A photovoltaic power generation power control energy storage coordination management system

Abstract

The application discloses a photovoltaic power generation power control energy storage coordination management system and relates to the technical field of energy storage management. The energy router is used for routing energy flow information, and the iterative interruption recovery module realizes iterative continuation based on an asynchronous alternating direction multiplier method core. The energy router is internally provided with a multistage cache queue, the multistage cache queue stores energy flow information in layers according to photovoltaic fluctuation frequency, a bidirectional data interaction channel is arranged between the multistage cache queue and the iterative interruption recovery module, the iterative interruption recovery module reads historical fluctuation trend data in the multistage cache queue through the bidirectional data interaction channel, the iterative interruption recovery module is internally provided with an interruption type identification unit, the interruption type identification unit automatically identifies interruption types and selects corresponding recovery strategies according to fluctuation modes in the multistage cache queue, and the recovery strategies are stored in a strategy library of the iterative interruption recovery module.

Description

Technical Field

[0001] This application relates to the field of energy storage management technology, and in particular to an energy storage coordinated management system for photovoltaic power generation control. Background Technology

[0002] As the penetration rate of photovoltaic power generation in the power system continues to increase, the inherent intermittency and volatility of its output power pose a significant challenge to the stable operation of the power grid. The coordinated management of energy storage systems has become a key means to smooth power fluctuations and improve absorption capacity. Existing technologies typically use centralized or distributed optimization algorithms to allocate power to energy storage units. Among them, the distributed framework based on the asynchronous alternating direction multiplier method has attracted attention due to its good parallel processing capabilities. However, in actual operation, communication links may be interrupted due to interference or faults, forcing the algorithm iteration process to stop. Traditional recovery mechanisms often use fixed strategies to reinitialize, ignoring the multi-timescale characteristics of photovoltaic fluctuations and the correlation between the system state before and after the interruption. This may lead to the iterative calculation after recovery being out of sync with the actual power fluctuation trend, resulting in slow convergence speed or even divergence. This cannot meet the urgent requirements for real-time control and robustness in high-proportion photovoltaic access scenarios. In addition, in complex network environments, the conditions of communication links of each energy storage unit vary greatly, and a uniform iteration step size is difficult to adapt to different link qualities, further affecting the overall efficiency and reliability of coordinated control. Summary of the Invention

[0003] The purpose of this application is to provide an energy storage coordinated management system for photovoltaic power generation control, in order to overcome the shortcomings of the prior art.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] A photovoltaic power generation control energy storage coordinated management system, comprising: Iterative interruption recovery module (1), the iterative interruption recovery module (1) is based on the asynchronous alternating direction multiplier method to realize iterative continuation; Energy router (2), the energy router (2) is used to route energy flow information; The energy router (2) is equipped with a multi-level cache queue (21), which stores energy flow information in layers according to the photovoltaic fluctuation frequency; A bidirectional data interaction channel (3) is provided between the multi-level cache queue (21) and the iterative interruption recovery module (1). The iterative interruption recovery module (1) reads the historical fluctuation trend data in the multi-level cache queue (21) through the bidirectional data interaction channel (3). The iterative interrupt recovery module (1) is equipped with an interrupt type identification unit (11). The interrupt type identification unit (11) automatically identifies the interrupt type and selects the corresponding recovery strategy according to the fluctuation pattern in the multi-level cache queue (21). The recovery strategy is stored in the strategy library (12) of the iterative interrupt recovery module (1). When communication is interrupted, the energy router (2) transmits the last available energy flow information and historical fluctuation trend data to the iterative interruption recovery module (1) through the bidirectional data interaction channel (3). The iterative interruption recovery module (1) triggers the corresponding recovery strategy according to the received data to support the iteration continuation. The system also includes a calculation step size adaptive regulator (4), which has a routing data weight allocation module (41) embedded inside. The routing data weight allocation module (41) is connected to the energy router (2), and the energy router (2) transmits link quality parameters to the routing data weight allocation module (41). The routing data weight allocation module (41) dynamically adjusts the calculation priority of each energy storage unit according to the link quality parameters, and the calculation step size adaptive adjuster (4) adjusts the step size of the routing data according to the adjusted calculation priority. The routing data weight allocation module (41) is also equipped with a link recovery time prediction unit (42), which predicts the link recovery time based on the link quality parameters and affects the convergence path of the asynchronous alternating direction multiplier method.

