Energy storage power station layered cooperative control device and method of use thereof

Abstract

The application discloses a layered cooperative control device of an energy storage power station and a use method thereof, and relates to the technical field of power station control devices. The layered cooperative control device of the energy storage power station comprises an energy management system, an SOC cooperative balancing controller, at least one energy storage converter and at least one battery management system. The SOC cooperative balancing controller is bidirectionally connected with the energy management system and the energy storage converter in communication, is used for receiving a state of charge parameter reported by the battery management system through the energy storage converter, generating a dynamic partition strategy and a power distribution suggestion and uploading the dynamic partition strategy and the power distribution suggestion to the energy management system, and simultaneously issuing a power correction instruction to the energy storage converter. The device realizes global redistribution of a power instruction, realizes active decision-making of a middle-layer controller and cross-layer negotiation, and improves state of charge balancing efficiency and system operation reliability.

Description

Technical Field

[0001] This invention relates to the field of power plant control device technology, specifically to a hierarchical collaborative control device for energy storage power plants and its usage method. Background Technology

[0002] Energy storage power stations are key infrastructure for achieving peak shaving and valley filling, frequency and voltage regulation, and renewable energy consumption in the power grid. Their control architecture typically adopts a hierarchical structure, mainly comprising three core components: an Energy Management System (EMS), a Power Processing System (PCS), and a Battery Management System (BMS). The EMS acts as the command center for the power station's operation, responsible for receiving grid dispatch instructions and generating power commands for the entire station. The PCS executes the power commands issued by the EMS, achieving bidirectional AC / DC conversion. The BMS monitors parameters such as voltage, current, and state of charge of the battery clusters in real time and feeds these parameters back to the EMS and PCS, forming a closed-loop control. Under this architecture, the EMS and PCS typically communicate via communication protocols such as IEC 61850. Data interaction is achieved through information sharing between the PCS and BMS via the CAN bus, enabling basic operation control of the energy storage power station. Regarding the issue of state-of-charge (SOC) balancing in parallel operation of multiple battery clusters in an energy storage system, existing technologies disclose various power allocation schemes based on droop control and SOC partitioning. By adopting a hierarchical control architecture, the average SOC of each battery cluster is obtained at the communication layer using a consensus algorithm. At the droop control layer, the droop coefficient is dynamically adjusted based on the current SOC of each unit. Research indicates that some schemes introduce SOC hierarchical control technology, dividing the energy storage batteries into different levels based on different SOC thresholds and setting corresponding charging and discharging strategies for each level to achieve adaptive regulation of the SOC.

[0003] The above-mentioned hierarchical control architecture has encountered the following technical problems during actual operation:

[0004] First, in the existing layered architecture, the EMS undertakes all the functions of global scheduling decision-making, while the PCS and BMS only serve as instruction execution terminals and data acquisition terminals. The middle layer lacks independent decision-making and negotiation capabilities. When the SOC of some battery clusters deviates from the normal range, the PCS can adjust the droop coefficient based on the local SOC, but the adjustment result cannot be passed up to the EMS. As a result, the EMS still allocates power according to the original weight in subsequent power scheduling. The SOC difference is amplified step by step in multiple scheduling cycles, and may even trigger a chain of derating accidents.

[0005] Second, the SOC zoning control strategy is usually only used for local control parameter adjustment, that is, modifying the droop coefficient of PCS according to the zoning result. However, the zoning label is not used to participate in the global power scheduling decision of EMS. When the local state of charge reaches the boundary of the area that urgently needs charging or discharging, this type of battery cluster cannot obtain the priority response of EMS at the power scheduling level, and the balancing efficiency is limited.

[0006] Third, when any PCS triggers power limiting due to SOC anomaly, the reduced power demand of the existing system's limited units is passively taken over by other PCS, which can easily lead to SOC imbalance and a chain reaction of temperature rise in the remaining units, affecting the overall operational safety and economic benefits of the energy storage power station. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a hierarchical collaborative control device for energy storage power stations and its usage method, thereby resolving the problems mentioned in the background section.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a hierarchical collaborative control device for an energy storage power station, comprising:

[0009] Energy management system;

[0010] The SOC collaborative equalization controller is bidirectionally connected to the energy management system.

