Network construction type energy storage system cooperative control method, apparatus and device, and storage medium

Abstract

The invention belongs to the technical field of energy storage control, and discloses a network construction type energy storage system cooperative control method, device and equipment and a storage medium. The method comprises the following steps: collecting real-time frequency and real-time voltage of a power grid; calculating a frequency deviation and a voltage deviation based on the rated frequency and the rated voltage, and determining a corresponding control scene according to the frequency deviation and the voltage deviation; calling a preset cooperative control strategy library based on the divided control scenes to determine a control strategy; loading virtual inertia parameters according to a control strategy to calculate an active power added value and a reactive power added value of each energy storage unit; and superposing the active power additional value and the reactive power additional value with the local power response value to generate a target power instruction, and issuing the target power instruction to the corresponding energy storage converter for cooperative control, so that dynamic selection of a control scene can be performed based on deviation, a control strategy is more targeted, and the control efficiency is improved. And meanwhile, the control strategy is real-time, so that the timeliness of cooperative control is ensured.

Description

Technical Field

[0001] This invention relates to the field of energy storage control technology, and in particular to a collaborative control method, device, equipment and storage medium for a grid-type energy storage system. Background Technology

[0002] As the global energy structure transitions towards a low-carbon model, the penetration rate of new energy power generation technologies such as wind and solar power continues to increase. However, new energy power generation is intermittent, volatile, and random. Large-scale grid connection leads to a decrease in grid inertia and a weakening of voltage support capacity. The regulation capacity of traditional synchronous generators is insufficient to meet the requirements for stable grid operation. Energy storage technology, as a key means to mitigate the fluctuations of new energy sources and enhance grid resilience, has become one of the core supporting technologies for power system upgrades.

[0003] Existing control strategies are mostly designed for single disturbance scenarios (such as frequency regulation or voltage regulation only), lacking a dynamic scenario segmentation mechanism. When the power grid experiences both frequency and voltage exceedances simultaneously, strategy switching delays or conflicts lead to prolonged recovery times, resulting in a lack of targeted and timely coordinated control.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this invention is to provide a collaborative control method, device, equipment, and storage medium for a grid-type energy storage system, aiming to solve the technical problems of lack of specificity and timeliness in collaborative control.

[0006] To achieve the above objectives, the present invention provides a collaborative control method for a grid-type energy storage system, the collaborative control method for a grid-type energy storage system comprising the following steps: Collect real-time frequency and real-time voltage of the power grid; Calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation; Based on the divided control scenarios, a preset collaborative control strategy library is invoked to determine the control strategy, which includes a frequency modulation priority strategy or a voltage regulation priority strategy. The active power addition value and reactive power addition value of each energy storage unit are calculated based on the virtual inertia parameters loaded according to the control strategy. The target power command is generated by superimposing the active power added value and the reactive power added value with the local power response value, and then the target power command is sent to the corresponding energy storage converter for coordinated control. The target power command includes target active power and target reactive power.

[0007] In some embodiments, determining the corresponding control scenario based on the frequency deviation and the voltage deviation includes: The frequency deviation is compared with a first deviation threshold. The voltage deviation is compared with a second deviation threshold. If the comparison results show that the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

[0008] In some embodiments, the step of calculating the active power addition value and reactive power addition value of each energy storage unit according to the virtual inertia parameters loaded by the control strategy includes: The corresponding virtual inertia parameters are loaded according to the control strategy, and the inertia ratio is calculated based on the virtual inertia parameters, wherein the inertia ratio α i =J i / ∑J i Jᵢ represents the virtual inertia parameter; The initial active power addition and initial reactive power addition are determined based on the set total power of the grid-type energy storage system and the inertia ratio. The initial active power addition value and the initial reactive power addition value are corrected based on preset constraints to obtain the active power addition value and reactive power addition value of each energy storage unit. The preset constraints are determined by the SOC of each energy storage unit.