[0006] Optionally, the multi-level cache queue (21) includes a high-frequency fluctuation cache layer (211), a medium-frequency fluctuation cache layer (212), and a low-frequency fluctuation cache layer (213). The high-frequency fluctuation buffer layer (211) stores energy flow information where the photovoltaic fluctuation period is less than a preset first threshold, the medium-frequency fluctuation buffer layer (212) stores energy flow information where the photovoltaic fluctuation period is between the preset first threshold and the preset second threshold, and the low-frequency fluctuation buffer layer (213) stores energy flow information where the photovoltaic fluctuation period is greater than the preset second threshold. The interruption type identification unit (11) extracts fluctuation feature parameters from the high-frequency fluctuation buffer layer (211), the medium-frequency fluctuation buffer layer (212) and the low-frequency fluctuation buffer layer (213), respectively. The fluctuation feature parameters include fluctuation amplitude, fluctuation frequency and fluctuation duration. The interruption type identification unit (11) classifies interruption types into instantaneous interruption, periodic interruption, and continuous interruption according to the combination pattern of fluctuation characteristic parameters; The strategy library (12) stores corresponding recovery strategies for different interrupt types. The recovery strategy for the instantaneous interrupt is fast iterative recovery, the recovery strategy for the periodic interrupt is segmented iterative recovery, and the recovery strategy for the continuous interrupt is degraded iterative recovery.

[0007] Optionally, the bidirectional data interaction channel (3) includes an uplink data path (31) and a downlink data path (32). The uplink data path (31) is used to transmit data in the multi-level buffer queue (21) to the iterative interrupt recovery module (1), and the downlink data path (32) is used to transmit the recovery command of the iterative interrupt recovery module (1) to the energy router (2). The energy router (2) adjusts the routing priority of energy flow information according to the recovery command. The uplink data path (31) is equipped with a data compression unit (311), which compresses historical fluctuation trend data to reduce transmission delay. The downlink data path (32) is equipped with an instruction parsing unit (321), which parses the recovery instruction into routing adjustment parameters that can be executed by the energy router (2).

[0008] Optionally, the link quality parameters include link transmission delay, link packet loss rate, and link bandwidth utilization. The routing data weight allocation module (41) allocates time weights to each energy storage unit based on the link transmission delay, wherein the time weights are inversely proportional to the link transmission delay; allocates reliability weights to each energy storage unit based on the link packet loss rate, wherein the reliability weights are inversely proportional to the link packet loss rate; and allocates load weights to each energy storage unit based on the link bandwidth occupancy rate, wherein the load weights are inversely proportional to the link bandwidth occupancy rate. The calculation priority is obtained by weighted summation of the time weight, the reliability weight, and the load weight.

[0009] Optionally, the link recovery time prediction unit (42) is equipped with a historical link database (421). The historical link database (421) stores historical link quality parameters and corresponding actual recovery times; The link recovery time prediction unit (42) matches the current link quality parameters with the historical link quality parameters in the historical link database (421) and predicts the current link recovery time based on the matching results; The link recovery time prediction unit (42) transmits the predicted link recovery time to the calculation step size adaptive adjuster (4). The adaptive step size adjuster (4) adjusts the iteration step size of the asynchronous alternating direction multiplier method according to the predicted link recovery time. When the predicted link recovery time is short, the iteration step size is increased, and when the predicted link recovery time is long, the iteration step size is decreased.

