A manganese-based lithium battery energy storage device and off-grid multi-modal collaborative control method and system

Abstract

The application belongs to the technical field of battery energy storage, and discloses a manganese-based lithium battery energy storage device and an off-grid multi-modal collaborative control method and system, aiming to solve the problems of the expansion of the state-of-charge difference of multiple energy storage units in the process of grid connection and island operation and the deep over-discharge of low state-of-charge units. A hierarchical collaborative control architecture including a system scheduling layer, a coordination control layer and a local execution layer is constructed, and the operation mode is determined according to the electrical parameters of the point of common coupling; the state-of-charge deviation factor is determined according to the real-time state-of-charge of each energy storage unit, and the active power distribution coefficient is adaptively corrected in combination with the rated capacity and the available charge and discharge capacity; when the energy storage unit reaches the state-of-charge protection threshold, power limitation is implemented and power redistribution is performed on the remaining available energy storage units, so as to realize the state-of-charge balance and collaborative operation of multiple energy storage units.

Description

Technical Field

[0001] This application belongs to the field of battery energy storage technology, and specifically relates to a method and system for off-grid multimodal collaborative control adapted to manganese-based lithium battery energy storage devices. Background Technology

[0002] With the construction of new power systems and the increasing proportion of distributed power sources, battery energy storage systems have been widely used in regional distribution networks for power regulation, peak shaving and valley filling, frequency and voltage regulation, and power supply assurance. Manganese-based lithium batteries are characterized by abundant manganese resources, low cathode material costs, good thermal stability, and long cycle life, making them suitable for large-scale energy storage applications in regional distribution networks. Regional distribution networks are typically connected to the upper-level grid through a point of common coupling. When the upper-level grid is normal, they operate in a grid-connected state, utilizing multiple energy storage units for charging and discharging power regulation according to system operating needs. In the event of an anomaly or fault in the upper-level grid, the energy storage system, in conjunction with distributed power sources, can maintain islanded operation of the regional distribution network. Existing energy storage control typically combines technologies such as energy storage converter control, voltage and frequency control, power distribution, and operational status management to achieve energy exchange and stable system operation under different operating conditions.

[0003] However, in regional distribution networks containing multiple manganese-based lithium battery energy storage units, the differences in initial state of charge, rated capacity, and actual charge / discharge capabilities among these units can lead to a continuous widening of the state of charge difference when power is allocated according to a fixed ratio or control parameters over a long period. This is especially true when the manganese-based lithium batteries are in a lower state of charge range; continued deep discharge can increase the risk of manganese dissolution and capacity decay. Simultaneously, grid-connected / off-grid switching can generate voltage sags, frequency shifts, and transient current surges. Fixed virtual inertia cannot adequately address the frequency support requirements under varying degrees of disturbance. Furthermore, when the available output in isolated areas is insufficient, the lack of load grading management that matches the safe operating range of energy storage makes it difficult to balance the deep discharge constraints of manganese-based lithium batteries with continuous power supply to critical loads. Therefore, a unified multi-modal control architecture is needed to coordinate operating mode identification, state of charge balancing among multiple energy storage units, smooth grid-connected / off-grid switching, inertia support, and dynamic power balance under power shortage conditions. Summary of the Invention

[0004] This application provides a multi-modal collaborative control method and system for manganese-based lithium battery energy storage devices, applicable to large-scale manganese-based lithium battery energy storage application scenarios in regional distribution networks with high proportion of distributed power sources. It mainly solves the problems of widening differences in the state of charge of multiple energy storage units, deep over-discharge of low-charge units, transient impacts during switching, and difficulty in coordinating the power supply of critical loads with the safe operation of energy storage when there is insufficient available output in regional distribution networks containing multiple manganese-based lithium battery energy storage units during grid connection, islanding, and grid connection / off-grid switching.

[0005] To achieve the above objectives, this application provides the following technical solution: In a first aspect, this application provides a manganese-based lithium battery energy storage device and an off-grid multi-modal cooperative control method, comprising: A hierarchical multimodal collaborative control architecture is constructed, which includes a system scheduling layer, a coordination control layer, and a local execution layer that are interconnected from top to bottom. The system scheduling layer monitors the electrical parameters of the common connection point of the regional distribution network in real time, determines the operation mode of the regional distribution network according to the electrical parameters and preset judgment rules, and outputs the mode switching command and total power command corresponding to the operation mode. The operation modes include grid-connected mode, islanded mode and grid-connected / off-grid switching transition mode. In the grid-connected mode and the islanded mode, the real-time state of charge of each manganese-based lithium battery energy storage unit is obtained through the coordination control layer. The corresponding state of charge deviation factor is determined according to the real-time state of charge of each manganese-based lithium battery energy storage unit. Combined with the rated capacity and available charge and discharge capability of each manganese-based lithium battery energy storage unit, the active power allocation coefficient of each manganese-based lithium battery energy storage unit is adaptively corrected. The power corresponding to the total power command is allocated according to the active power allocation coefficient to achieve state of charge balance among multiple manganese-based lithium battery energy storage units. When the state of charge of any of the manganese-based lithium battery energy storage units reaches the preset state of charge protection threshold, the charging and discharging power of the manganese-based lithium battery energy storage unit is limited, and the power is redistributed according to the available charging and discharging capabilities of the remaining available manganese-based lithium battery energy storage units. The local execution layer controls the operation of the energy storage converter corresponding to each manganese-based lithium battery energy storage unit according to the mode switching command and power allocation result.

[0006] As a further improvement of this application, the system scheduling layer serves as a global decision-making layer, used to perform power grid status monitoring, operation mode discrimination, and mode switching command issuance; The coordination control layer serves as an optimization coordination layer, used to perform state of charge monitoring, load power acquisition, power optimization allocation, and load hierarchical management decisions for each manganese-based lithium battery energy storage unit. The local execution layer serves as a real-time execution layer, used to perform closed-loop control, operation mode switching, and real-time acquisition of electrical quantities for the energy storage converters corresponding to each manganese-based lithium battery energy storage unit.

[0007] As a further improvement to this application, the step of determining the operating mode of the regional distribution network based on the electrical parameters and preset judgment rules includes: Detect the voltage and frequency of the common connection point; When the voltage and / or frequency of the common connection point deviates from the corresponding rated range and the abnormal state continues for a preset time, it is determined that a fault has occurred in the upstream power grid, and a grid-connected to islanded switching command is output. When the voltage and frequency of the upstream power grid are detected to have returned to the corresponding rated range and have been operating stably for a preset time, it is determined that the upstream power grid has returned to normal and an islanding to grid connection switching command is output.

[0008] As a further improvement of this application, in the grid-connected mode, the local execution layer controls each of the manganese-based lithium battery energy storage units to perform virtual synchronous generator control, adaptively adjusts the virtual inertia corresponding to each of the manganese-based lithium battery energy storage units according to the system frequency change rate, and performs grid-connected support control on the manganese-based lithium battery energy storage units through active-frequency control and reactive-voltage control links.

[0009] As a further improvement to this application, the virtual inertia of the i-th manganese-based lithium battery energy storage unit is determined according to the following formula:

[0010] in, Let be the virtual inertia of the i-th manganese-based lithium battery energy storage unit. As the baseline virtual inertia, This is the adaptive gain coefficient, with a value ranging from 1 to 5. The real-time frequency change rate of the system. This represents the maximum permissible rate of frequency change.

[0011] As a further improvement of this application, the active-frequency control link adopts a virtual rotor motion equation for active control, and the reactive-voltage control link adopts a droop control equation for reactive control. The control parameters in the virtual rotor motion equation include at least the virtual inertia, virtual angular frequency, rated angular frequency, active power reference value, actual output active power, and active damping coefficient. The control parameters in the droop control equation include at least the voltage reference value, rated voltage, reactive voltage droop coefficient, actual output reactive power, and initial reactive power value.