[0011] At least one energy storage converter, and each energy storage converter is bidirectionally connected to the SOC collaborative equalization controller;

[0012] At least one battery management system, each battery management system is installed on a corresponding battery cluster and is bidirectionally connected to the corresponding energy storage converter;

[0013] The SOC collaborative equalization controller is used to receive the state of charge parameters reported by each battery management system through the energy storage converter, generate dynamic zoning strategies and power allocation suggestions and upload them to the energy management system, and at the same time issue power correction commands to the energy storage converter.

[0014] Preferably, the SOC collaborative equalization controller includes:

[0015] The data acquisition module is used to receive the state of charge values ​​of each battery cluster;

[0016] A dynamic partitioning calculation module, connected to the data acquisition module, is used to divide each battery cluster into a region that urgently needs charging, a normal adjustment region, and a region that urgently needs discharging.

[0017] The negotiation decision module, connected to the dynamic partitioning calculation module and the energy management system, is used to generate priority tags for the battery clusters in the boundary area and upload them to the energy management system.

[0018] An adaptive correction module, connected to the dynamic partitioning calculation module and the energy storage converter, is used to send power correction coefficients to the energy storage converters corresponding to the battery clusters in the normal adjustment zone.

[0019] Preferably, the negotiation decision module includes:

[0020] The tag generation unit is used to generate first priority tags for battery clusters in areas requiring charging and second priority tags for battery clusters in areas requiring discharging.

[0021] The power redistribution negotiation unit, connected to the tag generation unit and the energy management system, is used to upload the priority tag to the energy management system and receive the redistributed power scheduling instruction returned by the energy management system.

[0022] Preferably, the adaptive correction module includes:

[0023] The droop coefficient calculation unit is used to calculate the adaptive droop coefficient correction amount according to the state of charge of each battery cluster in the partitioned area;

[0024] The instruction issuing unit is connected to the droop coefficient calculation unit and the energy storage converter, and is used to issue the correction amount to the corresponding energy storage converter.

[0025] Preferably, it also includes a power protection feedback loop, which is composed of an energy storage converter, a SOC collaborative equalization controller and an energy management system connected in series.

[0026] When any energy storage converter triggers a power limit, it is reported to the energy management system via the SOC collaborative equalization controller. The energy management system then reallocates power commands, transferring the power demand of the limited battery cluster to other battery clusters.

[0027] Preferably, the SOC collaborative equalization controller and the energy storage converter communicate via a real-time industrial Ethernet bus with a communication cycle of no more than 10 milliseconds; the SOC collaborative equalization controller and the energy management system communicate via the IEC61850 protocol.

[0028] Preferably, the dynamic partitioning operation module adopts an improved diffusion consensus algorithm that introduces gradient terms of state variables, so that the state of charge value of each battery cluster approaches the global average value at a quadratic convergence rate, and the data update cycle is no more than 10 seconds.

[0029] Preferably, the SOC collaborative balancing controller further includes a balancing trend analysis module, which is used to calculate the state of charge balance of the entire station. When the balancing degree continuously exceeds a preset threshold and the duration exceeds a preset time, a mode switching request is sent to the energy management system.

[0030] Preferably, the balance is defined as the difference between the maximum and minimum state of charge of each battery cluster in the entire station, the threshold is set to 12%~18%, and the preset duration is 2~5 minutes.

[0031] This invention also discloses a method for using a hierarchical collaborative control device for an energy storage power station, which, based on the aforementioned hierarchical collaborative control device for an energy storage power station, includes:

[0032] Step S1: The battery management system collects the state of charge value and reports it to the SOC collaborative equalization controller.

[0033] Step S2: The SOC collaborative equalization controller divides the region into a region that urgently needs charging, a normal adjustment region, and a region that urgently needs discharging.

[0034] Step S3: The SOC collaborative equalization controller generates power adjustment priority tags for the battery clusters in the boundary area and uploads them to the energy management system.

[0035] Step S4: The energy management system combines the priority tag to reallocate power instructions and issues them.

[0036] Step S5: The SOC collaborative equalization controller sends a power correction coefficient to the battery cluster in the normal adjustment zone and forwards the power command to the energy storage converter.

[0037] In step S6, the energy storage converter performs power output and continuously provides feedback on the actual output power and remaining regulation margin.

