgrids, requiring the two types of energy storage to be physically deployed in a centralized manner, making it difficult to achieve flexible coordination of distributed energy storage on a larger spatial scale.

[0004] To address the distributed application challenges of HESS in AC microgrids, grid-mounted converter (GFM) control technology has garnered significant attention. Among these technologies, Virtual Synchronous Generator (VSG) control, which simulates the inertia and damping characteristics of a synchronous generator, is widely used in grid-mounted converters, enabling them to perform frequency / voltage regulation and power distribution. However, conventional VSG control is difficult to apply directly to HESS. When the load fluctuates, the energy storage converter controlled by VSG will inevitably respond instantaneously to the load, which conflicts with the core objective of power storage to respond to transients. This makes it difficult for grid-mounted converters to effectively distinguish between high- and low-frequency power components, resulting in uneven power distribution and accelerated battery life loss.

[0005] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0006] This invention relates to energy storage and power storage connected to the AC grid via a grid-connected converter. Based on VSG control, transient virtual impedance control is added to suppress the response of energy storage to transient power, achieving dynamic decoupling of high and low frequency power required by HESS (Hybrid Energy Storage System). Then, according to a distributed control strategy based on multi-agent consensus theory, combined with an event-triggered mechanism to reduce communication burden, the power reference values ​​of each unit are adjusted to address the problem that grid-connected converters struggle to effectively distinguish between high and low frequency power components, resulting in uneven power distribution and accelerated battery life loss. Therefore, a distributed control method and system for hybrid energy storage grid-connected converters are proposed.

[0007] The objective of this invention can be achieved through the following technical solution: a distributed control method for hybrid energy storage grid-connected converters, comprising the following steps: Step 1: Construct an AC microgrid, establish a sparse communication network and a distributed control system for different grid-type converters in the AC microgrid, and at the same time, establish a multi-agent system based on the AC microgrid system that includes grid-type converters; Step 2: Collect the three-phase output voltage and output current of each converter, and calculate its frequency and power; Step 3: In the sparse communication network, determine the adjacent network converters and acquire information about the adjacent network converters; Step 4: Construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control. Use the control strategy to decouple high and low frequency power for each grid-type converter to obtain the control target to be executed, and apply transient virtual impedance to the energy storage unit. Step 5: Construct a distributed control strategy that adds consensus algorithm and event-triggered control. Each grid-type converter corrects the power reference value based on the consensus algorithm and uses the event-triggered mechanism to reduce the communication burden, and determines the control objective of achieving frequency error-free and steady-state power precise allocation. Step Six: Based on the voltage and frequency obtained by VSG control combined with transient virtual impedance control, distributed control and event-triggered control, the three-phase AC voltage waveform is obtained by dq transformation, and then further modulated into a three-phase PWM switching control signal, which is applied to the grid-type converter to achieve the control effect.

[0008] The present invention also proposes a distributed control system for hybrid energy storage grid-type converters, including a converter grouping module, a self-parameter acquisition module, a communication management module, a high- and low-frequency power decoupling module, a distributed control module, and a comprehensive modulation control module. The converter grouping construction module is used to obtain the type of the grid-type converter, encode and record it based on the type of the grid-type converter, and then build a sparse communication network between different grid-type converters. The self-parameter acquisition module acquires the operating parameters of each converter and sends the operating parameters to the high and low frequency power decoupling module. The communication management module obtains the construction information of the network converter through the converter grouping construction module, and enables adjacent network converters and intelligent agents to communicate. The high- and low-frequency power decoupling module can construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control, and decouple the acquired converter operating parameters for high and low frequency power to obtain the control target and control the corresponding energy storage unit. The distributed control module constructs a distributed control strategy that adds a consensus algorithm and event-triggered control, and analyzes the converter operating parameters again to determine the control objectives of frequency zero error and steady-state power precise allocation. The integrated modulation control module obtains control results through the high- and low-frequency power decoupling module and the distributed control module, and analyzes the modulation switch control signal based on changes.