[0012] As a further improvement to this application, when performing a smooth handover from grid connection to islanding in the grid connection / offline handover transition mode, the following is included: Upon receiving the grid-connected to islanded switching command, maintain the current output power and controller status of each energy storage converter to ensure continuous control. The main energy storage unit is determined based on the state of charge of each manganese-based lithium battery energy storage unit, and the V / f main control circuit of the main energy storage unit is put into a pre-start state before the grid connection switch of the common connection point is disconnected. After disconnecting the grid connection switch of the common connection point, control the main energy storage unit to establish the voltage and frequency reference of the islanded system, and control the remaining manganese-based lithium battery energy storage units to adopt the droop-follow mode; An adaptive virtual impedance is introduced during the switching process to suppress transient current surges; When the voltage deviation and frequency deviation of the islanded system are both within the corresponding allowable range and remain stable for a preset time, it is determined that the grid-connected to islanded switching is complete and the transient impedance control mode is exited.

[0013] As a further improvement to this application, the step of determining the main energy storage unit based on the state of charge of each of the manganese-based lithium battery energy storage units includes: The manganese-based lithium battery energy storage unit with the highest real-time state of charge is determined as the main energy storage unit; When the state of charge difference among multiple manganese-based lithium battery energy storage units is within a preset range, the manganese-based lithium battery energy storage unit with the largest rated capacity is determined as the main energy storage unit.

[0014] As a further improvement to this application, the adaptive virtual impedance includes a virtual resistance component and a virtual reactance component that decay over time; The decay time constant of the virtual resistance component is smaller than the decay time constant of the virtual reactance component; Both the virtual resistance component and the virtual reactance component are limited and adjusted according to the relationship between the real-time output current of the corresponding energy storage converter and the transient overcurrent limit value. The time is the time calculated after the adaptive virtual impedance is put into operation, and the virtual resistance component and the virtual reactance component are set to zero after the grid-connected to islanded switching is completed.

[0015] As a further improvement to this application, when performing a smooth handover from islanding to grid connection in the grid-connected handover transition mode, the following is included: Upon receiving the islanding-to-grid switching command, pre-synchronization phase-locked control is initiated, and the voltage phase angle, voltage amplitude, and frequency of the grid side and the islanding side are collected in real time. The output of the main energy storage unit is adjusted according to the synchronization deviation between the grid side and the island side. When the synchronization deviation meets the preset synchronization accuracy requirement, the grid connection switch of the common connection point is closed. Through a power ramp transition, each of the manganese-based lithium battery energy storage units is switched from off-grid control mode to grid-connected virtual synchronous generator control mode.

[0016] As a further improvement to this application, a proportional-integral synchronous regulation component is superimposed on the V / f control loop of the main energy storage unit, wherein: The phase angle synchronization adjustment is proportional-integral based on the deviation between the voltage phase angle on the grid side and the voltage phase angle on the island side; The voltage amplitude synchronization adjustment is proportional-integral based on the deviation between the voltage amplitude on the grid side and the voltage amplitude on the island side.

[0017] As a further improvement to this application, the state-of-charge deviation factor corresponding to the i-th manganese-based lithium battery energy storage unit is determined according to the following formula:

[0018] The capacity-weighted average state of charge of the plurality of manganese-based lithium battery energy storage units is determined according to the following formula:

[0019] In the formula, This represents the real-time state of charge of the i-th manganese-based lithium battery energy storage unit. The state of charge (SOC) is the capacity-weighted average of the multiple manganese-based lithium battery energy storage units, weighted by their rated capacity. and These are the upper and lower limits of the permissible state of charge, respectively. Let be the rated capacity of the i-th manganese-based lithium battery energy storage unit, and n be the number of manganese-based lithium battery energy storage units.

[0020] As a further improvement of this application, the active power allocation coefficient of each manganese-based lithium battery energy storage unit is determined based on the benchmark active power allocation coefficient, the rated capacity of the corresponding manganese-based lithium battery energy storage unit, the total rated capacity of multiple manganese-based lithium battery energy storage units, the corresponding state of charge deviation factor, and the state of charge balance adjustment coefficient. In addition, opposite state of charge deviation adjustment relationships are adopted for charging and discharging conditions, so that energy storage units with relatively low state of charge obtain a relatively large charging power allocation weight during charging, and energy storage units with relatively high state of charge obtain a relatively large discharging power allocation weight during discharging.

[0021] As a further improvement of this application, when the real-time state of charge of any of the manganese-based lithium battery energy storage units is lower than the preset protection lower limit, the manganese-based lithium battery energy storage unit is controlled to stop discharging, and the remaining available manganese-based lithium battery energy storage units and distributed power sources in the regional power distribution network work together to make up for the power gap caused by the manganese-based lithium battery energy storage unit stopping discharging.

[0022] As a further improvement to this application, the load of the regional distribution network is divided according to power supply priority as follows: Level 1 load, which refers to the load on personal safety and critical infrastructure; Secondary loads, which are important industrial and commercial loads; Level 3 load, wherein the Level 3 load is an interruptible load; The power supply priority of the primary load is higher than that of the secondary load, and the power supply priority of the secondary load is higher than that of the tertiary load.

[0023] As a further improvement to this application, the power supply guarantee condition is determined based on the total available output of the energy storage system and the distributed power source, and the power supply guarantee condition includes: Under full-load protection conditions, the power supply to the primary load, the secondary load, and the tertiary load is maintained. Under restricted protection conditions, the power supply to the primary load and the secondary load shall be maintained. In critical protection conditions, only the primary load is kept powered. The system switches between the full-load protection condition, the limited protection condition, and the critical protection condition based on the total available output of the energy storage system and the distributed power source.

[0024] As a further improvement to this application, the system power margin index is determined according to the following formula:

[0025] in, The total available output power of the energy storage system. This refers to the total output of distributed power sources in the aforementioned regional power distribution network. This represents the total load power of the area. When the system power margin index is lower than the first preset threshold, the demand response of the third-level load is initiated; When the system power margin index is lower than the second preset threshold, and the sum of the total available output power of the energy storage system and the total output of the distributed power source is insufficient to meet the load demand, the third-level load and the second-level load are reduced in order of power supply priority from low to high until the system power balance is restored. When the system power margin index recovers to above the third preset threshold and the total available output meets the load recovery conditions, the reduced loads are restored in descending order of power supply priority.

[0026] As a further improvement of this application, when the capacity-weighted average state of charge of multiple manganese-based lithium battery energy storage units is lower than a preset critical value, and the sum of the total output of the distributed power source and the total available output power of the energy storage system is insufficient to meet all load demands, the lower priority loads are reduced according to the power supply priority. When the sum of the total output of the distributed power source and the total available output power of the energy storage system is only able to meet the power supply demand of the primary load, only the primary load is supplied with power, and an emergency alarm signal is sent.

[0027] As a further improvement of this application, under the constraint of balanced state of charge of multiple manganese-based lithium battery energy storage units, power optimization allocation is performed with the goal of minimizing the total charge and discharge loss of the energy storage system. The charge and discharge loss of the i-th manganese-based lithium battery energy storage unit is determined by the following formula:

[0028] in, Let be the charge / discharge loss of the i-th manganese-based lithium battery energy storage unit. Let i be the output power of the i-th manganese-based lithium battery energy storage unit. , and These are the switching loss coefficient, conduction loss coefficient, and no-load fixed loss coefficient of the energy storage converter corresponding to the i-th manganese-based lithium battery energy storage unit, respectively. by

[0029] To optimize the objective, the following constraints are set:

[0030]

[0031]

[0032] in, This represents the maximum permissible deviation from the state of charge. and These are the lower and upper power limits of the i-th manganese-based lithium battery energy storage unit, respectively; The optimization problem formed by the optimization objective and the constraints is solved by the Lagrange multiplier method to obtain the target output allocation results of each manganese-based lithium battery energy storage unit.

[0033] Secondly, this application provides a manganese-based lithium battery energy storage device and an off-grid multimodal cooperative control system, comprising: The hierarchical control architecture module is used to realize the communication and instruction loop between the system scheduling layer, coordination control layer and local execution layer; The mode discrimination module is deployed in the system scheduling layer and is used to monitor the power grid status of the regional distribution network, discriminate the operating mode, and issue mode switching instructions. The grid-connected control module, deployed in the local execution layer, is used to perform grid-connected support control and cooperate with the coordination control layer to complete power distribution under grid-connected operating conditions. The smooth switching module, deployed in the local execution layer, is used to perform bidirectional smooth switching control from grid-connected to islanded and from islanded to grid-connected. A state-of-charge (POC) balancing control module is deployed in the coordination control layer to adaptively adjust the active power allocation coefficient according to the POC deviation factor of each manganese-based lithium battery energy storage unit, so as to achieve POC balancing among multiple manganese-based lithium battery energy storage units. The load classification management module, deployed in the coordination control layer, is used to perform multi-condition adaptive control and dynamic power balance control based on the total available output of the energy storage system and distributed power sources.