[0038] The technical effects and advantages of this invention are as follows:

[0039] 1. The hierarchical collaborative control device for this energy storage power station adds a State of Charge (SOC) collaborative equalization controller and establishes bidirectional communication connections with the energy management system and at least one energy storage converter. The SOC collaborative equalization controller receives the state of charge parameters reported by each battery management system through the energy storage converter, generates dynamic zoning strategies and power allocation suggestions, and uploads them to the energy management system. At the same time, it issues power correction commands to the energy storage converter, thus solving the technical problem that the SOC difference is amplified step by step due to the one-way communication between the EMS and PCS in the existing hierarchical architecture.

[0040] 2. The hierarchical collaborative control device for this energy storage power station, in the negotiation decision module, the tag generation unit generates priority tags for the battery clusters in the boundary area and uploads them to the energy management system, and in the adaptive correction module, the droop coefficient calculation unit independently calculates the droop coefficient correction amount for the battery clusters in the normal regulation area and sends it to the energy storage converter. This realizes dual-path differentiated collaborative control between the battery clusters in the boundary area and the battery clusters in the normal regulation area, and solves the technical problem that the SOC partitioning results can only be used for local parameter adjustment and cannot optimize global power scheduling.

[0041] 3. The hierarchical collaborative control device of this energy storage power station consists of a power protection feedback loop composed of an energy storage converter, a SOC collaborative equalization controller, and an energy management system connected in series. When any energy storage converter triggers a power limit, it reports to the energy management system through the SOC collaborative equalization controller. The energy management system redistributes the power command and transfers the power demand of the limited battery cluster to other battery clusters, thus solving the technical problem that the power limit at the bottom layer cannot trigger the global power command redistribution. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of the overall architecture of the present invention;

[0044] Figure 2 This is a diagram of the internal modules of the SOC collaborative equalization controller of the present invention;

[0045] Figure 3 This is a flowchart of the negotiation and decision-making module of the present invention;

[0046] Figure 4 This is a flowchart of the adaptive correction module of the present invention;

[0047] Figure 5 This is a flowchart of the method of using the present invention.

[0048] In the diagram: 100, Energy Management System; 200, SOC Collaborative Equalization Controller; 201, Data Acquisition Module; 202, Dynamic Partition Calculation Module; 203, Negotiation Decision Module; 204, Adaptive Correction Module; 205, Equalization Trend Analysis Module; 300, Energy Storage Converter; 400, Battery Management System. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] This embodiment discloses a hierarchical collaborative control device for an energy storage power station, according to the attached... Figures 1 to 5As shown, it includes an energy management system 100, a SOC collaborative equalization controller 200, at least one energy storage converter 300, and at least one battery management system 400.

[0051] The energy management system 100 is configured at the dispatch center station level to receive grid dispatch instructions, generate and send station-wide power instructions to lower levels. The SOC collaborative balancing controller 200 is configured at the station-domain coordination level and establishes bidirectional communication connections with the energy management system 100 and at least one energy storage converter 300 via a communication bus. Each energy storage converter 300 is configured at the unit execution level, electrically connected to one or more battery clusters, and bidirectionally communicates with the SOC collaborative balancing controller 200. Each battery management system 400 is configured at the battery slave control level, set on the corresponding battery cluster, and bidirectionally communicates with the corresponding energy storage converter 300.

[0052] Furthermore, the SOC collaborative balancing controller 200 is used to receive the state of charge (SOC) parameters reported by each battery management system 400 via the energy storage converter 300, generate a dynamic zoning strategy and power allocation suggestions based on the SOC parameters and upload them to the energy management system 100, and simultaneously issue power correction commands to the energy storage converter 300. The SOC collaborative balancing controller 200 specifically includes a data acquisition module 201, a dynamic zoning calculation module 202, a negotiation decision module 203 and an adaptive correction module 204. The data acquisition module 201 is communicatively connected to at least one energy storage converter 300 and is used to receive the SOC values, health values ​​and internal resistance information of each battery cluster uploaded by at least one energy storage converter 300. The dynamic zoning calculation module 202 is connected to the data acquisition module 201 and is used to perform distributed calculations on the SOC values ​​of each battery cluster based on the diffusion consensus algorithm, generate the SOC matrix of each battery cluster at the current moment, and divide each battery cluster into a charging zone, a normal adjustment zone and a discharging zone according to a preset SOC threshold.