[0009] In a preferred embodiment of the present invention, the grid-type converters obtained by the converter grouping construction module are a first type of grid-type converter and a second type of grid-type converter. The first type of grid-type converter is a grid-type converter connected to energy storage, and the second type of grid-type converter is a grid-type converter connected to power storage. Both energy storage and power storage are energy storage units in AC microgrids.

[0010] In a preferred embodiment of the present invention, the self-parameter acquisition module acquires the converter's own operating parameters, including three-phase output voltage and output current, self-frequency and power. The three-phase output voltage and output current are directly acquired by sensors, while the self-frequency and power are calculated from the voltage and current.

[0011] In a preferred embodiment of the present invention, each grid-type converter is treated as a node in the sparse communication network constructed by the converter group. If there is a communication connection between two nodes, they are said to be adjacent or neighboring nodes.

[0012] In a preferred embodiment of the present invention, the grid-type converter control strategy constructed by the high- and low-frequency power decoupling module is divided into two parts: VSG control and transient virtual impedance control. Both VSG control and transient virtual impedance control are controlled by unique control equations. The VSG control equation is as follows: ; In the formula, f is the VSG frequency, f0 is the rated frequency, J is the moment of inertia, D is the damping coefficient, and P... m P is the active power reference value. eP is the active power output by the GFM. ref For a given active power, k p The active droop factor is t, where t is time, E and E0 are the output voltage amplitude and rated voltage amplitude of the VSG, respectively, and k is the active droop factor. q Q is the reactive power droop factor. e For GFM, output reactive power; Q ref Given reactive power; The control equation for transient virtual impedance control is: ; In the formula, E d and E q These are the voltage command values ​​on the d and q axes, respectively, i d and i q The output currents on the d and q axes are respectively, r v For virtual resistance, L v For virtual reactance, and u d * with u q * This indicates the output of virtual impedance control; The high- and low-frequency power decoupling module calculates based on the converter's own operating parameters, and uses the converter corresponding to the energy storage unit to apply a transient virtual impedance to the energy storage unit to suppress its transient response, thereby obtaining the voltage command value and frequency command value required to realize hybrid energy storage.

[0013] In a preferred embodiment of the present invention, the distributed control module, when constructing the distributed control strategy, obtains the corrected second-order VSG control equations by adding a consensus algorithm to the VSG control equations, specifically as follows: ; In the formula, P refi Given the active power of the i-th GFM, G refi Let α be the consistency variable for the i-th GFM. ij k represents the communication weights among multiple agents. e This is the deviation correction factor; The distributed control module then adds event-triggered control to the VSG control equations, resulting in a second-order VSG control equation with low communication overhead: ; In the formula, ε is the event triggering condition parameter; The distributed control module analyzes and controls the converter based on its own parameters to obtain control results, which are voltage and frequency.

[0014] In a preferred embodiment of the present invention, after the integrated modulation control module obtains the control result, it obtains the three-phase AC voltage waveform through dq transformation, and further modulates it into a three-phase PWM switching control signal, which is then applied to the grid-type converter to achieve the control effect.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention deeply integrates and designs a closed-loop system of VSG control, transient virtual impedance, distributed consensus algorithm, and event triggering mechanism to form a complete hierarchical control solution. It breaks through the limitation of traditional hybrid energy storage relying on centralized DC bus, and can be directly applied to distributed energy storage power sources connected to the AC grid through grid-type converters without the need to add or modify power equipment.

[0016] This invention constructs a composite control strategy combining VSG control and transient virtual impedance control, achieving natural decoupling between energy-type and power-type energy storage in a hybrid energy storage system. During load surges, the transient virtual impedance automatically suppresses the instantaneous power response of energy-type energy storage, allowing it to focus on steady-state power support. Simultaneously, it guides power-type energy storage to quickly smooth high-frequency fluctuations, enabling power-type energy storage to handle high-frequency transient power while energy-type energy storage handles low-frequency steady-state power. This achieves high- and low-frequency power decoupling, leveraging the advantages of each and extending energy storage lifespan, significantly improving the dynamic performance and operational stability of AC microgrids.