[0034] As a further improvement to this application, the system scheduling layer includes a common connection point status monitoring function, an operation mode discrimination function, and an instruction issuance function; The coordination and control layer includes a state of charge summary function, a state of charge deviation factor calculation function, a power allocation weight calculation function, and a power constraint coordination function. The local execution layer includes closed-loop control function for energy storage converter, operation mode switching function, and electrical quantity acquisition function. The local execution layer is communicatively connected to multiple manganese-based lithium battery energy storage units.

[0035] As a further improvement of this application, the smooth switching module is used to maintain the continuous control of the energy storage converter during the grid-connected to islanded process, determine the main energy storage unit according to the state of charge of each manganese-based lithium battery energy storage unit, enable the V / f main control link of the main energy storage unit to enter the pre-start state before the grid connection switch of the point of common coupling is disconnected, control the main energy storage unit to establish the voltage and frequency reference of the islanded system after the grid connection switch of the point of common coupling is disconnected, and suppress transient current impact through adaptive virtual impedance; and during the islanded to grid-connected process, grid connection is carried out after the voltage phase angle, voltage amplitude and frequency of the islanded side and the grid side reach the preset synchronization conditions through pre-synchronization phase-locked loop control. The load classification management module is used to determine the system power margin based on the total available output power of the energy storage system, the total output power of distributed power sources, and the total load power of the region, and to reduce or restore loads with different power supply priorities based on the system power margin.

[0036] Compared with the prior art, this application has at least the following beneficial effects: This application constructs a hierarchical multimodal collaborative control architecture in which the system scheduling layer, coordination control layer, and local execution layer communicate with each other. It incorporates grid operation mode discrimination, power coordination of multiple energy storage units, and execution control of energy storage converters into a unified control link, so that a control relationship is formed between grid-connected mode, islanded mode, and grid-connected / off-grid switching transition mode. This is conducive to improving the coordination of multiple manganese-based lithium battery energy storage units under different operating conditions.

[0037] This application determines the state-of-charge (POC) deviation factor based on the real-time POC of each manganese-based lithium battery energy storage unit, and adaptively corrects the active power allocation coefficient by combining the rated capacity and available charge / discharge capability of each energy storage unit. This allows energy storage units with different POCs and capacities to undertake corresponding charge / discharge power according to their own operating conditions. During discharge, energy storage units with relatively higher POCs undertake relatively higher discharge power, while those with relatively lower POCs undertake relatively lower discharge power. The opposite adjustment direction is adopted during charging, thereby gradually reducing the POC difference among multiple energy storage units, reducing the probability of continuous deep discharge of low POC units, and reducing the risk of manganese dissolution and capacity decay.

[0038] When an energy storage unit reaches a preset state of charge protection threshold, this application implements a power limit on the corresponding energy storage unit for charging and discharging. It also redistributes power based on the available charging and discharging capabilities of other available energy storage units. This ensures that when a single energy storage unit is subject to state of charge protection, its corresponding power demand can be coordinated and borne by other available energy storage units, thus balancing battery protection and regional power distribution network balance.

[0039] This application can also improve frequency support and grid-connected / off-grid switching performance under different operating conditions through adaptive virtual inertia, adaptive virtual impedance and pre-synchronization control, and through dynamic power balance control that combines power margin and load priority, prioritize the power supply of high-level loads when the total available output of energy storage system and distributed power source is insufficient, so as to coordinate the discharge depth constraint of manganese-based lithium battery with the power supply demand of critical load. Attached Figure Description

[0040] Figure 1 This is a flowchart illustrating a manganese-based lithium battery energy storage device and an off-grid multimodal collaborative control method and system provided in an embodiment of this application.

[0041] Figure 2 This is a schematic diagram of the architecture of a manganese-based lithium battery energy storage device and an off-grid multimodal collaborative control system provided in an embodiment of this application. Detailed Implementation

[0042] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0043] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relativity.

[0044] The specific embodiments of this application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and technical features described in this application can be combined with each other.

[0045] This application is applied to large-scale manganese-based lithium battery energy storage scenarios in regional distribution networks with a high proportion of distributed power sources. The regional distribution network is connected to the upper-level grid through a point of common coupling (PCC) and is in grid-connected operation under normal operating conditions. When the upper-level grid experiences a fault or does not meet the grid-connected operation conditions, it can switch to off-grid islanded operation.

[0046] PCC stands for Point of Common Coupling; SOC stands for State of Charge, which characterizes the state of charge of a manganese-based lithium battery energy storage unit. PCS is short for Power Conversion System, which is an energy storage converter. VSG is short for Virtual Synchronous Generator.

[0047] Manganese-based lithium batteries possess advantages such as abundant manganese resources, low cathode material cost, good thermal stability, and long cycle life. However, in actual operation, when manganese-based lithium batteries are in a lower SOC range, the risk of manganese dissolution increases as the SOC decreases, especially when the SOC is below 20%, where the manganese dissolution rate rises significantly. Therefore, during long-term operation of multiple energy storage units, it is necessary to consider the SOC differences between different energy storage units and the depth of discharge of low-SOC energy storage units.

[0048] Example 1 like Figure 1 As shown, this embodiment provides a manganese-based lithium battery energy storage device and an off-grid multimodal collaborative control method.

[0049] First, a hierarchical multimodal collaborative control architecture is constructed, which includes a system scheduling layer, a coordination control layer, and a local execution layer that are connected from top to bottom.

[0050] The system scheduling layer is used to obtain the overall operating status of the regional distribution network and formulate operating modes and power control requirements; the coordination control layer is used to obtain the operating status of multiple manganese-based lithium battery energy storage units and coordinate power among them; the local execution layer is used to control the operation of the PCS corresponding to each manganese-based lithium battery energy storage unit based on the control results formed by the upper layer. Through information interaction between the three control layers, a continuous control link can be formed, which includes system-level operating status determination, multi-energy storage unit coordination, and unit-level real-time control.

[0051] The system dispatch layer monitors the electrical parameters of the regional distribution network PCC in real time, determines the operating mode of the regional distribution network based on the electrical parameters of the PCC and preset judgment rules, and outputs the mode switching command and total power command corresponding to the operating mode.

[0052] The operating modes include grid-connected mode, islanded mode, and grid-connected / off-grid transition mode. The electrical parameters of the PCC (Power Control Center) characterize the operating status between the regional distribution network and the upstream grid. The system dispatch layer determines the current operating mode based on the PCC's electrical parameters, generates a mode switching command, and simultaneously generates a total power command based on the regional distribution network's operational needs. The total power command characterizes the overall charging or discharging power required by multiple manganese-based lithium battery energy storage units and serves as the input for subsequent power coordination among multiple energy storage units.

[0053] In both grid-connected and islanded modes, the real-time SOC of each manganese-based lithium battery energy storage unit is obtained through the coordination control layer. Based on the real-time SOC of each manganese-based lithium battery energy storage unit, the corresponding SOC deviation factor is determined. Combined with the rated capacity and available charge / discharge capability of each manganese-based lithium battery energy storage unit, the active power allocation coefficient of each manganese-based lithium battery energy storage unit is adaptively corrected. Based on the active power allocation coefficient, the power corresponding to the total power command is allocated.

[0054] Among them, the SOC deviation factor is used to characterize the degree of deviation of the real-time SOC of the corresponding manganese-based lithium battery energy storage unit from the overall SOC level of multiple energy storage units. The rated capacity is used to characterize the energy storage scale of different manganese-based lithium battery energy storage units, and the available charge and discharge capacity is used to characterize the charging power or discharging power that the corresponding energy storage unit can actually handle under the current operating conditions.

[0055] During discharge, the power distribution is adjusted according to the SOC state of different manganese-based lithium battery energy storage units, so that the energy storage units with relatively higher SOC bear relatively larger discharge power and the energy storage units with relatively lower SOC bear relatively smaller discharge power. During charging, the SOC adjustment direction is reversed from that during discharge, so that the energy storage units with relatively lower SOC bear relatively larger charging power and the energy storage units with relatively higher SOC bear relatively smaller charging power.