[0053] The negotiation decision module 203 is connected to the dynamic partitioning calculation module 202 and the energy management system 100 respectively. It is used to generate priority tags for battery clusters located in the boundary areas of the charging zone and the discharging zone, and upload the power allocation suggestions with priority tags to the energy management system 100 so that the energy management system 100 can adjust the power allocation weight of each battery cluster in the whole station power scheduling. The adaptive correction module 204 is connected to the dynamic partitioning calculation module 202 and at least one energy storage converter 300 respectively. It is used to generate power correction coefficients according to the state of charge of each battery cluster in the partition area, and send the power correction coefficients to the corresponding energy storage converter 300.

[0054] Furthermore, the negotiation decision module 203 includes a tag generation unit and a power redistribution negotiation unit. The tag generation unit is used to generate a first priority tag for battery clusters located in areas requiring urgent charging, indicating that such battery clusters should prioritize increasing power absorption during charging and reducing power output during discharging; and to generate a second priority tag for battery clusters located in areas requiring urgent discharging, indicating that such battery clusters should prioritize increasing power output during discharging and reducing power absorption during charging. The power redistribution negotiation unit is connected to the tag generation unit and the energy management system 100, and is used to upload the first priority tag and the second priority tag to the energy management system 100 in the form of a power allocation suggestion data packet, and to receive the redistributed power scheduling instruction returned by the energy management system 100.

[0055] Furthermore, the adaptive correction module 204 includes a droop coefficient calculation unit and a command issuing unit. The droop coefficient calculation unit is used to calculate the adaptive droop coefficient correction amount according to the state of charge partitioning area where each battery cluster is located, based on a preset linear or nonlinear function. Specifically, the droop coefficient correction amount of the battery cluster located in the charging zone increases as the state of charge value decreases under charging conditions, while the droop coefficient correction amount of the battery cluster located in the discharging zone increases as the state of charge value increases under discharging conditions. The command issuing unit is connected to the droop coefficient calculation unit and at least one energy storage converter 300, and is used to issue the adaptive droop coefficient correction amount to the corresponding energy storage converter 300 in the form of a pulse width modulation signal or a bus data packet.

[0056] Specifically disclosed, the device also includes a power protection feedback loop, which is composed of an energy storage converter 300, a SOC collaborative equalization controller 200, and an energy management system 100 connected in series. When any energy storage converter 300 detects that the state of charge value of the connected battery cluster exceeds the preset protection threshold and triggers power limiting, the energy storage converter 300 actively reports the power limiting event information to the SOC collaborative equalization controller 200. After receiving the power limiting event information, the SOC collaborative equalization controller 200 forwards the power limiting event information to the energy management system 100. Based on the received power limiting event information, the energy management system 100 recalculates the power allocation matrix of the entire station in the next scheduling cycle and transfers the power demand corresponding to the limited battery cluster to other battery clusters with balanced state of charge.

[0057] Specifically disclosed, the SOC collaborative equalization controller 200 and at least one energy storage converter 300 are connected via a real-time industrial Ethernet bus with a communication cycle of no more than 10 milliseconds. The SOC collaborative equalization controller 200 and the energy management system 100 are connected via the IEC61850 standard communication protocol. The diffusion consensus algorithm used in the dynamic partitioning calculation module 202 is an improved diffusion consensus algorithm. This algorithm introduces a state variable gradient term on the basis of the standard diffusion consensus algorithm, so that the state of charge value of each battery cluster approaches the global average value with a quadratic convergence rate during the distributed iteration process. The state of charge data update cycle of the dynamic partitioning calculation module 202 is no more than 10 seconds, which is used to refresh the state of charge matrix at regular intervals.

[0058] It is worth emphasizing that the SOC collaborative balancing controller 200 also includes a balancing trend analysis module 205. The balancing trend analysis module 205 is connected to the dynamic partitioning calculation module 202 and is used to calculate the overall station's state of charge balance based on the state of charge matrix of multiple consecutive sampling periods. When the balance continuously exceeds the preset balance threshold and the duration exceeds the preset duration, a mode switching request is generated and uploaded to the energy management system 100. The mode switching request is used to instruct the energy management system 100 to switch from the economic dispatch mode to the state of charge balance priority mode. The balance is defined as the difference between the maximum and minimum state of charge of each battery cluster in the entire station. The balance threshold is set to any value within the range of 12% to 18%, preferably 15% in this embodiment. The preset duration is set to any value within the range of 2 minutes to 5 minutes, preferably 3 minutes in this embodiment.