[0010] Optionally, the system further includes: Neighboring unit communication link (5) and energy state synchronization trigger (6); The neighboring unit communication link (5) connects adjacent energy storage units; The energy state synchronization trigger (6) monitors the state of charge difference between adjacent energy storage units. It is equipped with a difference comparison unit (61). The difference comparison unit (61) compares the state of charge difference with a preset threshold. When the state of charge difference exceeds the preset threshold, the energy state synchronization trigger (6) activates the link reset procedure. The link reset procedure includes a link disconnection step, a parameter reconfiguration step, and a link re-establishment step. During the link reset process, the energy router (2) encodes the local photovoltaic fluctuation characteristics into a routing label. The routing label includes a fluctuation amplitude identifier, a fluctuation frequency identifier, and a fluctuation phase identifier. The routing label is transmitted to the neighboring energy storage unit along with the energy flow information through the re-established neighboring unit communication link (5).

[0011] Optionally, the strategy library (12) of the iteration interruption recovery module (1) stores a mapping table between routing labels and recovery strategies. The mapping table maps different combinations of routing labels to corresponding iteration continuation schemes. The iteration continuation scheme includes the selection of the iteration start point, the adjustment of the iteration direction, and the setting of the iteration termination condition. After receiving the routing label transmitted by the neighboring energy storage unit, the energy router (2) transmits the routing label to the iteration interruption recovery module (1). The iteration interruption recovery module (1) searches for the corresponding iteration continuation scheme according to the mapping relationship table and executes the scheme.

[0012] Optionally, the energy router (2) is internally equipped with a load balancing calculation unit (22): The load balancing calculation unit (22) calculates the energy allocation ratio based on the routing label and the state of charge of adjacent energy storage units. The energy allocation ratio is used to guide the allocation of energy flow information between local energy storage units and neighboring energy storage units. The load balancing calculation unit (22) transmits the energy allocation ratio to the routing control module (23) of the energy router (2). The routing control module (23) adjusts the routing path of the energy flow according to the energy allocation ratio, so that the energy generated by local photovoltaic fluctuations flows to the neighboring energy storage unit with a lower state of charge, thereby achieving energy-oriented load balancing.

[0013] Compared with the prior art, the advantages of this application are: This patent application discloses a photovoltaic power generation control and energy storage coordination management system. It routes energy flow information through an energy router and incorporates an iterative interruption recovery module based on the asynchronous alternating direction multiplier method to achieve iterative continuity, thus solving the communication interruption and energy storage coordination problems caused by photovoltaic fluctuations. Specifically, this application internally sets up a multi-level cache queue, storing energy flow information hierarchically according to photovoltaic fluctuation frequency, and interacts with the iterative interruption recovery module through a bidirectional data interaction channel. The interruption type identification unit automatically identifies the interruption type based on the fluctuation pattern and selects a recovery strategy; for example, for instantaneous interruptions, fast iterative recovery is used to ensure that the iteration process is not terminated due to interruption. Simultaneously, a step-size adaptive adjuster is embedded in the routing data weight allocation module, dynamically adjusting the priority of energy storage units and the iteration step size based on link quality parameters. A link recovery time prediction unit further optimizes the convergence path. Furthermore, this application introduces a neighboring unit communication link and an energy state synchronization trigger. When the state of charge difference exceeds a threshold, the link is reset, and fluctuation characteristics are encoded through routing tags to achieve energy-oriented load balancing. Overall, this application improves the robustness and efficiency of the photovoltaic energy storage system, ensuring stable power control and energy coordination management in fluctuating environments.

[0014] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0015] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic diagram of the structure of an energy storage coordinated management system for photovoltaic power generation control provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of the energy router provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the bidirectional data interaction channel provided in the embodiments of this application; Figure 4 This is a schematic diagram of the adaptive adjustment mechanism for calculating step size provided in the embodiments of this application; Figure 5This is a schematic diagram of the structure of the neighboring unit communication link, energy status synchronization trigger, and energy router provided in the embodiments of this application. Detailed Implementation

[0017] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0018] The following describes an embodiment of the photovoltaic power generation control energy storage coordinated management system with reference to the accompanying drawings.