[0009] In some embodiments, the initial active power addition and the initial reactive power addition are respectively ΔP_temp1=α i ×ΔP_total and ΔP_temp2=(1-α) i )×ΔP_total, where α i ΔP_total and ΔP_total represent the inertia percentage and the set total power, respectively. Accordingly, the correction of the initial active power increment and the initial reactive power increment based on preset constraints includes: Obtain the current SOC of each energy storage unit; The current SOC is compared with the SOC threshold corresponding to the preset constraint conditions; The correction coefficients are determined based on the comparison results; The initial active power addition and the initial reactive power addition are corrected based on the correction coefficient.

[0010] In some embodiments, sending the target power command to the corresponding energy storage converter for coordinated control includes: Convert the target active power and target reactive power into active power and reactive power commands in the dq coordinate system; A trigger pulse is generated by a pulse width modulation module, and the active power command and the reactive power command are sent to the corresponding energy storage converter for coordinated control using the trigger pulse. The frequency and voltage deviations of the energy storage converter during the collaborative control process are monitored in real time. If the frequency and voltage deviations consistently exceed the frequency or voltage deviation thresholds within a preset time period, the system switches to the backup control channel and reissues the active power command and the reactive power command through the backup control channel.

[0011] In some embodiments, the method further includes: Obtain the frequency recovery time t_rec and voltage fluctuation amplitude ΔU_max of the power grid after coordinated control; If t_rec > 2s or ΔU_max > 5%Un, where Un represents the rated voltage, then the standardized formula for the evaluation index is called: r(i,j) = x(i,j) [x max (i) +x min (i)]; Where x(i,j) is the original evaluation data, x_max(i) and x_min(i) are the maximum and minimum values ​​of sample i, respectively, and r(i,j) is the standardized evaluation index. When sample i=1, x(i,j) represents the frequency recovery time t_rec after the j-th coordinated control, and when sample i=2, x(i,j) represents the voltage fluctuation amplitude ΔU_max after the j-th coordinated control. The virtual inertia parameters are optimized using the particle swarm optimization algorithm based on r(i,j), and new active power and reactive power values ​​are obtained based on the optimized virtual inertia parameters. These new active power and reactive power values ​​are used for coordinated control in the next cycle.

[0012] Furthermore, to achieve the above objectives, the present invention also proposes a collaborative control device for a grid-type energy storage system, the collaborative control device for the grid-type energy storage system comprising: The data acquisition module is used to acquire the real-time frequency and real-time voltage of the power grid. The judgment module is used to calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation. The filtering module is used to call a preset collaborative control strategy library to determine the control strategy based on the divided control scenarios. The control strategy includes a frequency modulation priority strategy or a voltage regulation priority strategy. The calculation module is used to calculate the active power addition value and reactive power addition value of each energy storage unit based on the virtual inertia parameters loaded according to the control strategy. The control module is used to superimpose the active power added value and the reactive power added value with the local power response value to generate a target power command, and to send the target power command to the corresponding energy storage converter for coordinated control. The target power command includes target active power and target reactive power.

[0013] In some embodiments, the determining module is configured to compare the frequency deviation with a first deviation threshold. The voltage deviation is compared with a second deviation threshold. If the comparison results show that the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

[0014] Furthermore, to achieve the above objectives, the present invention also proposes a grid-type energy storage system collaborative control device, which includes: a memory, a processor, and a grid-type energy storage system collaborative control program stored in the memory and executable on the processor. The grid-type energy storage system collaborative control program is configured to implement the steps of the grid-type energy storage system collaborative control method described above.

[0015] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a collaborative control program for a grid-type energy storage system. When the collaborative control program for the grid-type energy storage system is executed by a processor, it implements the steps of the collaborative control method for the grid-type energy storage system as described above.