[0059] It is particularly important to emphasize that the bidirectional communication connection between the SOC collaborative equalization controller 200 and the energy storage converter 300 adopts a hybrid communication mechanism that combines master-slave polling with active reporting: Under steady-state conditions, the SOC collaborative equalization controller 200 polls the status information of each energy storage converter 300 sequentially at a period of no more than 10 milliseconds; when an electrical disturbance or a sudden change in battery status is detected, the energy storage converter 300 can actively send an interrupt-type data packet to the SOC collaborative equalization controller 200 within the next 5-millisecond time window without waiting for the polling time slot.

[0060] The working process of this device will be described in detail below with reference to specific embodiments.

[0061] Example 1: This example takes an energy storage power station operating under steady-state charging and discharging conditions as an example, combined with the attached... Figure 1 To be continued Figure 3 The workflow is explained in detail below:

[0062] Step S1: Each battery management system 400 collects the state of charge (SOC) value of its battery clusters in real time at a sampling frequency of no less than once per second, and reports the collected SOC value to the data acquisition module 201 of the SOC collaborative equalization controller 200 via the corresponding energy storage converter 300. The reported data packet contains the battery cluster identifier, timestamp, and SOC value.

[0063] Step S2: The data acquisition module 201 sends the received state of charge (SOC) values ​​of each battery cluster to the dynamic partitioning calculation module 202. The dynamic partitioning calculation module 202 uses an improved diffusion consensus algorithm that introduces gradient terms of state variables to perform distributed iterative calculations on the SOC values ​​of each battery cluster, generating the SOC matrix at the current moment. Subsequently, the dynamic partitioning calculation module 202 dynamically divides each battery cluster into an urgent charging zone, a normal adjustment zone, and an urgent discharging zone according to preset SOC thresholds: urgently needed charging zone SOC < 20%, normal adjustment zone 20% ≤ SOC ≤ 80%, and urgently needed discharging zone SOC > 80%. In this embodiment, the SOC values ​​of most battery clusters are distributed between 45% and 65%, all falling into the normal adjustment zone.

[0064] Step S3: The negotiation decision module 203 receives the partitioning results from the dynamic partitioning calculation module 202. Since there are no battery clusters in the boundary areas that urgently need charging or discharging in this embodiment, the negotiation decision module 203 does not generate priority tags or upload power allocation suggestions to the energy management system 100.

[0065] Step S4: The droop coefficient calculation unit of the adaptive correction module 204 calculates the adaptive droop coefficient correction amount according to the normal adjustment zone of each battery cluster and a preset linear function. Since the state of charge values ​​of each battery cluster are close, the calculated droop coefficient correction amounts are close to the reference values. The instruction issuing unit sends the calculated correction amount to each corresponding energy storage converter 300 in the form of a bus data packet.

[0066] Step S5: The energy management system 100 generates a total station power command based on the external power grid dispatch command. In this embodiment, it is a charging command with a total power of 10MW. The total station power command is then sent to the SOC collaborative equalization controller 200, which forwards the total station power command to each energy storage converter 300.

[0067] Step S6: Each energy storage converter 300 executes power output using a droop control algorithm based on the received total station power command and adaptive droop coefficient correction. During execution, each energy storage converter 300 continuously feeds back the actual output power value and remaining regulation margin to the SOC collaborative equalization controller 200 to form a closed-loop regulation. The equalization trend analysis module 205 continuously monitors the total station charge state balance. In this embodiment, the balance is 6%, which is lower than the preset threshold of 15%, so no mode switching request is triggered.

[0068] Example 2: This example uses a scenario where some battery clusters have excessively low SOC, triggering power redistribution. It is combined with the attached... Figure 1 To be continued Figure 5 The workflow is explained in detail below:

[0069] Step S1: The battery management system 400 collects and reports the state of charge (SOC) values ​​of the battery clusters 401 under its jurisdiction in real time. In this embodiment, the energy storage power station contains a total of 10 battery clusters, of which the SOC value of battery cluster A is 12%, the SOC value of battery cluster B is 18%, and the SOC values ​​of the remaining 8 battery clusters 401 are distributed between 45% and 55%.