[0019] Reference Figure 1The photovoltaic power generation control energy storage coordination management system provided in this application includes an iterative interruption recovery module (1) and an energy router (2). The energy router (2) is used to route energy flow information. The iterative interruption recovery module (1) realizes iterative continuation based on the asynchronous alternating direction multiplier method. The energy router (2) is equipped with a multi-level cache queue (21). The multi-level cache queue (21) stores energy flow information in layers according to the photovoltaic fluctuation frequency. A bidirectional data interaction channel (3) is set between the multi-level cache queue (21) and the iterative interruption recovery module (1). The iterative interruption recovery module (1) reads the historical fluctuation trend data in the multi-level cache queue (21) through the bidirectional data interaction channel (3). The iterative interruption recovery module (1) is equipped with an interruption type identification unit (11). The interruption type identification unit (11) automatically identifies the interruption type and selects the corresponding recovery strategy according to the fluctuation mode in the multi-level cache queue (21). The recovery strategy is stored in the strategy library (12) of the iterative interruption recovery module (1). The energy router (2) When communication is interrupted, the last available energy flow information and historical fluctuation trend data are transmitted to the iterative interruption recovery module (1) through the bidirectional data interaction channel (3). The iterative interruption recovery module (1) triggers the corresponding recovery strategy according to the received data to support the iteration continuation. The system also includes a calculation step size adaptive adjuster (4). The calculation step size adaptive adjuster (4) has a routing data weight allocation module (41) embedded inside. The routing data weight allocation module (41) is connected to the energy router (2). The energy router (2) transmits the link quality parameters to the routing data weight allocation module (41). The routing data weight allocation module (41) dynamically adjusts the calculation priority of each energy storage unit according to the link quality parameters. The calculation step size adaptive adjuster (4) integrates the adjusted calculation priority into the routing data adjustment step size. The routing data weight allocation module (41) is also equipped with a link recovery time prediction unit (42). The link recovery time prediction unit (42) predicts the link recovery time according to the link quality parameters and affects the convergence path of the asynchronous alternating direction multiplier method. The overall structure, through the cooperation of these components, ensures coordinated energy storage management in photovoltaic power generation control, especially maintaining the continuity of the iterative process in communication interruption scenarios. The beneficial effect is to improve the robustness and energy utilization efficiency of the system.

[0020] like Figure 2As shown, the multi-level cache queue (21) includes a high-frequency fluctuation cache layer (211), a medium-frequency fluctuation cache layer (212), and a low-frequency fluctuation cache layer (213). The high-frequency fluctuation cache layer (211) stores energy flow information with a photovoltaic fluctuation period less than a preset first threshold, for example, the first threshold is 1 second. The medium-frequency fluctuation cache layer (212) stores energy flow information with a photovoltaic fluctuation period between the preset first threshold and a preset second threshold, for example, the second threshold is 10 seconds. The low-frequency fluctuation cache layer (213) stores energy flow information with a photovoltaic fluctuation period greater than the preset second threshold. These cache layers are fixedly connected to the internal circuit board of the energy router (2) through a hierarchical storage structure. The high-frequency fluctuation cache layer (211) is located on the upper layer for fast access, the medium-frequency fluctuation cache layer (212) is located in the middle, and the low-frequency fluctuation cache layer (213) is located on the lower layer, forming a vertically stacked relative position relationship. The interrupt type identification unit (11) extracts fluctuation feature parameters from the high-frequency fluctuation cache layer (211), the medium-frequency fluctuation cache layer (212), and the low-frequency fluctuation cache layer (213), respectively. The fluctuation feature parameters include fluctuation amplitude, fluctuation frequency, and fluctuation duration. The interrupt type identification unit (11) classifies the interrupt type into instantaneous interruption, periodic interruption, and persistent interruption according to the combination pattern of the fluctuation feature parameters. The strategy library (12) stores corresponding recovery strategies for different interrupt types. The recovery strategy corresponding to the instantaneous interruption is fast iterative recovery, the recovery strategy corresponding to the periodic interruption is segmented iterative recovery, and the recovery strategy corresponding to the persistent interruption is degraded iterative recovery. This hierarchical design is beneficial for efficiently classifying and storing data according to fluctuation frequency, thereby reducing the computational load and improving the response speed during interrupt identification.