[0016] This invention collects the real-time frequency and voltage of the power grid; calculates frequency and voltage deviations based on the rated frequency and voltage, and determines the corresponding control scenarios based on the frequency and voltage deviations; determines the control strategy by calling a preset collaborative control strategy library based on the divided control scenarios; calculates the active power and reactive power added values ​​of each energy storage unit by loading virtual inertia parameters according to the control strategy; generates a target power command by superimposing the active power and reactive power added values ​​with the local power response value, and sends the target power command to the corresponding energy storage converter for collaborative control. The above method enables dynamic selection of control scenarios based on deviations, making the control strategy more targeted. At the same time, since the control strategy is also real-time, it ensures the timeliness of collaborative control. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the first embodiment of the collaborative control method for a grid-type energy storage system according to the present invention. Figure 2 This is a structural block diagram of the first embodiment of the collaborative control device for a grid-type energy storage system of the present invention.

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0020] This invention provides a collaborative control method for a grid-type energy storage system, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of a collaborative control method for a grid-type energy storage system according to the present invention.

[0021] In this embodiment, the collaborative control method for the grid-type energy storage system includes the following steps: Step S10: Collect the real-time frequency and real-time voltage of the power grid.

[0022] In this embodiment, the executing entity is a grid-type energy storage system collaborative control device. This grid-type energy storage system collaborative control device has functions such as data processing, data communication, and program execution. The grid-type energy storage system collaborative control device can be a computer terminal device or other network device, or other devices with similar functions. This embodiment does not limit this.

[0023] It should be noted that as the global energy structure transitions towards a low-carbon model, the penetration rate of new energy power generation technologies such as wind and solar power continues to increase. However, new energy power generation is intermittent, volatile, and random. Large-scale grid connection leads to a decrease in grid inertia and a weakening of voltage support capabilities, making it difficult for traditional synchronous generators to meet the requirements for stable grid operation. Energy storage technology, as a key means to mitigate the fluctuations of new energy and enhance grid resilience, has become one of the core supporting technologies for power system upgrades. Existing control strategies are mostly designed for single disturbance scenarios (such as frequency regulation or voltage regulation only), lacking a dynamic scenario segmentation mechanism. When the grid experiences both frequency and voltage exceedances simultaneously, strategy switching delays or conflicts lead to prolonged recovery times, resulting in a lack of targeted and timely coordinated control.

[0024] To address the aforementioned technical issues, this embodiment acquires the real-time frequency and voltage of the power grid; calculates frequency and voltage deviations based on the rated frequency and voltage, and determines the corresponding control scenarios based on these deviations; determines the control strategy by calling a preset collaborative control strategy library based on the divided control scenarios; calculates the active power and reactive power added values ​​of each energy storage unit by loading virtual inertia parameters according to the control strategy; generates a target power command by superimposing the active power and reactive power added values ​​with the local power response value, and sends the target power command to the corresponding energy storage converter for collaborative control. This method enables dynamic selection of control scenarios based on deviations, making the control strategy more targeted. Furthermore, since the control strategy is also real-time, it ensures the timeliness of collaborative control. Specifically, it can be implemented as follows.

[0025] In this specific implementation, it is necessary to first collect the real-time frequency and real-time voltage of the power grid. Specifically, the real-time frequency and real-time voltage of the power grid can be collected through devices such as PMU, current sensor and temperature sensor.

[0026] In one embodiment, after the above data is collected, a second-order Butterworth low-pass filter can be used to filter out high-frequency noise. The cutoff frequency of the second-order Butterworth low-pass filter can be set to 50Hz.

[0027] Step S20: Calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation.

[0028] In practical implementation, frequency deviation and voltage deviation are based on rated frequency and rated voltage. For example, the calculation assumes a rated frequency f. n =50Hz, rated voltage U n =10kV, the calculated frequency deviation is Δf=ff n Where, assuming the real-time frequency f is 50.2Hz, then Δf = 0.2Hz. The voltage deviation is ΔU = (UU... n ) / U n ×100%, where, assuming the real-time voltage U=9.8kV, then ΔU=-2%. The above parameters are for illustrative purposes only. In actual situations, calculations should be performed using the above formulas. In this embodiment, the rated frequency and rated voltage are not limited and need to be determined based on the actual operating data of the power grid.