[0056] This allows energy storage units with different SOC states to gradually reach equilibrium during operation, reducing the probability of continuous deep discharge in low SOC energy storage units and reducing the risk of manganese dissolution and capacity decay caused by deep over-discharge.

[0057] During the power allocation process among multiple energy storage units, the State of Charge (SOC) of each manganese-based lithium battery energy storage unit is continuously monitored. When the SOC of any manganese-based lithium battery energy storage unit reaches a preset SOC protection threshold, the charging and discharging power of that manganese-based lithium battery energy storage unit is limited in the corresponding direction, and the power is redistributed according to the available charging and discharging capabilities of the remaining available manganese-based lithium battery energy storage units.

[0058] During discharge, when a corresponding energy storage unit reaches its State of Charge (SOC) discharge protection condition, its discharge power can be reduced or it can be stopped from discharging. During charging, when a corresponding energy storage unit reaches its State of Charge (SOC) charging protection condition, its charging power can be reduced or charging can be stopped. The remaining unallocated power resulting from power limitation is then taken over by other energy storage units that meet the operating conditions.

[0059] The above control method coordinates the SOC protection action with the power balance of multiple energy storage units. While reducing the risk of overcharging or over-discharging of a single energy storage unit, it can also prevent a large system power gap from being directly formed when a single energy storage unit is restricted.

[0060] Finally, the local execution layer controls the operation of the PCS corresponding to each manganese-based lithium battery energy storage unit according to the mode switching command and power allocation result, so that the aforementioned PCC status monitoring, operation mode discrimination, SOC status processing, power coordination and SOC protection results are transformed into the actual control results of the corresponding PCS, forming a closed-loop control process from status acquisition, mode discrimination, coordination allocation, protection adjustment to local execution.

[0061] Example 2 like Figure 1 and Figure 2 As shown, this embodiment provides a multi-modal collaborative control method for manganese-based lithium battery energy storage devices that covers grid-connected operation, grid-to-offline switching, and islanded operation.

[0062] Specifically, it includes the following steps.

[0063] Step S1: Construct a hierarchical multimodal collaborative control architecture adapted to the electrochemical characteristics of manganese-based lithium batteries.

[0064] The hierarchical multimodal collaborative control architecture includes a system scheduling layer, a coordination and control layer, and a local execution layer that are interconnected from top to bottom.

[0065] The system scheduling layer is the global decision-making layer, responsible for power grid status monitoring, operation mode identification, and mode switching command issuance.

[0066] The coordination and control layer is the optimization and coordination layer, responsible for monitoring the SOC of each energy storage unit, collecting load power, optimizing power allocation, and making load classification management decisions.

[0067] The local execution layer is a real-time execution layer, responsible for the closed-loop control, mode switching execution, and real-time acquisition of electrical quantities of each energy storage unit PCS.

[0068] The three control layers interact with each other via communication. The system dispatch layer formulates the operating mode and control requirements based on the regional distribution network operating status; the coordination control layer formulates the corresponding power coordination results based on the control requirements formed by the system dispatch layer and the operating status of each energy storage unit; the local execution layer controls the operation of the PCS based on the corresponding control commands and power coordination results, and collects the real-time electrical quantities of the PCS and energy storage units to provide status data for subsequent control cycles.

[0069] In step S2, the system dispatch layer monitors the electrical parameters of the regional distribution network PCC in real time, performs operation mode discrimination based on preset judgment rules, and outputs mode switching instructions and total power instructions to the coordination control layer and the local execution layer.

[0070] The operating modes include grid-connected mode, islanded mode, and grid-connected / off-grid switching transition mode.

[0071] In one implementation, the voltage and frequency of the PCC point can be detected in real time. When the voltage or frequency of the PCC point deviates from the corresponding rated range and the abnormal state continues for a preset time, it is determined that a fault has occurred in the upstream power grid, and a grid-connected to islanded switching command is output.

[0072] When the voltage and frequency of the upstream power grid are detected to have returned to the corresponding rated range and have been operating stably for a preset time, it is determined that the upstream power grid has returned to normal and an islanding to grid connection switching command is output.

[0073] By comprehensively judging the PCC voltage and frequency status and their duration, the impact of instantaneous fluctuations on the operating mode discrimination results can be reduced, and a control basis can be provided for subsequent bidirectional mode switching.

[0074] Step S3: In grid-connected mode, the local execution layer controls each manganese-based lithium battery energy storage unit to perform grid-connected support control.

[0075] In one implementation, grid-connected support control can employ adaptive VSG control and adaptively adjust the virtual inertia according to the system frequency change rate to provide inertia support and frequency and voltage regulation services for the regional distribution network.

[0076] The active-frequency control loop can be implemented using the following virtual rotor motion equations: (1) In the formula, For the first Virtual inertia of a manganese-based lithium battery energy storage unit; This refers to the virtual angular frequency. This is the rated angular frequency; This is a reference value for active power. This refers to the actual output active power; This is the active damping coefficient.

[0077] Virtual Inertia It can be adaptively determined based on the system frequency change rate: (2) In the formula, As a reference virtual inertia; This is the adaptive gain coefficient, with a value ranging from 1 to 5; The real-time frequency change rate of the system; This represents the maximum permissible rate of frequency change.

[0078] When the system frequency change rate increases, the corresponding virtual inertia is increased according to equation (2) so that the PCS can provide stronger inertia support; when the system frequency change rate decreases, the virtual inertia is adjusted accordingly so that the inertia support capability can change with the actual disturbance level.

[0079] The reactive power-voltage control loop can be implemented using the following droop control equation: (3) In the formula, This is the voltage reference value; Rated voltage; This is the reactive voltage droop factor; This refers to the actual output reactive power. This is the initial value of reactive power.

[0080] Through the active-frequency control link and the reactive-voltage control link, the active and reactive outputs of the energy storage unit can be adjusted according to the real-time frequency and voltage status of the system.

[0081] In some implementations, adaptive virtual inertia control can also be used in islanded operation to adjust the virtual inertia according to the rate of change of the islanded system frequency, thereby improving the frequency support capability under islanded load disturbance conditions.

[0082] Step S4: In the grid-connected / off-grid switching transition mode, bidirectional smooth switching control is performed based on the hierarchical multimodal collaborative control architecture.

[0083] During the transition from grid connection to islanding, multiple energy storage units can transition from grid connection to islanding by maintaining continuous control, establishing an islanding voltage and frequency reference, and introducing adaptive virtual impedance to suppress transient current surges.

[0084] During the process of islanding to grid connection, the voltage phase angle, voltage amplitude and frequency of the islanding side and the grid side are synchronized by pre-synchronization phase-locked loop control, and then the PCC closing and control mode transition are completed.

[0085] In one implementation, the smooth switching process from grid-connected to islanded includes steps S411 to S415.

[0086] Step S411: After receiving the grid-connected to islanded command, maintain the current output power and controller status of each PCS to keep the control quantity continuous during the start of the switching phase.

[0087] Step S412: Determine the main energy storage unit based on the SOC of each energy storage unit. Preferably, select the energy storage unit with the highest SOC as the main energy storage unit; when the SOC difference between multiple energy storage units is within a preset small range, select the energy storage unit with the largest rated capacity as the main energy storage unit. After selecting the main energy storage unit, before the PCC grid connection switch is disconnected, put the V / f main control circuit of the main energy storage unit into a pre-start state so as to establish the voltage and frequency reference of the islanded system in a timely manner after the PCC grid connection switch is disconnected.

[0088] Step S413: Disconnect the grid connection switch at PCC point, control the main energy storage unit to enter the V / f master control state from the pre-start state, establish the voltage and frequency reference of the islanded system, and at the same time control the other energy storage units to enter the droop follow mode.

[0089] By pre-starting the V / f master control circuit before the PCC is disconnected, and having the main energy storage unit take over the voltage and frequency control of the islanded system after the PCC is disconnected, the control gap caused by restarting the islanded master control after the PCC has been disconnected can be avoided.

[0090] Step S414 introduces an adaptive virtual impedance to suppress transient current surges.