[0070] Step S2: The dynamic partitioning calculation module 202 partitions the battery clusters according to the preset thresholds: the battery cluster ASOC=12% is classified into the urgent charging zone, the battery cluster BSOC=18% is classified into the boundary of the urgent charging zone, and the remaining 8 battery clusters 401 are classified into the normal adjustment zone because they are close to the 20% threshold.

[0071] Step S3: The tag generation unit of the negotiation decision module 203 generates first priority tags for battery cluster A and battery cluster B. The priority level is level 3 for battery cluster A and level 1 for battery cluster B. The higher the level, the higher the charging urgency. The power redistribution negotiation unit uploads the power allocation suggestion data packet with priority tags to the energy management system 100, suggesting that the power absorption of battery cluster A and battery cluster B should be increased in the charging scheduling.

[0072] Step S4: The energy management system 100 receives the power allocation suggestion data packet and, in conjunction with the external power grid dispatch command (in this embodiment, a charging command with a total power of 5MW), recalculates the power allocation weight of each battery cluster 401: the allocation weight of battery cluster A is increased from the base value of 0.1 to 0.25, the allocation weight of battery cluster B is increased from the base value of 0.1 to 0.15, and the allocation weight of the remaining 8 battery clusters is reduced accordingly. An adjusted power command for the entire station is generated and sent to the SOC collaborative equalization controller 200.

[0073] Step S5: The droop coefficient calculation unit of the adaptive correction module 204 calculates the adaptive droop coefficient correction amount according to the partition area where each battery cluster is located: For the 8 battery clusters located in the normal adjustment zone, the adaptive droop coefficient correction amount is calculated; For battery clusters A and B located in the urgent charging zone, the droop coefficient calculation unit calculates the droop coefficient correction amount under their charging conditions, which increases as the SOC value decreases. The instruction issuing unit issues the correction amount to each energy storage converter 300. At the same time, the SOC collaborative equalization controller 200 forwards the station power instruction issued by the energy management system 100 to each energy storage converter 300.

[0074] Step S6: Each energy storage converter 300 executes power output according to the received power command and adaptive droop coefficient correction. The energy storage converter 300 corresponding to battery cluster A charges at a power of 1.25MW, with the original baseline allocation being 0.5MW. The energy storage converter 300 corresponding to battery cluster B charges at a power of 0.75MW. The energy storage converters 300 corresponding to the remaining 8 battery clusters charge at an average power of 0.375MW. During the execution process, each energy storage converter 300 continuously feeds back the actual output power value and remaining regulation margin to the SOC collaborative equalization controller 200.

[0075] Step S7: After 30 minutes of operation, the equilibrium trend analysis module 205 detects that the overall state of charge balance of the station has dropped from the initial 43% to 18%, exceeding the preset threshold of 15% and lasting for more than 3 minutes. The equilibrium trend analysis module 205 generates a mode switching request and uploads it to the energy management system 100. After receiving the mode switching request, the energy management system 100 switches from the economic dispatch mode to the state of charge balance priority mode, and further adjusts the power allocation strategy of each battery cluster until the balance drops back to below 15%.

[0076] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A hierarchical collaborative control device for an energy storage power station, characterized in that, include: Energy Management System (100); The SOC collaborative balancing controller (200) is bidirectionally connected to the energy management system (100); At least one energy storage converter (300) is provided, and each energy storage converter (300) is bidirectionally connected to the SOC collaborative equalization controller (200); At least one battery management system (400) is provided, each battery management system (400) is respectively set on the corresponding battery cluster and bidirectionally communicated with the corresponding energy storage converter (300); The SOC collaborative equalization controller (200) is used to receive the state of charge parameters reported by each battery management system (400) through the energy storage converter (300), generate dynamic partitioning strategies and power allocation suggestions and upload them to the energy management system (100), and at the same time issue power correction instructions to the energy storage converter (300).