[0029] Furthermore, after calculating the deviation, this embodiment can also determine the corresponding control scenario based on the frequency deviation and the voltage deviation. Specifically, the frequency deviation is compared with a first deviation threshold; the voltage deviation is compared with a second deviation threshold; and if the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold in the comparison results, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

[0030] It should be noted that the first deviation threshold (frequency) is assumed to be ±0.3Hz; and the second deviation threshold (voltage) is ±10%U. n (i.e., ±1kV). The comparison logic is implemented in the FPGA using a hardware description language (VHDL), and the judgment process is as follows: if |Δf|>0.3Hz and |ΔU|≤10%U n : Determined to be a frequency-dominant scenario; if |ΔU|>10%U n And |Δf| ≤ 0.3Hz: determined to be a voltage-dominated scenario; if |Δf| > 0.3Hz and |ΔU| > 10%U n The scenario is identified as a complex disturbance, and frequency deviation is the primary consideration. In this embodiment, scenarios such as control scenario A (Δf > 0.3Hz) and control scenario B (Δf < -0.3Hz) are defined as follows: control scenario A (Δf > 0.3Hz) with frequency as the primary control parameter, specifically reducing the active power output of the energy storage to suppress frequency increase; control scenario B (Δf < -0.3Hz) with frequency as the primary control parameter, specifically increasing the active power output of the energy storage to suppress frequency decrease; and control scenario C (ΔU > 10%U) are defined as follows. n The main control parameter is voltage, and the specific scenario is to reduce the reactive power output of the energy storage and suppress voltage rise. The control scenario for D is ΔU < -10%U. n The main control parameter is voltage, and the specific scenario is to increase the reactive power output of energy storage and suppress voltage drop.

[0031] Step S30: Determine the control strategy by calling the preset collaborative control strategy library based on the divided control scenario.

[0032] In a specific implementation, after determining the divided control scenarios, this embodiment can further determine the corresponding control strategies. For example, based on the above description, the control strategy corresponding to control scenarios A and B is a frequency modulation priority strategy, and the control strategy corresponding to control scenarios C and D is a voltage regulation priority strategy.

[0033] Step S40: Calculate the active power addition value and reactive power addition value of each energy storage unit by loading virtual inertia parameters according to the control strategy.

[0034] In practical implementation, assuming the control strategy is a frequency-priority strategy, the virtual inertia parameters corresponding to this strategy can be set to [1.2, 1.0, 0.8, 1.1, 0.9], and the inertia ratio α i =J i / ∑J i α can be calculated i =[0.24,0.20, 0.16, 0.22, 0.18].

[0035] Furthermore, the initial active power addition value and the initial reactive power addition value are determined based on the set total power of the grid-type energy storage system and the inertia ratio; the initial active power addition value and the initial reactive power addition value are corrected based on preset constraints to obtain the active power addition value and reactive power addition value of each energy storage unit, wherein the preset constraints are determined by the SOC of each energy storage unit.

[0036] In this embodiment, the initial active power increment and the initial reactive power increment are respectively ΔP_temp1=α i ×ΔP_total and ΔP_temp2=(1-α) i )×ΔP_total, where α i ΔP_total and ΔP_total represent the inertia percentage and the set total power, respectively. Taking the initial active power increment as an example, assuming ΔP_total = 80kW, and combining this with the aforementioned α... i =[0.24, 0.20, 0.16, 0.22, 0.18], ΔP_temp1= [19.2, 16.0, 12.8, 17.6, 14.4] kW, and by averaging, P_temp1=16kW.