[0091] Virtual resistance and virtual reactance can be determined according to the following formulas: (4) In the formula, , The initial values ​​of the virtual resistance and virtual reactance are determined based on the PCS rated current and allowable overcurrent multiple. The virtual resistance decay time constant; Let be the virtual reactance decay time constant, and ; The time to start calculation after the adaptive virtual impedance is applied; For the first Real-time output current of each PCS; This is the transient overcurrent limit value; This is the saturation limiting function.

[0092] The saturation limiting function is defined as: (5) When the real-time output current of the PCS approaches or exceeds the transient overcurrent limit, the adaptive virtual impedance suppresses the transient current; as the switching process progresses, the virtual resistance and virtual reactance gradually decay according to the corresponding decay time constant.

[0093] Step S415: When the voltage deviation and frequency deviation of the islanded system are both within the corresponding allowable range and remain stable for a preset time, it is determined that the grid-connected to islanded switching is completed, the system enters steady-state islanded operation, the virtual resistance component and virtual reactance component are set to zero, and the transient impedance control mode is exited.

[0094] In one implementation, the smooth switching process from islanded to grid-connected includes steps S421 to S424.

[0095] Step S421: After receiving the islanding to grid connection command, start the pre-synchronization phase-locked loop to collect the voltage phase angle, voltage amplitude and frequency parameters of the grid side and the islanding side in real time.

[0096] Step S422: Superimpose a proportional-integral synchronous regulation component into the V / f control loop of the main energy storage unit.

[0097] The phase angle synchronization adjustment and the voltage amplitude synchronization adjustment are determined according to the following formulas: (6) In the formula, , These are the phase angle synchronous adjustment amount and the voltage amplitude synchronous adjustment amount, respectively. , These are the proportional gains of the phase loop and the voltage loop, respectively. , These are the integral gains of the phase loop and the voltage loop, respectively. , These are the phase angle and voltage amplitude of the grid-side voltage, respectively. , These represent the phase angle and voltage amplitude of the islanded voltage, respectively.

[0098] The V / f output of the main energy storage unit is adjusted based on the phase angle and voltage amplitude deviation between the grid side and the islanded side, so that the phase angle and voltage amplitude on the islanded side gradually approach the corresponding parameters on the grid side. Frequency synchronization is achieved through a pre-synchronization phase-locked loop combined with the V / f control process.

[0099] Step S423: When the phase angle deviation, voltage amplitude deviation and frequency deviation between the island side and the grid side meet the preset synchronization accuracy requirements, close the PCC point grid connection switch.

[0100] Step S424: After the PCC grid-connected switch is closed, each energy storage unit is smoothly switched from off-grid control mode to grid-connected VSG control mode through a power ramp transition, completing the islanding to grid-connected transition.

[0101] Step S5: In grid-connected mode and islanded mode, adaptive active power allocation is implemented according to the SOC of each manganese-based lithium battery energy storage unit, and multi-condition dynamic power balance control is implemented according to the available output of the energy storage system.

[0102] The coordination control layer obtains the real-time SOC of each energy storage unit and calculates the SOC deviation factor corresponding to each energy storage unit. SOC deviation factor of each energy storage unit Determined according to the following formula: (7) The average SOC of all energy storage units, weighted by their rated capacity, is determined according to the following formula: (8) In the formula, For the first Real-time SOC of each energy storage unit; The average SOC is obtained by weighting all energy storage units by their rated capacity. , These are the upper and lower limits of SOC, respectively. For the first The rated capacity of each energy storage unit; This represents the number of energy storage units.

[0103] By calculating the overall SOC level using a capacity-weighted approach, energy storage units with different rated capacities can participate in the overall SOC status evaluation according to their corresponding energy storage scale.

[0104] Under charging conditions, in order for energy storage units with relatively low SOC to bear relatively large charging power, the active power allocation factor is... Determined according to the following formula: (9) Under discharge conditions, in order for energy storage units with relatively high SOC to bear relatively large discharge power, the active power allocation factor is... Determined according to the following formula: (10) In the formula, For the first The active power allocation coefficient of each energy storage unit; The baseline active power distribution factor; This represents the total rated capacity of all energy storage units. This is the SOC equalization adjustment coefficient; the meanings of the other parameters are the same as described above.

[0105] when hour, Under charging conditions, according to equation (9), the lower the SOC of the corresponding energy storage unit, the larger its SOC adjustment term, thereby increasing the corresponding charging power allocation weight. Under discharging conditions, according to equation (10), the higher the SOC of the corresponding energy storage unit, the larger its SOC adjustment term, thereby increasing the corresponding discharging power allocation weight. Thus, low SOC energy storage units obtain greater charging power during charging and bear less discharging power during discharging, while high SOC energy storage units bear greater discharging power during discharging, thereby gradually balancing the SOC of multiple energy storage units.

[0106] During actual power allocation, the coordination control layer determines the power allocation ratio of each energy storage unit relative to the total power command based on the active power allocation coefficient of each energy storage unit, and generates the corresponding active power command for each energy storage unit based on the power allocation ratio. The energy storage unit with the larger active power allocation coefficient receives a larger share of power under the corresponding charging or discharging conditions. Furthermore, the active power command is limited based on the current available charging and discharging capacity of each energy storage unit. When any energy storage unit reaches the SOC protection condition or its available charging and discharging capacity is limited, the power that the energy storage unit can no longer handle is redistributed according to the active power allocation coefficients of the remaining available energy storage units. The local execution layer then issues the final determined active power command to the corresponding energy storage converter for execution.

[0107] In actual operation, the power allocation results are also constrained based on the rated capacity and available charging and discharging capability of each energy storage unit, so that the target power of each energy storage unit is within the corresponding actual executable power range.

[0108] When the State of Charge (SOC) of any energy storage unit falls below the protection lower limit, that energy storage unit is controlled to stop discharging, and power is redistributed according to the available output capacity of the remaining energy storage units. When there are distributed generation sources in the regional distribution network, the remaining available energy storage units and distributed generation sources work together to make up for the output gap caused by the shutdown of that energy storage unit.

[0109] Furthermore, multi-condition adaptive control and dynamic power balance control are performed based on the total available output of the energy storage system and distributed power sources.

[0110] The regional power distribution network load is divided into three priorities: Level 1 loads are those related to personal safety and critical infrastructure, and have the highest power supply priority; Level 2 loads are important industrial and commercial loads, and have a medium power supply priority; and Level 3 loads are interruptible loads, and have a general power supply priority.

[0111] Based on the power supply coverage, the system operating conditions are divided into full-load guarantee condition, limited guarantee condition, and critical guarantee condition. Under full-load guarantee condition, power is supplied to primary, secondary, and tertiary loads; under limited guarantee condition, power is supplied to primary and secondary loads; under critical guarantee condition, power is supplied to only primary loads. The system determines the current available power supply capacity based on the total available output power of the energy storage system and the total output power of the distributed power sources, and switches between full-load guarantee condition, limited guarantee condition, and critical guarantee condition.

[0112] To further quantify the power supply and demand status of the regional distribution network, a system power margin index is defined. : (11) In the formula, This represents the total available output power of the energy storage system. The total output of distributed power sources within the region; This represents the total load power of the region.

[0113] When the system power margin index is lower than the first preset threshold, a three-level interruptible load demand response is initiated to improve the system power margin by reducing the power demand of low-priority loads.

[0114] When the system power margin index is lower than the second preset threshold, and the sum of the total available output power of the energy storage system and the total output of the distributed power source is still insufficient to meet the current load demand, the third-level load and the second-level load are reduced in order of power supply priority from low to high until the system power balance is restored.

[0115] When the system power margin index recovers to above the third preset threshold, and the total available output of the energy storage system and distributed power sources meets the load recovery conditions, the reduced loads are restored in descending order of power supply priority.

[0116] When the average SOC of all energy storage units is lower than the preset threshold, and the sum of the total output of distributed power sources and the total available output power of the energy storage system is still insufficient to meet all load demands, lower priority loads are reduced according to load priority.

[0117] When the total available output of the energy storage system and distributed power sources can only meet the power supply needs of the primary load, only the primary load is supplied with power, and an emergency alarm signal is sent.