[0017] This invention also employs a distributed control framework based on a consensus algorithm, combined with an event-triggered communication mechanism. This allows each grid-type converter to collaboratively achieve error-free frequency regulation and precise on-demand allocation of steady-state power by communicating sparsely with adjacent nodes. This enables geographically dispersed energy storage power sources to collaboratively achieve hybrid energy storage and achieve error-free frequency and precise steady-state power allocation. At the same time, the event-triggered mechanism effectively reduces the communication burden of the system and improves flexibility. Attached Figure Description

[0018] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0019] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a system block diagram of the present invention; Figure 3 This is a circuit logic diagram of the present invention; Figure 4 This is a schematic diagram of the control process of the present invention. Detailed Implementation

[0020] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1: Please refer to Figure 1 - Figure 4 As shown, the distributed control method for hybrid energy storage grid-connected converters includes the following steps: Step 1: Construct an AC microgrid that includes both energy storage and power storage. The energy storage devices are connected to the grid through their respective grid-connected converters. The basic components of the AC microgrid system are grid-connected converters, filter circuits, line impedance, and loads. Establish a sparse communication network and a distributed control system for the different grid-connected converters in the AC microgrid. The converters are divided into grid-connected converters that connect to energy storage and grid-connected converters that connect to power storage. Step 2: Collect the three-phase output voltage and output current of each converter, calculate its frequency and power, and communicate with neighboring agents in the sparse communication network to obtain information. This information will be used for the proposed distributed control strategy for grid-type converters. Step 3: In the sparse communication network, determine the adjacent network converters and acquire information about the adjacent network converters; Step 4: Construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control. Use the control strategy to decouple high and low frequency power for each grid-type converter to obtain the control target to be executed, and apply transient virtual impedance to the energy storage unit. Step 5: Construct a distributed control strategy that adds consensus algorithm and event-triggered control. Each grid-type converter corrects the power reference value based on the consensus algorithm and uses the event-triggered mechanism to reduce the communication burden, and determines the control objective of achieving frequency error-free and steady-state power precise allocation. Step Six: Based on the voltage and frequency obtained by VSG control combined with transient virtual impedance control, distributed control and event-triggered control, the three-phase AC voltage waveform is obtained by dq transformation, and then further modulated into a three-phase PWM switching control signal, which is applied to the grid-type converter to achieve the control effect.