[0037] Further, the correction process involves obtaining the current SOC of each energy storage unit; comparing the current SOC with the SOC threshold corresponding to the preset constraints; determining the correction coefficient based on the comparison result; and correcting the initial active power addition value and the initial reactive power addition value based on the correction coefficient. The preset constraints are determined by the SOC of each energy storage unit, for example, 20% and 80%. The correction is as follows: when SOC > 80%, the correction coefficient k = 1.2 (allowing additional generation); when 20% ≤ SOC ≤ 80%, the correction coefficient k = 1.0 (normal generation increase); when SOC < 20%, the correction coefficient k = 0.8 (limited generation increase). The corrected active power addition value is ΔP1 = k. i ×ΔPtemp1,k i Determined based on the above conditions.

[0038] Step S50: The active power additional value and the reactive power additional value are superimposed with the local power response value to generate a target power command, and the target power command is sent to the corresponding energy storage converter for coordinated control.

[0039] In this embodiment, the target power command includes target active power and target reactive power. The coordinated control process specifically includes converting the target active power and target reactive power into active power commands and reactive power commands in the dq coordinate system; generating a trigger pulse through a pulse width modulation module, and using the trigger pulse to send the active power commands and the reactive power commands to the corresponding energy storage converters for coordinated control; monitoring the frequency deviation and voltage deviation of the energy storage converters in real time during the coordinated control process; if the frequency deviation and voltage deviation consistently exceed the frequency deviation threshold or voltage deviation threshold within a preset time period, switching to the backup control channel, and re-sending the active power commands and the reactive power commands through the backup control channel.

[0040] It should be noted that converting active / reactive power commands into DC quantities in the dq coordinate system facilitates converter control, for example:

[0041] The PWM pulse generation and IGBT control of the energy storage converter adopt a two-level topology. The trigger pulse is generated by space vector pulse width modulation (SVPWM): voltage vector synthesis: calculate the amplitude and angle of the reference voltage vector according to the dq axis command voltage; sector judgment: determine the sector where the reference vector is located and select the adjacent basic vector; pulse width calculation: calculate the action time of each vector according to the volt-second balance principle and generate PWM wave (switching frequency 20kHz).

[0042] Furthermore, to make the coordinated control more precise, this embodiment obtains the frequency recovery time t_rec and voltage fluctuation amplitude ΔU_max of the power grid after coordinated control; if t_rec>2s or ΔU_max>5%U n U n If the rated voltage is used, then the standardized formula for the evaluation index is called: r(i,j) = x(i,j) [x max (i) +x min (i)]; Where x(i,j) is the original evaluation data, x_max(i) and x_min(i) are the maximum and minimum values ​​of sample i, respectively, and r(i,j) is the standardized evaluation index. When sample i=1, x(i,j) represents the frequency recovery time t_rec after the j-th coordinated control, and when sample i=2, x(i,j) represents the voltage fluctuation amplitude ΔU_max after the j-th coordinated control. Based on r(i,j), the virtual inertia parameters are optimized by the particle swarm optimization algorithm, and new active power and reactive power additional values ​​are obtained based on the optimized virtual inertia parameters. The new active power and reactive power additional values ​​are used for the coordinated control of the next cycle.

[0043] In this embodiment, the real-time frequency and voltage of the power grid are collected; frequency deviation and voltage deviation are calculated based on the rated frequency and rated voltage, and the corresponding control scenario is determined according to the frequency deviation and voltage deviation; the control strategy is determined by calling the preset collaborative control strategy library based on the divided control scenario; the active power added value and reactive power added value of each energy storage unit are calculated by loading virtual inertia parameters according to the control strategy; the active power added value and reactive power added value are superimposed with the local power response value to generate the target power command, and the target power command is sent to the corresponding energy storage converter for collaborative control. The above method can dynamically select the control scenario based on the deviation, making the control strategy more targeted. At the same time, since the control strategy is also real-time, the timeliness of collaborative control is guaranteed.