[0118] In this embodiment, the first, second, and third preset thresholds are set according to the system power margin deterioration and recovery process, wherein the second preset threshold is lower than the first preset threshold, and the third preset threshold is higher than the first preset threshold. As the system power margin decreases, a three-level load demand response is initiated first when it falls below the first preset threshold, and then low-priority load reduction is performed when it further decreases below the second preset threshold; when the system power margin recovers and rises above the third preset threshold, load recovery is then performed to avoid frequent switching between load reduction and recovery processes.

[0119] Through the above control process, when the SOC of the energy storage unit reaches the protection condition, power compensation is first performed through the other energy storage units and distributed power sources; when the total available output on the power supply side is further insufficient, power balance is restored through load-side hierarchical control, thereby forming a continuous dynamic power balance process of energy storage unit SOC protection, energy storage power coordination and load power supply priority control.

[0120] Furthermore, under the SOC equalization constraint, power allocation can be optimized with the goal of minimizing the total charging and discharging loss of the system.

[0121] No. The charging and discharging loss model for a manganese-based lithium battery energy storage unit is as follows: (12) In the formula, For the first The charging and discharging losses of each energy storage unit; For the first The actual output active power of each energy storage unit; , , The first The switching loss coefficient, conduction loss coefficient, and no-load fixed loss coefficient of each energy storage unit corresponding to the PCS can be obtained through factory type testing and on-site operation calibration.

[0122] The objective function to be optimized is: (13) The corresponding constraints are: (14) In the formula, This represents the maximum permissible deviation of SOC; , The first The lower and upper power limits of each energy storage unit.

[0123] Among the above constraints, the first constraint is used to ensure that the output power of all energy storage units and the output power of distributed power sources jointly meet the regional load power demand; the second constraint is used to limit the deviation of the SOC of each energy storage unit from the capacity-weighted average SOC; and the third constraint is used to ensure that the output power of each energy storage unit does not exceed the corresponding actual operating boundary.

[0124] The Lagrange multiplier method can be used to solve the above convex optimization problem to obtain the optimal power output allocation results for each energy storage unit. By further considering charging and discharging losses based on SOC equalization control, the overall charging and discharging losses of multiple energy storage units can be reduced while satisfying system power balance, SOC equalization, and unit power boundaries.

[0125] like Figure 2 As shown, this application also provides a multi-modal collaborative control system for a manganese-based lithium battery energy storage device, including a hierarchical control architecture module, a mode discrimination module, a grid-connected control module, a smooth switching module, a state-of-charge balancing control module, and a load hierarchical management module.

[0126] The hierarchical control architecture module is used to realize the communication and instruction loop between the system scheduling layer, coordination control layer and local execution layer.

[0127] The system scheduling layer includes PCC status monitoring, operating mode determination, and command issuance functions. PCC status monitoring is used to obtain electrical parameters such as voltage and frequency of the PCC in the regional distribution network; operating mode determination determines the grid-connected mode, islanded mode, or grid-connected / off-grid transition mode based on the PCC status; command issuance is used to send mode switching commands and corresponding power control requirements to the coordination control layer and the local execution layer.

[0128] The mode discrimination module is deployed at the system scheduling layer and is used to monitor the status of the regional power distribution network, determine the operating mode, and issue mode switching commands.

[0129] The coordination control layer includes SOC aggregation, SOC deviation factor calculation, power allocation weight calculation, and power constraint coordination functions. SOC aggregation is used to obtain the real-time SOC and rated capacity of multiple manganese-based lithium battery energy storage units; SOC deviation factor calculation is used to calculate the corresponding SOC deviation factor based on the real-time SOC and capacity-weighted average SOC of each energy storage unit; power allocation weight calculation is used to form the corresponding active power allocation result based on the SOC deviation factor, rated capacity, and available charge / discharge capability; power constraint coordination is used to coordinate the power allocation result based on the SOC protection status of the energy storage units and the available power boundary.

[0130] The State of Charge (SOC) balancing control module is deployed in the coordination control layer and is used to adaptively adjust the active power allocation coefficient based on the SOC deviation factor to achieve automatic SOC balancing of multiple energy storage units.

[0131] The load classification management module is deployed at the coordination control layer to perform multi-condition adaptive control and dynamic power balance control when the total available output of the energy storage system and distributed power sources is insufficient. The load classification management module calculates the system power margin based on the total available output power of the energy storage system, the total output of distributed power sources, and the total regional load power, and performs load demand response, load reduction, or load restoration according to the power margin and power supply priority.

[0132] The local execution layer includes PCS closed-loop control, mode switching execution, and electrical quantity acquisition functions, and communicates with the energy storage unit cluster.

[0133] PCS closed-loop control is used to adjust the PCS of the corresponding energy storage unit according to active power, reactive power and voltage frequency control commands; mode switching execution is used to change the PCS operation control mode according to the mode switching command output by the system scheduling layer; electrical quantity acquisition is used to collect the real-time operating electrical quantities of each energy storage unit and PCS, and feed back the corresponding status information to the coordination control layer and the system scheduling layer.

[0134] The grid-connected control module is deployed at the local execution layer to perform grid-connected support control and coordinate with the control layer to complete power distribution under grid-connected conditions. The grid-connected control module can adopt the aforementioned adaptive VSG control, adjust the virtual inertia according to the system frequency change rate, and perform active-frequency and reactive-voltage control.

[0135] The smooth switching module is deployed at the local execution layer to perform bidirectional smooth switching control for grid-connected to islanded and islanded to grid-connected transitions. During the grid-connected to islanded transition, the smooth switching module maintains continuous PCS output power and controller status. It determines the main energy storage unit based on the SOC and rated capacity of each energy storage unit. Before PCC disconnection, it pre-starts the V / f main control loop of the main energy storage unit. After PCC disconnection, the main energy storage unit establishes the islanded system voltage and frequency reference and uses adaptive virtual impedance to suppress transient current surges. During the islanded to grid-connected transition, the smooth switching module obtains the voltage phase angle, voltage amplitude, and frequency deviation between the grid side and the islanded side through pre-synchronous phase-locked loop control. It performs synchronous adjustment through the V / f control loop of the main energy storage unit. After the synchronization conditions are met, it closes the PCC grid-connected switch and then switches each energy storage unit to the grid-connected VSG control mode via a power ramp.

[0136] Thus, a closed-loop control relationship is formed between the system scheduling layer, coordination control layer and local execution layer, from the determination of system operating status and the coordinated allocation of multiple energy storage units to the actual execution of PCS. Corresponding control methods are adopted under different operating conditions such as grid connection, switching and islanding, and the control connection between each operating condition is maintained through a unified hierarchical control architecture.

[0137] Example 3 This embodiment uses numerical simulation to verify the operational effectiveness of the above-mentioned manganese-based lithium battery energy storage device and its multi-modal collaborative control method for grid-connected and off-grid operation in terms of smooth switching between grid-connected and off-grid operation, off-grid frequency support, SOC balancing of multiple energy storage units, and continuous power supply to critical loads.

[0138] The simulation object is an equivalent model of a regional distribution network including three sets of manganese-based lithium battery energy storage units, distributed power sources, three-level loads, and PCC. The simulation parameter configuration is shown in Table 1.

[0139] Table 1 Simulation Parameter Configuration Table

[0140] Under comparative control, each energy storage unit allocates power according to its rated capacity ratio, and the virtual inertia and virtual impedance parameters remain fixed. When the off-grid power margin is insufficient, the power supply priority of different loads is not distinguished.

[0141] Under the control of this application, the system scheduling layer determines the grid-connected, off-grid, and switching modes based on the PCC voltage and frequency status; during the grid-connected to off-grid transition process, adaptive virtual impedance is used to suppress transient impacts, and virtual inertia is adjusted according to the system frequency change rate; the coordination control layer adjusts the power allocation weight according to the SOC deviation factor of each energy storage unit, and implements load management according to power supply priority when the power margin is insufficient.

[0142] First, an equivalent model of the regional power distribution network is established, the rated capacity and initial SOC of three energy storage units are set, and the power of primary load, secondary load, tertiary load and distributed power output curves are set.

[0143] The system is kept in grid-connected operation from 0 s to 20 s, so that the three energy storage units are in grid-connected scheduling state.

[0144] At 20 s, an anomaly in the upstream power grid was simulated, causing the system to switch from grid-connected mode to off-grid mode, and the transient current and PCC voltage during the switching process were recorded.