[0022] Example 2: Please refer to Figure 1 - Figure 4 As shown, the distributed control system for hybrid energy storage grid-type converters includes a converter grouping module, a self-parameter acquisition module, a communication management module, a high- and low-frequency power decoupling module, a distributed control module, and a comprehensive modulation control module. The converter grouping construction module is used to obtain the type of grid-connected converter, which is a first type of grid-connected converter and a second type of grid-connected converter. The first type of grid-connected converter is a grid-connected converter connected to energy storage, and the second type of grid-connected converter is a grid-connected converter connected to power storage. Both energy storage and power storage are energy storage units in AC microgrids. The module encodes and records the grid-connected converters based on their types, and then constructs a sparse communication network between different grid-connected converters. The self-parameter acquisition module acquires the operating parameters of each converter, including the three-phase output voltage and output current, its own frequency and power, and sends the operating parameters to the high and low frequency power decoupling module. The three-phase output voltage and output current are directly acquired by the sensors, while the own frequency and power are calculated by voltage and current. The communication management module obtains the construction information of the network converter through the converter grouping construction module, and treats each network converter as a node. If there is a communication connection between two nodes, they are called adjacent or neighbor nodes, and the adjacent network converters and the agent communicate with each other. The high- and low-frequency power decoupling module can construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control. It decouples the acquired converter operating parameters for high- and low-frequency power, specifically through two parts: VSG control and transient virtual impedance control. VSG control is implemented using control equations, the derivation of which is as follows: A GFM using VSG control can provide inertial support for the microgrid. Therefore, by introducing rotor motion equations, VSG control endows distributed power sources with inertial and damping characteristics, similar to the control process of a traditional synchronous generator. Figure 4 The primary frequency regulation and primary voltage regulation control equations of the VSG, as well as the rotor motion equations in the virtual synchronous engine, are as follows: ; In the formula, f is the VSG frequency, f0 is the rated frequency, J is the moment of inertia, D is the damping coefficient, and P... m P is the active power reference value. e P is the active power output by the GFM. ref For a given active power, k p The active droop factor is t, where t is time, E and E0 are the output voltage amplitude and rated voltage amplitude of the VSG, respectively, and k is the active droop factor. q Q is the reactive power droop factor. e For GFM, output reactive power; Q ref Given reactive power; For a microgrid system composed of multiple grid-connected converters with droop characteristics, the active power of the converters is directly related to the phase difference. For high-voltage systems, the line impedance is considered to be mainly inductive. In this case, the active power output of the microgrid can be approximated as: ; In the formula, E is the effective value of the power supply output voltage, U is the effective value of the AC bus voltage, X is the impedance between the power supply and the bus, and δ is the phase of the power supply voltage relative to the AC bus voltage. By introducing virtual impedance into the control algorithm, the converter can simulate the external characteristics of the actual source impedance, thereby enhancing system stability, reducing power fluctuations, and optimizing power distribution among different energy storage components. The specific form of virtual impedance is as follows: ; In the formula, E d and E q These are the voltage command values ​​on the d and q axes, respectively, i d and i q The output currents on the d and q axes are respectively, r v For virtual resistance, L v For virtual reactance, and u d * with u q * This represents the output of virtual impedance control, where ω is the angular frequency; In GFM, the dynamic distribution of active power is mainly dominated by line impedance, especially the inductive reactance between the power source and the AC bus. The higher the output impedance, the smaller the power fluctuation under load disturbances. Therefore, virtual impedance can be introduced at the control level to reshape the equivalent output impedance, thereby adjusting power distribution and achieving the synergistic goal of HESS. Since active power distribution is mainly affected by inductive reactance rather than resistance, directly configuring virtual resistors will cause unnecessary voltage drops. Therefore, only virtual inductance is introduced on the battery side. However, while relying solely on a large virtual inductance can change the dynamic distribution, it may lead to increased steady-state voltage drop and lag in dynamic response due to the battery bearing more power in steady state.