2. The hierarchical collaborative control device for an energy storage power station according to claim 1, characterized in that, The SOC collaborative equalization controller (200) includes: The data acquisition module (201) is used to receive the state of charge values ​​of each battery cluster; The dynamic partitioning calculation module (202), connected to the data acquisition module (201), is used to divide each battery cluster into a charging zone, a normal adjustment zone, and a discharging zone. The negotiation decision module (203) is connected to the dynamic partitioning calculation module (202) and the energy management system (100) and is used to generate priority tags for the battery clusters in the boundary area and upload them to the energy management system (100). The adaptive correction module (204) is connected to the dynamic partitioning calculation module (202) and the energy storage converter (300) and is used to send power correction coefficients to the energy storage converter (300) corresponding to the battery cluster in the normal adjustment zone.

3. The hierarchical collaborative control device for an energy storage power station according to claim 2, characterized in that, The negotiation decision-making module (203) includes: The tag generation unit is used to generate first priority tags for battery clusters in areas requiring charging and second priority tags for battery clusters in areas requiring discharging. The power redistribution negotiation unit is connected to the tag generation unit and the energy management system (100) and is used to upload the priority tag to the energy management system (100) and receive the redistributed power scheduling instruction returned by the energy management system (100).

4. The hierarchical collaborative control device for an energy storage power station according to claim 2, characterized in that, The adaptive correction module (204) includes: The droop coefficient calculation unit is used to calculate the adaptive droop coefficient correction amount according to the state of charge of each battery cluster in the partitioned area; The instruction issuing unit is connected to the droop coefficient calculation unit and the energy storage converter (300) and is used to issue the correction amount to the corresponding energy storage converter.

5. The hierarchical collaborative control device for an energy storage power station according to claim 1, characterized in that, It also includes a power protection feedback loop, which is composed of an energy storage converter (300), a SOC collaborative equalization controller (200), and an energy management system (100) connected in series. When any energy storage converter triggers a power limit, it is reported sequentially to the energy management system (100) via the SOC collaborative equalization controller (200). The energy management system (100) then redistributes the power command, transferring the power demand of the limited battery cluster to other battery clusters.

6. The hierarchical collaborative control device for an energy storage power station according to claim 1, characterized in that, The SOC collaborative equalization controller (200) and the energy storage converter (300) communicate via a real-time industrial Ethernet bus with a communication cycle of no more than 10 milliseconds; the SOC collaborative equalization controller (200) and the energy management system (100) communicate via the IEC61850 protocol.

7. The hierarchical collaborative control device for an energy storage power station according to claim 2, characterized in that, The dynamic partitioning operation module (202) adopts an improved diffusion consistency algorithm that introduces gradient terms of state variables, so that the state of charge value of each battery cluster approaches the global average value at a quadratic convergence rate, and the data update cycle is no more than 10 seconds.

8. The hierarchical collaborative control device for an energy storage power station according to claim 1, characterized in that, The SOC collaborative balancing controller (200) also includes a balancing trend analysis module (205) for calculating the overall station charge state balance. When the balance exceeds a preset threshold continuously and the duration exceeds a preset time, a mode switching request is sent to the energy management system (100).

9. A hierarchical collaborative control device for an energy storage power station according to claim 8, characterized in that, The equalization degree is defined as the difference between the maximum and minimum state of charge of each battery cluster in the entire station, the threshold is set to 12%~18%, and the preset duration is 2~5 minutes.

10. A method of using a hierarchical collaborative control device for an energy storage power station, based on the hierarchical collaborative control device for an energy storage power station as described in any one of claims 1 to 9, characterized in that, include: Step S1: The battery management system (400) collects the state of charge value and reports it to the SOC collaborative equalization controller (200). Step S2, the SOC collaborative equalization controller (200) divides the area into a charging zone, a normal adjustment zone, and a discharging zone; Step S3, the SOC collaborative equalization controller (200) generates power adjustment priority tags for the battery clusters in the boundary area and uploads them to the energy management system (100). Step S4: The energy management system (100) combines the priority tag to reallocate power instructions and issues them; In step S5, the SOC collaborative equalization controller (200) sends a power correction coefficient to the battery cluster in the normal regulation zone and forwards the power command to the energy storage converter (300). In step S6, the energy storage converter (300) performs power output and continuously feeds back the actual output power and remaining regulation margin.

Images