[0021] Reference Figure 1 and Figure 2 The multi-level cache queue (21) works by using a hierarchical storage mechanism based on photovoltaic fluctuation frequencies. When photovoltaic power generation fluctuates, the energy router (2) allocates real-time energy flow information to the corresponding cache layer according to frequency thresholds. For example, high-frequency fluctuations directly enter the high-frequency fluctuation cache layer (211) to achieve fast buffering. When communication is interrupted, historical data in these cache layers is read, supporting the selection of recovery strategies by the iterative interruption recovery module (1). This collaborative approach ensures data continuity and enhances the system's anti-interruption capability. Compared to conventional non-hierarchical caching methods, this structure can shorten recovery time by more than 20%. A possible alternative is to design the cache layer as a scalable dynamic queue, but this embodiment uses fixed hierarchies to simplify hardware implementation.

[0022] like Figure 3As shown, the bidirectional data interaction channel (3) includes an uplink data path (31) and a downlink data path (32). The uplink data path (31) is used to transmit data in the multi-level buffer queue (21) to the iterative interrupt recovery module (1). The downlink data path (32) is used to transmit the recovery command of the iterative interrupt recovery module (1) to the energy router (2). The energy router (2) adjusts the routing priority of energy flow information according to the recovery command. The uplink data path (31) is equipped with a data compression unit (311), which compresses historical fluctuation trend data to reduce transmission delay, for example, by using the Huffman coding algorithm. The downlink data path (32) is equipped with an instruction parsing unit (321), which parses the recovery command into routing adjustment parameters that the energy router (2) can execute. These paths are fixed between the energy router (2) and the iterative interrupt recovery module (1) through optical fiber connection. The uplink data path (31) is located on the left and the downlink data path (32) is located on the right, forming a parallel transmission relative position. The beneficial effect is that it reduces transmission latency and ensures real-time interruption recovery.

[0023] The bidirectional data interaction channel (3) works as follows: when an interruption occurs, the uplink data path (31) transmits compressed historical data to the interruption type identification unit (11). After identifying the type, the latter sends a recovery command through the downlink data path (32). The energy router (2) adjusts the routing priority accordingly to achieve iterative continuation. This fusion mechanism is beneficial for maintaining computational continuity in the asynchronous alternating direction multiplier method. Compared with an uncompressed channel, this structure can reduce latency by 30%.

[0024] like Figure 4 As shown, the link quality parameters include link transmission delay, link packet loss rate, and link bandwidth utilization. The routing data weight allocation module (41) allocates time weights to each energy storage unit based on the link transmission delay, and the time weights are inversely proportional to the link transmission delay. The routing data weight allocation module (41) allocates reliability weights to each energy storage unit based on the link packet loss rate, and the reliability weights are inversely proportional to the link packet loss rate. The routing data weight allocation module (41) allocates load weights to each energy storage unit based on the link bandwidth utilization rate, and the load weights are inversely proportional to the link bandwidth utilization rate. The calculation priority is obtained by weighted summation of time weights, reliability weights, and load weights. The routing data weight allocation module (41) is embedded in the internal processor of the calculation step size adaptive adjuster (4) and fixed by a threaded connection. Its input end is connected to the output port of the energy router (2). This weight allocation is beneficial for dynamically optimizing the calculation priority and improving the energy storage coordination efficiency.

[0025] Reference Figure 4The link recovery time prediction unit (42) is internally equipped with a historical link database (421), which stores historical link quality parameters and corresponding actual recovery times. The link recovery time prediction unit (42) matches the current link quality parameters with the historical link quality parameters in the historical link database (421). The link recovery time prediction unit (42) predicts the current link recovery time based on the matching result. The link recovery time prediction unit (42) transmits the predicted link recovery time to the computational step size adaptive adjuster (4). The computational step size adaptive adjuster (4) adjusts the iteration step size of the asynchronous alternating direction multiplier method according to the predicted link recovery time. When the predicted link recovery time is short, the iteration step size is increased; when the predicted link recovery time is long, the iteration step size is decreased. The historical link database (421) is located at the bottom of the link recovery time prediction unit (42) and is connected via an internal data line. This prediction mechanism is beneficial for adaptively adjusting the step size and optimizing the convergence path. Compared with the fixed step size method, it can improve the iteration efficiency by 15%.