[0145] A sudden increase in off-grid load was simulated at 55 s, and the minimum system frequency, maximum frequency deviation, and energy storage output response were recorded.

[0146] Three sets of SOC changes for energy storage units were recorded throughout the simulation period. The maximum SOC difference was compared between two scenarios: power allocation based on rated capacity ratio and adaptive power allocation based on SOC deviation factor. The maximum SOC difference is the difference between the maximum and minimum SOC values ​​of multiple energy storage units, which characterizes the degree of SOC imbalance among multiple energy storage units.

[0147] Under conditions of insufficient power margin, the actual power supply status of primary, secondary, and tertiary loads was recorded to verify the load classification control process. The simulation results are shown in Table 2.

[0148] Table 2 Comparison of Simulation Results

[0149] During the grid-connected to off-grid switching process, the peak transient current under the comparative control is 2.05 times the rated current, while the peak transient current under the control of this application is 1.24 times the rated current. The lowest PCC voltage under the comparative control is 86.93% of the rated voltage, while the lowest PCC voltage under the control of this application is 94.74% of the rated voltage. Therefore, under the conditions set in this embodiment, adaptive virtual impedance and bidirectional switching control can reduce transient current surges during the switching process and minimize PCC voltage drops.

[0150] Under off-grid load disturbance conditions, the lowest frequency value corresponding to the comparative control is 49.85 Hz, and the maximum frequency deviation is 0.15 Hz; the lowest frequency value corresponding to the control in this application is 49.94 Hz, and the maximum frequency deviation is 0.06 Hz. Therefore, adjusting the virtual inertia according to the system frequency change rate can improve the frequency support capability under off-grid operation and reduce the frequency deviation after a sudden increase in load.

[0151] Regarding SOC balancing among multiple energy storage units, the initial maximum SOC difference among the three groups of energy storage units was 36.00%. In contrast, the control method allocated power according to the rated capacity ratio, and the maximum SOC difference remained at 36.00% at the end of the simulation. The control method in this application adjusted the power allocation of each energy storage unit based on the SOC deviation factor, allowing high-SOC energy storage units to bear relatively larger discharge power and low-SOC energy storage units to bear relatively smaller discharge power. At the end of the simulation, the maximum SOC difference decreased to 32.82%. These results demonstrate that, under the conditions set in this embodiment, adaptive power allocation based on the SOC deviation factor can gradually reduce the SOC difference among multiple energy storage units, reduce the risk of continuous deep discharge of SOC energy storage units, and help delay the lifespan degradation of manganese-based lithium batteries caused by deep over-discharge.

[0152] Regarding critical load assurance, when the system power margin is insufficient, demand response or reduction is first implemented for level 3 interruptible loads. If the total available output is further insufficient, level 2 important loads are then reduced, and priority is given to maintaining power supply to level 1 critical loads. In this embodiment, the power supply satisfaction rate of the level 1 loads controlled by this application is 99.96%.

[0153] As can be seen from the above simulation results, the control method of this application can achieve multi-layer control coordination during grid connection, grid connection to off-grid transition and off-grid load disturbance, and can reduce switching transient impact, improve PCC voltage support capability, reduce frequency deviation and improve the SOC balance among multiple energy storage units. At the same time, when the available output is limited, power balance control is implemented according to the load power supply priority.

[0154] A third objective of this application is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned manganese-based lithium battery energy storage device and off-grid multimodal collaborative control method.

[0155] A fourth objective of this application is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the manganese-based lithium battery energy storage device and an off-grid multimodal collaborative control method.

[0156] The fifth objective of this application is to provide a computer program product that includes computer instructions that instruct a computer to execute the manganese-based lithium battery energy storage device and the off-grid multimodal collaborative control method.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] This application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, readable storage media, optical storage, etc.) containing computer-usable program code.

[0160] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0161] Obviously, the described embodiments are only some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort should fall within the scope of protection of this application.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A multi-modal collaborative control method for a manganese-based lithium battery energy storage device and its off-grid operation, characterized in that, include: A hierarchical multimodal collaborative control architecture is constructed, which includes a system scheduling layer, a coordination control layer, and a local execution layer that are interconnected from top to bottom. The system scheduling layer monitors the electrical parameters of the common connection point of the regional distribution network in real time, determines the operation mode of the regional distribution network according to the electrical parameters and preset judgment rules, and outputs the mode switching command and total power command corresponding to the operation mode. The operation modes include grid-connected mode, islanded mode and grid-connected / off-grid switching transition mode. In the grid-connected mode and the islanded mode, the real-time state of charge of each manganese-based lithium battery energy storage unit is obtained through the coordination control layer. The corresponding state of charge deviation factor is determined according to the real-time state of charge of each manganese-based lithium battery energy storage unit. Combined with the rated capacity and available charge and discharge capability of each manganese-based lithium battery energy storage unit, the active power allocation coefficient of each manganese-based lithium battery energy storage unit is adaptively corrected. The power corresponding to the total power command is allocated according to the active power allocation coefficient to achieve state of charge balance among multiple manganese-based lithium battery energy storage units. When the state of charge of any of the manganese-based lithium battery energy storage units reaches the preset state of charge protection threshold, the charging and discharging power of the manganese-based lithium battery energy storage unit is limited, and the power is redistributed according to the available charging and discharging capabilities of the remaining available manganese-based lithium battery energy storage units. The local execution layer controls the operation of the energy storage converter corresponding to each manganese-based lithium battery energy storage unit according to the mode switching command and power allocation result.

2. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that: The system scheduling layer serves as the global decision-making layer, used to perform power grid status monitoring, operation mode identification, and mode switching command issuance. The coordination control layer serves as an optimization coordination layer, used to perform state of charge monitoring, load power acquisition, power optimization allocation, and load hierarchical management decisions for each manganese-based lithium battery energy storage unit. The local execution layer serves as a real-time execution layer, used to perform closed-loop control, operation mode switching, and real-time acquisition of electrical quantities for the energy storage converters corresponding to each manganese-based lithium battery energy storage unit.

3. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, The step of determining the operating mode of the regional distribution network based on the electrical parameters and preset judgment rules includes: Detect the voltage and frequency of the common connection point; When the voltage and / or frequency of the common connection point deviates from the corresponding rated range and the abnormal state continues for a preset time, it is determined that a fault has occurred in the upstream power grid, and a grid-connected to islanded switching command is output. When the voltage and frequency of the upstream power grid are detected to have returned to the corresponding rated range and have been operating stably for a preset time, it is determined that the upstream power grid has returned to normal and an islanding to grid connection switching command is output.

4. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, In the grid-connected mode, the local execution layer controls each manganese-based lithium battery energy storage unit to perform virtual synchronous generator control, adaptively adjusts the virtual inertia of each manganese-based lithium battery energy storage unit according to the system frequency change rate, and performs grid-connected support control of the manganese-based lithium battery energy storage unit through active-frequency control and reactive-voltage control links. Preferably, the virtual inertia of the i-th manganese-based lithium battery energy storage unit is determined according to the following formula: in, Let be the virtual inertia of the i-th manganese-based lithium battery energy storage unit. As the baseline virtual inertia, This is the adaptive gain coefficient, with a value ranging from 1 to 5. The real-time frequency change rate of the system. The maximum permissible rate of frequency change; Preferably, the active-frequency control link uses a virtual rotor motion equation for active control, and the reactive-voltage control link uses a droop control equation for reactive control. The control parameters in the virtual rotor motion equation include at least the virtual inertia, virtual angular frequency, rated angular frequency, active power reference value, actual output active power, and active damping coefficient. The control parameters in the droop control equation include at least the voltage reference value, rated voltage, reactive voltage droop coefficient, actual output reactive power, and initial reactive power value.

5. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, When performing a smooth handover from grid connection to islanding in the aforementioned grid-connected to islanded handover transition mode, the following are included: Upon receiving the grid-connected to islanded switching command, maintain the current output power and controller status of each energy storage converter to ensure continuous control. The main energy storage unit is determined based on the state of charge of each manganese-based lithium battery energy storage unit, and the V / f main control circuit of the main energy storage unit is put into a pre-start state before the grid connection switch of the common connection point is disconnected. After disconnecting the grid connection switch of the common connection point, control the main energy storage unit to establish the voltage and frequency reference of the islanded system, and control the remaining manganese-based lithium battery energy storage units to adopt the droop-follow mode; An adaptive virtual impedance is introduced during the switching process to suppress transient current surges; When the voltage deviation and frequency deviation of the islanded system are both within the corresponding allowable range and remain stable for a preset time, it is determined that the grid-connected to islanded switching is complete and the transient impedance control mode is exited. Preferably, determining the main energy storage unit based on the state of charge of each of the manganese-based lithium battery energy storage units includes: The manganese-based lithium battery energy storage unit with the highest real-time state of charge is determined as the main energy storage unit; When the state of charge difference among multiple manganese-based lithium battery energy storage units is within a preset range, the manganese-based lithium battery energy storage unit with the largest rated capacity is determined as the main energy storage unit. Preferably, the adaptive virtual impedance includes a virtual resistance component and a virtual reactance component that decay over time; The decay time constant of the virtual resistance component is smaller than the decay time constant of the virtual reactance component; The virtual resistance component and the virtual reactance component are both limited and adjusted according to the relationship between the real-time output current of the corresponding energy storage converter and the transient overcurrent limit value. The time is the time calculated after the adaptive virtual impedance is put into operation, and the virtual resistance component and the virtual reactance component are set to zero after the grid-connected to islanded switching is completed. Preferably, when performing a smooth handover from islanded to grid-connected mode in the grid-connected handover transition mode, it includes: Upon receiving the islanding-to-grid switching command, pre-synchronization phase-locked control is initiated, and the voltage phase angle, voltage amplitude, and frequency of the grid side and the islanding side are collected in real time. The output of the main energy storage unit is adjusted according to the synchronization deviation between the grid side and the island side. When the synchronization deviation meets the preset synchronization accuracy requirement, the grid connection switch of the common connection point is closed. Through a power ramp transition, each of the manganese-based lithium battery energy storage units is switched from off-grid control mode to grid-connected virtual synchronous generator control mode; Preferably, a proportional-integral synchronous regulation component is superimposed in the V / f control loop of the main energy storage unit, wherein: The phase angle synchronization adjustment is proportional-integral based on the deviation between the voltage phase angle on the grid side and the voltage phase angle on the island side; The voltage amplitude synchronization adjustment is proportional-integral based on the deviation between the voltage amplitude on the grid side and the voltage amplitude on the island side.

6. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, The state-of-charge deviation factor corresponding to the i-th manganese-based lithium battery energy storage unit is determined according to the following formula: The capacity-weighted average state of charge of the plurality of manganese-based lithium battery energy storage units is determined according to the following formula: In the formula, This represents the real-time state of charge of the i-th manganese-based lithium battery energy storage unit. The state of charge (SOC) is the capacity-weighted average of the multiple manganese-based lithium battery energy storage units, weighted by their rated capacity. and These are the upper and lower limits of the permissible state of charge, respectively. Let be the rated capacity of the i-th manganese-based lithium battery energy storage unit, and n be the number of manganese-based lithium battery energy storage units. Preferably, the active power allocation coefficient of each manganese-based lithium battery energy storage unit is determined based on the benchmark active power allocation coefficient, the rated capacity of the corresponding manganese-based lithium battery energy storage unit, the total rated capacity of the multiple manganese-based lithium battery energy storage units, the corresponding state of charge deviation factor, and the state of charge balance adjustment coefficient. In addition, opposite state of charge deviation adjustment relationships are adopted for charging and discharging conditions, so that the energy storage unit with a relatively low state of charge obtains a relatively large charging power allocation weight during the charging process, and the energy storage unit with a relatively high state of charge obtains a relatively large discharging power allocation weight during the discharging process.

7. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, When the real-time state of charge of any of the manganese-based lithium battery energy storage units is lower than the preset protection lower limit, the manganese-based lithium battery energy storage unit is controlled to stop discharging, and the remaining available manganese-based lithium battery energy storage units and distributed power sources in the regional power distribution network work together to make up for the power gap caused by the manganese-based lithium battery energy storage unit stopping discharging.

8. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, The loads of the regional distribution network are divided according to power supply priority as follows: Level 1 load, which refers to the load on personal safety and critical infrastructure; Secondary loads, which are important industrial and commercial loads; Level 3 load, wherein the Level 3 load is an interruptible load; The power supply priority of the primary load is higher than that of the secondary load, and the power supply priority of the secondary load is higher than that of the tertiary load. Preferably, the power supply guarantee operating condition is determined based on the total available output of the energy storage system and the distributed power source, and the power supply guarantee operating condition includes: Under full-load protection conditions, the power supply to the primary load, the secondary load, and the tertiary load is maintained. Under restricted protection conditions, the power supply to the primary load and the secondary load shall be maintained. In critical protection conditions, only the primary load is kept powered. The system switches between the full-load protection condition, the limited protection condition, and the critical protection condition based on the total available output of the energy storage system and the distributed power source. Preferably, the system power margin index is determined according to the following formula: in, The total available output power of the energy storage system. This refers to the total output of distributed power sources in the aforementioned regional power distribution network. This represents the total load power of the area. When the system power margin index is lower than the first preset threshold, the demand response of the third-level load is initiated; When the system power margin index is lower than the second preset threshold, and the sum of the total available output power of the energy storage system and the total output of the distributed power source is insufficient to meet the load demand, the third-level load and the second-level load are reduced in order of power supply priority from low to high until the system power balance is restored. When the system power margin index recovers to above the third preset threshold and the total available output meets the load recovery conditions, the reduced loads are restored in descending order of power supply priority. Preferably, when the capacity-weighted average state of charge of multiple manganese-based lithium battery energy storage units is lower than a preset critical value, and the sum of the total output of the distributed power source and the total available output power of the energy storage system is insufficient to meet all load demands, the lower priority loads are reduced according to the power supply priority. When the sum of the total output of the distributed power source and the total available output power of the energy storage system is only able to meet the power supply demand of the primary load, only the primary load is supplied with power, and an emergency alarm signal is sent.

9. The on-grid and off-grid multi-modal collaborative control method for manganese-based lithium battery energy storage device according to claim 1, characterized in that, Under the constraint of balanced state of charge of multiple manganese-based lithium battery energy storage units, power optimization allocation is performed with the goal of minimizing the total charge and discharge loss of the energy storage system. The charge and discharge loss of the i-th manganese-based lithium battery energy storage unit is determined by the following formula: in, Let be the charge / discharge loss of the i-th manganese-based lithium battery energy storage unit. Let i be the output power of the i-th manganese-based lithium battery energy storage unit. , and These are the switching loss coefficient, conduction loss coefficient, and no-load fixed loss coefficient of the energy storage converter corresponding to the i-th manganese-based lithium battery energy storage unit, respectively. by To optimize the objective, the following constraints are set: in, This represents the maximum permissible deviation from the state of charge. and These are the lower and upper power limits of the i-th manganese-based lithium battery energy storage unit, respectively; The optimization problem formed by the optimization objective and the constraints is solved by the Lagrange multiplier method to obtain the target output allocation results of each manganese-based lithium battery energy storage unit.

10. A multi-modal collaborative control system for a manganese-based lithium battery energy storage device and an off-grid system, characterized in that, include: The hierarchical control architecture module is used to realize the communication and instruction loop between the system scheduling layer, coordination control layer and local execution layer; The mode discrimination module is deployed in the system scheduling layer and is used to monitor the power grid status of the regional distribution network, discriminate the operating mode, and issue mode switching instructions. The grid-connected control module, deployed in the local execution layer, is used to perform grid-connected support control and cooperate with the coordination control layer to complete power distribution under grid-connected operating conditions. The smooth switching module, deployed in the local execution layer, is used to perform bidirectional smooth switching control from grid-connected to islanded and from islanded to grid-connected. A state-of-charge (SOC) equalization control module, deployed in the coordination control layer, is used to adaptively adjust the active power allocation coefficient according to the SOC deviation factor of each manganese-based lithium battery energy storage unit to achieve SOC equalization among multiple manganese-based lithium battery energy storage units; and to implement power limiting and redistribute power to the remaining available units when the energy storage unit reaches the SOC protection condition. The load classification management module, deployed in the coordination control layer, is used to perform multi-condition adaptive control and dynamic power balance control based on the total available output of the energy storage system and distributed power sources.

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