[0023] To balance dynamic and steady-state performance, using transient virtual impedance is more feasible. TVI only operates during current changes and decays rapidly over time after high-pass filtering. This temporarily increases the equivalent inductive reactance on the battery side during load surges, suppressing its contribution to high-frequency / transient power. When the load is stable, it intervenes almost entirely, thus not affecting the steady-state power supplied by the battery. Therefore, the control equation for transient virtual impedance control is: ; In the formula, E d and E q These are the voltage command values ​​on the d and q axes, respectively, id and i q The output currents on the d and q axes are respectively, r v For virtual resistance, L v For virtual reactance, and u d * with u q * This represents the output of the virtual impedance control, where Ts is the time constant of the high-pass filter. The high and low frequency power decoupling module calculates based on the converter's own operating parameters, and uses the converter corresponding to the energy storage unit to apply transient virtual impedance to the energy storage unit to suppress its transient response, thereby obtaining the voltage command value and frequency command value required to realize hybrid energy storage. The distributed control module constructs a distributed control strategy that incorporates a consensus algorithm and event-triggered control. By adding the consensus algorithm to the VSG control equations, the corrected second-order VSG control equations are obtained, as follows: ; In the formula, P refi Given the active power of the i-th GFM, G refi Let α be the consistency variable for the i-th GFM. ij k represents the communication weights among multiple agents. e This is the deviation correction factor; It should be noted that for a multi-agent system with n nodes, if there exists a communication link ij connecting GFCi and GFCj, then GFCj is considered to be in the neighborhood set Ni, indicating j∈Ni. In the multi-agent system, a single GFCi can only receive information from the neighborhood set Ni. Furthermore, considering the differences between agents in the communication topology, the impact of information from each neighbor on the local control strategy is usually adjusted based on a communication weight matrix. A common form of the communication weight matrix is ​​as follows: ; In the formula, α ij n represents the communication weights among multiple agents. i Let α be the number of individuals in the neighborhood of GFCi, and let α be the set of positive numbers for system stability. Based on the communication weight matrix, the following multi-agent control method can be formed: ; In the formula, G ref For consistency variables; This control strategy allows G ref Information is transmitted and corrected among individual agents, ultimately ensuring that each agent in a multi-agent system receives globally consistent information G. refmg Using global information G refmg For Pref Adjustments are made to achieve the control objectives of frequency restoration and power distribution. To this end, the following controls are established: ; Secondly, during the control process, based on the actual output power P and the VSG rated power P ref Difference adjustment G ref The value of G is implemented. ref With P ref Matching: ; In the formula, k e This is the deviation correction factor; Through these two measures, P refmg The corresponding adjusted G refmg With the total power P of the microgrid mg match: ; Combined with the active-frequency equation, that is: ; In other words, the global frequency of the microgrid is unbiased; therefore, the following conclusion can be drawn: ; In other words, while keeping the frequency at its rated value, the power of any converter is equal to its power reference value, which is subject to the uniform value G. refmg And the influence of setting parameters, and can be precisely controlled, that is, P refi Set to G refi This is to ensure that the power of each GFM is evenly distributed under this strategy, and finally obtain the VSG active frequency control equation after adding the consensus algorithm, where bi refers to the i-th energy storage unit. To reduce communication load, the system introduces an event-triggered mechanism. This mechanism, based on preset trigger conditions, transforms continuous real-time information updates into intermittent updates that only occur when the conditions are met. The event trigger conditions are as follows: ; In the formula, ε is the event triggering condition parameter, and the triggering condition is determined every 0.1 seconds; when converter i meets the condition, it will publish its immediate G. refi Information is provided to neighbors to update their local data; otherwise, each neighbor node retains and uses a copy of the last received data. The distributed control module then adds event-triggered control to the VSG control equations, resulting in a second-order VSG control equation with low communication overhead: ; This allows us to determine the control objectives of zero frequency error and precise steady-state power allocation; The integrated modulation and control module obtains the control results through the high- and low-frequency power decoupling module and the distributed control module. It obtains the three-phase AC voltage waveform through dq transformation, and further modulates it into a three-phase PWM switching control signal, which is then applied to the grid-type converter to achieve the control effect.

[0024] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A distributed control method for hybrid energy storage grid-connected converters, characterized in that, Includes the following steps: Step 1: Construct an AC microgrid, establish a sparse communication network and a distributed control system for different grid-type converters in the AC microgrid, and at the same time, establish a multi-agent system based on the AC microgrid system that includes grid-type converters; Step 2: Collect the three-phase output voltage and output current of each converter, and calculate its frequency and power; Step 3: In the sparse communication network, identify neighboring agents and acquire information from them; Step 4: Construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control. Use the control strategy to decouple high and low frequency power for each grid-type converter to obtain the control target to be executed, and apply transient virtual impedance to the energy storage unit. Step 5: Construct a distributed control strategy that adds consensus algorithm and event-triggered control. Each grid-type converter corrects the power reference value based on the consensus algorithm and uses the event-triggered mechanism to reduce the communication burden, and determines the control objective of achieving frequency error-free and steady-state power precise allocation. Step Six: Based on the voltage and frequency obtained by VSG control combined with transient virtual impedance control, distributed control and event-triggered control, the three-phase AC voltage waveform is obtained by dq transformation, and then further modulated into a three-phase PWM switching control signal, which is applied to the grid-type converter to achieve the control effect.