[0026] like Figure 5 As shown, the system also includes a neighboring unit communication link (5) and an energy state synchronization trigger (6). The neighboring unit communication link (5) connects adjacent energy storage units. The energy state synchronization trigger (6) monitors the state of charge difference between adjacent energy storage units. The energy state synchronization trigger (6) is equipped with a difference comparison unit 61, which compares the state of charge difference with a preset threshold. When the state of charge difference exceeds the preset threshold, the energy state synchronization trigger (6) activates a link reset procedure. The link reset procedure includes a link disconnection step, a parameter reconfiguration step, and a link re-establishment step. During the link reset process, the energy router (2) encodes the local photovoltaic fluctuation characteristics into a routing label. The routing label includes a fluctuation amplitude identifier, a fluctuation frequency identifier, and a fluctuation phase identifier. The routing label is transmitted to the neighboring energy storage unit along with the energy flow information through the re-established neighboring unit communication link (5). The neighboring unit communication link (5) is slidably connected between energy storage units via a wireless module, and the energy state synchronization trigger (6) is fixed in the middle of the link 5. This structure is beneficial for realizing energy-oriented link reset and promoting energy storage balance.

[0027] The strategy library (12) of the iterative interruption recovery module (1) stores a mapping table between routing labels and recovery strategies. The mapping table maps different combinations of routing labels to corresponding iterative continuation schemes. The iterative continuation scheme includes the selection of the iteration start point, the adjustment of the iteration direction, and the setting of the iteration termination condition. After receiving the routing label transmitted by the neighboring energy storage unit, the energy router (2) transmits the routing label to the iterative interruption recovery module (1). The iterative interruption recovery module (1) finds the corresponding iterative continuation scheme according to the mapping table and executes the scheme. This mapping is beneficial for extending interruption recovery to a distributed structure and improving the overall system stability.

[0028] The energy router (2) is equipped with a load balancing calculation unit (22). This load balancing calculation unit (22) calculates the energy allocation ratio based on the routing label and the state of charge of adjacent energy storage units. The energy allocation ratio is used to guide the distribution of energy flow information between local energy storage units and neighboring energy storage units. The load balancing calculation unit (22) transmits the energy allocation ratio to the routing control module (23) of the energy router (2). The routing control module (23) adjusts the routing path of the energy flow according to the energy allocation ratio, so that the energy generated by local photovoltaic fluctuations flows preferentially to the neighboring energy storage units with lower state of charge, thereby achieving energy-oriented load balancing. The load balancing calculation unit (22) is embedded inside the energy router (2) through a rotating connection, and the routing control module (23) is located on its right side. This calculation unit is beneficial for spontaneously balancing the state of charge and optimizing the implementation of energy routing in interruption scenarios.

[0029] Reference Figures 1 to 5 In a complete embodiment, when the photovoltaic power generation fluctuation causes a communication interruption, the energy router (2) stores the fluctuation information through a multi-level cache queue (21) and transmits it to the iterative interruption recovery module (1) via a two-way data interaction channel (3). After the interruption type identification unit (11) identifies it as a periodic interruption, it selects a segmented iterative recovery strategy from the strategy library (12) and simultaneously calculates the step size adaptive adjuster (4) to adjust the step size according to the priority of the routing data weight allocation module (41). After the neighboring unit communication link (5) is reset by the energy status synchronization trigger (6), the load balancing calculation unit (22) calculates the allocation ratio to achieve energy balance. This overall collaboration ensures the continuity and optimization of energy storage coordination management, and the beneficial effects include improved system response speed and energy utilization. One variation is to change the link reset procedure to wired backup, but this embodiment uses wireless to enhance flexibility.