[0044] Furthermore, this embodiment of the invention also proposes a storage medium storing a collaborative control program for a grid-type energy storage system. When the collaborative control program for the grid-type energy storage system is executed by a processor, it implements the steps of the collaborative control method for the grid-type energy storage system as described above.

[0045] Reference Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the collaborative control device for a grid-type energy storage system of the present invention.

[0046] like Figure 2 As shown, the collaborative control device for a grid-type energy storage system proposed in this embodiment of the invention includes: The acquisition module 10 is used to acquire the real-time frequency and real-time voltage of the power grid; The judgment module 20 is used to calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation. The filtering module 30 is used to call a preset collaborative control strategy library to determine the control strategy based on the divided control scenario. The control strategy includes a frequency modulation priority strategy or a voltage regulation priority strategy. The calculation module 40 is used to calculate the active power addition value and reactive power addition value of each energy storage unit according to the virtual inertia parameters loaded by the control strategy. The control module 50 is used to generate a target power command by superimposing the active power additional value and the reactive power additional value with the local power response value, and to send the target power command to the corresponding energy storage converter for coordinated control. The target power command includes target active power and target reactive power.

[0047] In this embodiment, the real-time frequency and voltage of the power grid are collected; frequency deviation and voltage deviation are calculated based on the rated frequency and rated voltage, and the corresponding control scenario is determined according to the frequency deviation and voltage deviation; the control strategy is determined by calling the preset collaborative control strategy library based on the divided control scenario; the active power added value and reactive power added value of each energy storage unit are calculated by loading virtual inertia parameters according to the control strategy; the active power added value and reactive power added value are superimposed with the local power response value to generate the target power command, and the target power command is sent to the corresponding energy storage converter for collaborative control. The above method can dynamically select the control scenario based on the deviation, making the control strategy more targeted. At the same time, since the control strategy is also real-time, the timeliness of collaborative control is guaranteed.

[0048] In some embodiments, the determination module 20 is used to compare the frequency deviation with a first deviation threshold. The voltage deviation is compared with a second deviation threshold. If the comparison results show that the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

[0049] In some embodiments, the calculation module 40 is configured to load corresponding virtual inertia parameters according to the control strategy, and calculate the inertia ratio based on the virtual inertia parameters, wherein the inertia ratio α i =J i / ∑J i Jᵢ represents the virtual inertia parameter; The initial active power addition and initial reactive power addition are determined based on the set total power of the grid-type energy storage system and the inertia ratio. The initial active power addition value and the initial reactive power addition value are corrected based on preset constraints to obtain the active power addition value and reactive power addition value of each energy storage unit. The preset constraints are determined by the SOC of each energy storage unit.

[0050] In some embodiments, the initial active power addition value and the initial reactive power addition value are ΔP_temp1=αᵢ×ΔP_total and ΔP_temp2=(1-αᵢ)×ΔP_total, respectively, where αᵢ and ΔP_total are the inertia ratio and the set total power, respectively. Accordingly, the calculation module 40 is used to obtain the current SOC of each energy storage unit; The current SOC is compared with the SOC threshold corresponding to the preset constraint conditions; The correction coefficients are determined based on the comparison results; The initial active power addition and the initial reactive power addition are corrected based on the correction coefficient.

[0051] In some embodiments, the control module 50 is used to convert the target active power and the target reactive power into active power commands and reactive power commands in the dq coordinate system; A trigger pulse is generated by a pulse width modulation module, and the active power command and the reactive power command are sent to the corresponding energy storage converter for coordinated control using the trigger pulse. The frequency and voltage deviations of the energy storage converter during the collaborative control process are monitored in real time. If the frequency and voltage deviations consistently exceed the frequency or voltage deviation thresholds within a preset time period, the system switches to the backup control channel and reissues the active power command and the reactive power command through the backup control channel.