2. A distributed control system for hybrid energy storage grid-connected converters, applied to the distributed control method for hybrid energy storage grid-connected converters as described in claim 1, characterized in that, It includes a converter grouping construction module, a self-parameter acquisition module, a communication management module, a high- and low-frequency power decoupling module, a distributed control module, and a comprehensive modulation control module; The converter grouping construction module is used to obtain the type of the grid-type converter, encode and record it based on the type of the grid-type converter, and then build a sparse communication network between different grid-type converters. The self-parameter acquisition module acquires the operating parameters of each converter and sends the operating parameters to the high and low frequency power decoupling module. The communication management module obtains the construction information of the network converter through the converter grouping construction module, and enables adjacent network converters and intelligent agents to communicate. The high- and low-frequency power decoupling module can construct a grid-type converter control strategy that combines VSG control and transient virtual impedance control, and decouple the acquired converter operating parameters for high and low frequency power to obtain the control target and control the corresponding energy storage unit. The distributed control module constructs a distributed control strategy that adds a consensus algorithm and event-triggered control, and analyzes the converter operating parameters again to determine the control objectives of frequency zero error and steady-state power precise allocation. The integrated modulation control module obtains control results through the high- and low-frequency power decoupling module and the distributed control module, and analyzes the modulation switch control signal based on changes.

3. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, The grid-type converters obtained by the converter grouping construction module are the first type of grid-type converter and the second type of grid-type converter. The first type of grid-type converter is a grid-type converter connected to energy storage, and the second type of grid-type converter is a grid-type converter connected to power storage. Both energy storage and power storage are energy storage units in AC microgrids.

4. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, The self-parameter acquisition module acquires the converter's own operating parameters, including three-phase output voltage and output current, self-frequency and power. The three-phase output voltage and output current are directly acquired by sensors, while the self-frequency and power are calculated from the voltage and current.

5. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, In the sparse communication network constructed by the converter group, each network-type converter is treated as a node. If there is a communication connection between two nodes, they are said to be adjacent or neighboring nodes.

6. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, The grid-type converter control strategy constructed by the high- and low-frequency power decoupling modules consists of two parts: VSG control and transient virtual impedance control. Both VSG control and transient virtual impedance control are controlled by unique control equations. The VSG control equation is as follows: ; In the formula, f is the VSG frequency, f0 is the rated frequency, J is the moment of inertia, D is the damping coefficient, and P... m P is the active power reference value. e P is the active power output by the GFM. ref For a given active power, k p The active droop factor is t, where t is time, E and E0 are the output voltage amplitude and rated voltage amplitude of the VSG, respectively, and k is the active droop factor. q Q is the reactive power droop factor. e For GFM, output reactive power; Q ref Given reactive power; The control equation for transient virtual impedance control is: ; In the formula, E d and E q These are the voltage command values ​​on the d and q axes, respectively, i d and i q The output currents on the d and q axes are respectively, r v For virtual resistance, L v For virtual reactance, and u d * with u q * This represents the output of the virtual impedance control, where Ts is the time constant of the high-pass filter. The high- and low-frequency power decoupling module calculates based on the converter's own operating parameters, and uses the converter corresponding to the energy storage unit to apply a transient virtual impedance to the energy storage unit to suppress its transient response, thereby obtaining the voltage command value and frequency command value required to realize hybrid energy storage.

7. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, When constructing the distributed control strategy, the distributed control module adds a consensus algorithm to the VSG control equations to obtain the corrected second-level VSG control equations, specifically: ; In the formula, P refi Given the active power of the i-th GFM, G refi Let α be the consistency variable for the i-th GFM. ij k represents the communication weights among multiple agents. e This is the deviation correction factor; The distributed control module then adds event-triggered control to the VSG control equations, resulting in a second-order VSG control equation with low communication overhead: ； In the formula, ε is the event triggering condition parameter; The distributed control module analyzes and controls the converter based on its own parameters to obtain control results, which are voltage and frequency.

8. The distributed control system for hybrid energy storage grid-type converters according to claim 2, characterized in that, After obtaining the control result, the integrated modulation control module obtains the three-phase AC voltage waveform through dq transformation, and further modulates it into a three-phase PWM switching control signal, which is then applied to the grid-type converter to achieve the control effect.

Images