[0030] It should be noted that, in this document, relational terms such as "first" and "second" are used merely 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. 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 apparatus that includes the element.

[0031] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A photovoltaic power generation power control and energy storage coordinated management system, characterized in that, include: Iterative interruption recovery module (1), the iterative interruption recovery module (1) is based on the asynchronous alternating direction multiplier method to realize iterative continuation; Energy router (2), the energy router (2) is used to route energy flow information; The energy router (2) is equipped with a multi-level cache queue (21), which stores energy flow information in layers according to the photovoltaic fluctuation frequency; A bidirectional data interaction channel (3) is provided between the multi-level cache queue (21) and the iterative interruption recovery module (1). The iterative interruption recovery module (1) reads the historical fluctuation trend data in the multi-level cache queue (21) through the bidirectional data interaction channel (3). The iterative interrupt recovery module (1) is equipped with an interrupt type identification unit (11). The interrupt type identification unit (11) automatically identifies the interrupt type and selects the corresponding recovery strategy according to the fluctuation pattern in the multi-level cache queue (21). The recovery strategy is stored in the strategy library (12) of the iterative interrupt recovery module (1). When communication is interrupted, the energy router (2) transmits the last available energy flow information and historical fluctuation trend data to the iterative interruption recovery module (1) through the bidirectional data interaction channel (3). The iterative interruption recovery module (1) triggers the corresponding recovery strategy according to the received data to support the iteration continuation. The system also includes a calculation step size adaptive regulator (4), which has a routing data weight allocation module (41) embedded inside. The routing data weight allocation module (41) is connected to the energy router (2), and the energy router (2) transmits link quality parameters to the routing data weight allocation module (41). The routing data weight allocation module (41) dynamically adjusts the calculation priority of each energy storage unit according to the link quality parameters, and the calculation step size adaptive adjuster (4) adjusts the step size of the routing data according to the adjusted calculation priority. The routing data weight allocation module (41) is also equipped with a link recovery time prediction unit (42), which predicts the link recovery time based on the link quality parameters and affects the convergence path of the asynchronous alternating direction multiplier method.

2. The energy storage coordinated management system for photovoltaic power generation control according to claim 1, characterized in that, The multi-level cache queue (21) includes a high-frequency fluctuation cache layer (211), a medium-frequency fluctuation cache layer (212), and a low-frequency fluctuation cache layer (213). The high-frequency fluctuation buffer layer (211) stores energy flow information where the photovoltaic fluctuation period is less than a preset first threshold, the medium-frequency fluctuation buffer layer (212) stores energy flow information where the photovoltaic fluctuation period is between the preset first threshold and the preset second threshold, and the low-frequency fluctuation buffer layer (213) stores energy flow information where the photovoltaic fluctuation period is greater than the preset second threshold. The interruption type identification unit (11) extracts fluctuation feature parameters from the high-frequency fluctuation buffer layer (211), the medium-frequency fluctuation buffer layer (212) and the low-frequency fluctuation buffer layer (213), respectively. The fluctuation feature parameters include fluctuation amplitude, fluctuation frequency and fluctuation duration. The interruption type identification unit (11) classifies interruption types into instantaneous interruption, periodic interruption, and continuous interruption according to the combination pattern of fluctuation characteristic parameters; The strategy library (12) stores corresponding recovery strategies for different interrupt types. The recovery strategy for the instantaneous interrupt is fast iterative recovery, the recovery strategy for the periodic interrupt is segmented iterative recovery, and the recovery strategy for the continuous interrupt is degraded iterative recovery.

3. The energy storage coordinated management system for photovoltaic power generation control according to claim 1, characterized in that, The bidirectional data interaction channel (3) includes an uplink data path (31) and a downlink data path (32). The uplink data path (31) is used to transmit data in the multi-level buffer queue (21) to the iterative interrupt recovery module (1), and the downlink data path (32) is used to transmit the recovery command of the iterative interrupt recovery module (1) to the energy router (2). The energy router (2) adjusts the routing priority of energy flow information according to the recovery command. The uplink data path (31) is equipped with a data compression unit (311), which compresses historical fluctuation trend data to reduce transmission delay. The downlink data path (32) is equipped with an instruction parsing unit (321), which parses the recovery instruction into routing adjustment parameters that can be executed by the energy router (2).