[0052] In some embodiments, the control module 50 is configured to acquire the frequency recovery time t_rec and voltage fluctuation amplitude ΔU_max of the power grid after coordinated control. If t_rec>2s or ΔU_max>5%U n U n If the rated voltage is used, then the standardized formula for the evaluation index is called: r(i,j) = x(i,j) [x max (i) +x min (i)]; Where x(i,j) is the original evaluation data, x_max(i) and x_min(i) are the maximum and minimum values ​​of sample i, respectively, and r(i,j) is the standardized evaluation index. When sample i=1, x(i,j) represents the frequency recovery time t_rec after the j-th coordinated control, and when sample i=2, x(i,j) represents the voltage fluctuation amplitude ΔU_max after the j-th coordinated control. The virtual inertia parameters are optimized using the particle swarm optimization algorithm based on r(i,j), and new active power and reactive power values ​​are obtained based on the optimized virtual inertia parameters. These new active power and reactive power values ​​are used for coordinated control in the next cycle.

[0053] This application embodiment also provides a collaborative control device for a grid-type energy storage system, including a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other through the communication bus. The memory is used to store the collaborative control program for the grid-type energy storage system. When the processor executes the program stored in the memory, it implements the above-mentioned collaborative control method for the grid-type energy storage system.

[0054] The communication bus mentioned in the aforementioned network-type energy storage system's collaborative control equipment can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc.

[0055] The communication interface is used for communication between the collaborative control equipment of the aforementioned grid-type energy storage system and other equipment.

[0056] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0057] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0058] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0059] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0060] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0061] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention 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 the present invention.

[0062] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0063] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0064] In addition, for technical details not described in detail in this embodiment, please refer to the collaborative control method of the grid-type energy storage system provided in any embodiment of the present invention, which will not be repeated here.

[0065] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0066] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0068] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

[0069] It is understood that the system provided in the embodiments of the present invention corresponds to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

Claims

1. A collaborative control method for a grid-type energy storage system, characterized in that, The collaborative control method for the grid-type energy storage system includes: Collect real-time frequency and real-time voltage of the power grid; Calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation; Based on the divided control scenarios, a preset collaborative control strategy library is invoked to determine the control strategy, which includes a frequency modulation priority strategy or a voltage regulation priority strategy. The active power addition value and reactive power addition value of each energy storage unit are calculated based on the virtual inertia parameters loaded according to the control strategy. The target power command is generated by superimposing the active power added value and the reactive power added value with the local power response value, and then the target power command is sent to the corresponding energy storage converter for coordinated control. The target power command includes target active power and target reactive power.

2. The collaborative control method for a grid-type energy storage system as described in claim 1, characterized in that, The step of determining the corresponding control scenario based on the frequency deviation and the voltage deviation includes: The frequency deviation is compared with a first deviation threshold. The voltage deviation is compared with a second deviation threshold. If the comparison results show that the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

3. The collaborative control method for a grid-type energy storage system as described in claim 1, characterized in that, The calculation of the active power addition value and reactive power addition value of each energy storage unit based on the virtual inertia parameters loaded according to the control strategy includes: The corresponding virtual inertia parameters are loaded according to the control strategy, and the inertia ratio is calculated based on the virtual inertia parameters, wherein the inertia ratio α i =J i / ∑J i Jᵢ represents the virtual inertia parameter; The initial active power addition and initial reactive power addition are determined based on the set total power of the grid-type energy storage system and the inertia ratio. The initial active power addition value and the initial reactive power addition value are corrected based on preset constraints to obtain the active power addition value and reactive power addition value of each energy storage unit. The preset constraints are determined by the SOC of each energy storage unit.

4. The collaborative control method for a grid-type energy storage system as described in claim 3, characterized in that, The initial active power increment and the initial reactive power increment are respectively ΔP_temp1=α i ×ΔP_total and ΔP_temp2=(1-α) i )×ΔP_total, where α i ΔP_total and ΔP_total represent the inertia percentage and the set total power, respectively. Accordingly, the correction of the initial active power increment and the initial reactive power increment based on preset constraints includes: Obtain the current SOC of each energy storage unit; The current SOC is compared with the SOC threshold corresponding to the preset constraint conditions; The correction coefficients are determined based on the comparison results; The initial active power addition and the initial reactive power addition are corrected based on the correction coefficient.