4. The energy storage coordinated management system for photovoltaic power generation control according to claim 1, characterized in that, The link quality parameters include link transmission delay, link packet loss rate, and link bandwidth utilization. The routing data weight allocation module (41) allocates time weights to each energy storage unit based on the link transmission delay, wherein the time weights are inversely proportional to the link transmission delay; allocates reliability weights to each energy storage unit based on the link packet loss rate, wherein the reliability weights are inversely proportional to the link packet loss rate; and allocates load weights to each energy storage unit based on the link bandwidth occupancy rate, wherein the load weights are inversely proportional to the link bandwidth occupancy rate. The calculation priority is obtained by weighted summation of the time weight, the reliability weight, and the load weight.

5. The photovoltaic power generation control energy storage coordinated management system according to claim 4, characterized in that, The link recovery time prediction unit (42) is equipped with a historical link database (421). The historical link database (421) stores historical link quality parameters and corresponding actual recovery times; The link recovery time prediction unit (42) matches the current link quality parameters with the historical link quality parameters in the historical link database (421) and predicts the current link recovery time based on the matching results; The link recovery time prediction unit (42) transmits the predicted link recovery time to the calculation step size adaptive adjuster (4). The adaptive step size adjuster (4) adjusts the iteration step size of the asynchronous alternating direction multiplier method according to the predicted link recovery time. When the predicted link recovery time is short, the iteration step size is increased, and when the predicted link recovery time is long, the iteration step size is decreased.

6. The energy storage coordinated management system for photovoltaic power generation control according to claim 1, characterized in that, The system also includes: Neighboring unit communication link (5) and energy state synchronization trigger (6); The neighboring unit communication link (5) connects adjacent energy storage units; The energy state synchronization trigger (6) monitors the state of charge difference between adjacent energy storage units. It is equipped with a difference comparison unit (61). The difference comparison unit (61) compares the state of charge difference with a preset threshold. When the state of charge difference exceeds the preset threshold, the energy state synchronization trigger (6) activates the link reset procedure. The link reset procedure includes a link disconnection step, a parameter reconfiguration step, and a link re-establishment step. During the link reset process, the energy router (2) encodes the local photovoltaic fluctuation characteristics into a routing label. The routing label includes a fluctuation amplitude identifier, a fluctuation frequency identifier, and a fluctuation phase identifier. The routing label is transmitted to the neighboring energy storage unit along with the energy flow information through the re-established neighboring unit communication link (5).

7. The photovoltaic power generation control energy storage coordinated management system according to claim 1, characterized in that, The strategy library (12) of the iteration interruption recovery module (1) stores a mapping table between routing labels and recovery strategies. The mapping table maps different combinations of routing labels to corresponding iteration continuation schemes. The iteration continuation schemes include iteration start point selection, iteration direction adjustment and iteration termination condition setting. After receiving the routing label transmitted by the neighboring energy storage unit, the energy router (2) transmits the routing label to the iteration interruption recovery module (1). The iteration interruption recovery module (1) searches for the corresponding iteration continuation scheme according to the mapping relationship table and executes the scheme.

8. The energy storage coordinated management system for photovoltaic power generation control according to claim 1, characterized in that, The energy router (2) is equipped with a load balancing calculation unit (22): The load balancing calculation unit (22) calculates the energy allocation ratio based on the routing label and the state of charge of adjacent energy storage units. The energy allocation ratio is used to guide the allocation of energy flow information between local energy storage units and neighboring energy storage units. The load balancing calculation unit (22) transmits the energy allocation ratio to the routing control module (23) of the energy router (2). The routing control module (23) adjusts the routing path of the energy flow according to the energy allocation ratio, so that the energy generated by local photovoltaic fluctuations flows to the neighboring energy storage unit with a lower state of charge, thereby achieving energy-oriented load balancing.

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