5. The collaborative control method for a grid-type energy storage system as described in claim 1, characterized in that, The step of sending the target power command to the corresponding energy storage converter for coordinated control includes: Convert the target active power and target reactive power into active power and reactive power commands in the dq coordinate system; A trigger pulse is generated by a pulse width modulation module, and the active power command and the reactive power command are sent to the corresponding energy storage converter for coordinated control using the trigger pulse. The frequency and voltage deviations of the energy storage converter during the collaborative control process are monitored in real time. If the frequency and voltage deviations consistently exceed the frequency or voltage deviation thresholds within a preset time period, the system switches to the backup control channel and reissues the active power command and the reactive power command through the backup control channel.

6. The collaborative control method for a grid-type energy storage system as described in claim 1, characterized in that, The method further includes: Obtain the frequency recovery time t_rec and voltage fluctuation amplitude ΔU_max of the power grid after coordinated control; If t_rec>2s or ΔU_max>5%U n U n If the rated voltage is used, then the standardized formula for the evaluation index is called: r(i,j) = x(i,j) [x max (i) +x min (i)]; Where x(i,j) is the original evaluation data, x_max(i) and x_min(i) are the maximum and minimum values ​​of sample i, respectively, and r(i,j) is the standardized evaluation index. When sample i=1, x(i,j) represents the frequency recovery time t_rec after the j-th coordinated control, and when sample i=2, x(i,j) represents the voltage fluctuation amplitude ΔU_max after the j-th coordinated control. The virtual inertia parameters are optimized using the particle swarm optimization algorithm based on r(i,j), and new active power and reactive power values ​​are obtained based on the optimized virtual inertia parameters. These new active power and reactive power values ​​are used for coordinated control in the next cycle.

7. A collaborative control device for a grid-type energy storage system, characterized in that, The collaborative control device for the grid-type energy storage system includes: The data acquisition module is used to acquire the real-time frequency and real-time voltage of the power grid. The judgment module is used to calculate the frequency deviation and voltage deviation based on the rated frequency and rated voltage, and determine the corresponding control scenario based on the frequency deviation and voltage deviation. The filtering module is used to call a preset collaborative control strategy library to determine the control strategy based on the divided control scenarios. The control strategy includes a frequency modulation priority strategy or a voltage regulation priority strategy. The calculation module is used to calculate the active power addition value and reactive power addition value of each energy storage unit based on the virtual inertia parameters loaded according to the control strategy. The control module is used to superimpose the active power added value and the reactive power added value with the local power response value to generate a target power command, and to send the target power command to the corresponding energy storage converter for coordinated control. The target power command includes target active power and target reactive power.

8. The collaborative control device for a grid-type energy storage system as described in claim 7, characterized in that, The judgment module is used to compare the frequency deviation with a first deviation threshold. The voltage deviation is compared with a second deviation threshold. If the comparison results show that the frequency deviation exceeds the first deviation threshold and / or the voltage deviation exceeds the second deviation threshold, then the corresponding control scenario is determined based on the frequency deviation and / or the voltage deviation.

9. A collaborative control device for a grid-type energy storage system, characterized in that, The grid-type energy storage system collaborative control device includes: a memory, a processor, and a grid-type energy storage system collaborative control program stored in the memory and executable on the processor. The grid-type energy storage system collaborative control program is configured to implement the steps of the grid-type energy storage system collaborative control method as described in any one of claims 1 to 6.

10. A storage medium, characterized in that, The storage medium stores a collaborative control program for a grid-type energy storage system. When the processor executes the collaborative control program for the grid-type energy storage system, it implements the steps of the collaborative control method for a grid-type energy storage system as described in any one of claims 1 to 6.

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