Charging pile cross-platform remote management and scheduling method and system

Abstract

The application discloses a charging pile cross-platform remote management and scheduling method and system, relates to the technical field of charging pile cross-platform management, and specifically comprises the following steps: in the case of scheduling retry, the interactive fragment of the corresponding charging pile in the scheduling track sequence is extracted based on the time sequence identification string, the interactive fragment is subjected to time sequence reorganization and conflict resolution processing, the charging pile available state evolution sequence is formed, and the available state of the charging pile is determined; the state constraint sequence is constructed based on the charging pile available state evolution sequence, the state constraint sequence is embedded into the scheduling input sequence, the original state fragment in the scheduling input sequence is subjected to consistency correction and replacement, and the updated scheduling input sequence is formed. The application solves the problem that the charging pile available state is invalid under the scheduling retry condition, the scheduling object cannot be reselected, the scheduling object reconstruction based on the state dynamic update is realized, and the scheduling accuracy and success rate are improved.

Description

Technical Field

[0001] This invention relates to the field of cross-platform management technology for charging piles, and specifically to a cross-platform remote management and scheduling method and system for charging piles. Background Technology

[0002] Cross-platform remote management and scheduling of charging piles refers to a technical method that, within a unified cloud or platform system, constructs a management architecture compatible with various device types, communication protocols, and operating environments. This enables centralized access, status monitoring, control command issuance, and coordinated allocation of charging tasks for charging piles distributed across different geographical locations. This technology typically relies on IoT communication technology and cloud computing platforms. Charging piles from different manufacturers or using different protocols are standardized at the access layer. Through protocol adaptation and data conversion mechanisms, unified data modeling and interoperability of heterogeneous devices are achieved. On this basis, the platform side uses a remote management module to collect and monitor the charging pile's operating status, current and voltage information, and charging progress in real time, supporting remote start / stop control, parameter configuration, and anomaly alarm handling. Simultaneously, at the scheduling level, the system allocates and schedules charging tasks based on user charging requests, device availability, and preset strategies, completing processes such as task issuance, execution feedback, and result recording. The overall implementation process typically includes multiple stages such as device access and authentication, communication protocol adaptation, data acquisition and processing, remote control command interaction, scheduling strategy execution, and operational result feedback, thus forming a complete cross-platform remote management and scheduling technology system.

[0003] The existing technology has the following shortcomings: During the cross-platform remote management and scheduling of charging piles, when no execution feedback is received after the remote management and scheduling command is sent to the target charging pile, a scheduling retry process is triggered. At this time, in order to ensure the continuity of scheduling, the system usually continues to resend the command using the charging pile object selected during the first scheduling, without re-acquiring the current availability status of the charging pile for scheduling calculation. Since the charging pile may be occupied by other requests or its operating status may change during the time interval between the scheduling command being sent and the retry being triggered, the availability status of the charging pile on which the first scheduling was based has become invalid. Existing technology cannot reselect the scheduling object based on the availability status of the charging pile in the case of scheduling retry during the cross-platform remote management and scheduling process. This will cause the scheduling retry to still apply to unavailable or changed charging piles, which will lead to scheduling execution failure, increased invalid interactions, and a decrease in the overall scheduling success rate.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a cross-platform remote management and scheduling method and system for charging piles to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a cross-platform remote management and scheduling method for charging piles, specifically including the following steps: S1. Assign a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and record the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. Determine whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. S2. In the event of a scheduling retry, the interaction segment of the corresponding charging pile in the scheduling trajectory sequence is extracted based on the time sequence identifier string, and the interaction segment is reorganized in time and conflict resolution is performed to form the charging pile availability state evolution sequence to determine the charging pile availability state. S3. Construct a state constraint sequence based on the available state evolution sequence of charging piles, embed the state constraint sequence into the scheduling input sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence, and form an updated scheduling input sequence. S4. Based on the updated scheduling input sequence, constrain and filter the state change characteristics in the charging pile availability state evolution sequence and re-sort the priority to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. S5. The scheduling object sequence and the scheduling trajectory sequence are associated and updated, and subsequent changes in the charging pile status are continuously written into the scheduling trajectory sequence. The scheduling input sequence and the scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

[0007] Preferably, S1 is as follows: Based on the generation time order of remote management and scheduling instructions in the cross-platform remote management and scheduling process and the transmission order in the cross-platform remote management and scheduling link, the remote management and scheduling instructions are sequentially encoded to generate a time sequence identifier string corresponding to the generation time and transmission path, and the time sequence identifier string is embedded in the remote management and scheduling instructions to form an identifiable instruction. After the remote management and scheduling command is sent to the charging pile, the response behavior generated by the charging pile is bound with the corresponding time sequence identifier string, and the command sending behavior and response behavior are arranged item by item according to the order of the time sequence identifier string. Each command sending behavior and corresponding response behavior are combined and written into the same sequence position to form a continuously arranged scheduling trajectory sequence. The command sending behavior and response behavior corresponding to each time sequence identifier string are matched one by one along the arrangement order of the scheduling trajectory sequence. When there is a command sending behavior that does not match the corresponding response behavior and a new time sequence identifier string corresponding to the same remote management scheduling command appears in the subsequent arrangement position, the command sending behavior corresponding to the new time sequence identifier string is determined as a scheduling retry behavior, thereby determining the situation of scheduling retry of the charging pile.

[0008] Preferably, S2 specifically includes the following steps: S201. In the event of a scheduling retry, the interaction segments of the corresponding charging pile in the scheduling trajectory sequence are extracted based on the timing identifier string. According to the association between the timing identifier string and the charging pile identifier, the instruction sending behavior and response behavior corresponding to the same charging pile are selected in the scheduling trajectory sequence, and a continuous set of interaction segments is formed according to the continuity of the timing identifier string. S202. Perform time-series reorganization and conflict resolution on the set of interaction segments. Rearrange the set of interaction segments according to the order of the time sequence identifier strings. Resolve conflicts between interaction records with different response behaviors corresponding to multiple instruction sending behaviors in the same time interval. By retaining the response behaviors with later time sequence and removing conflicting response behaviors, a conflict-free time-series reorganized interaction segment sequence is formed. S203. Extract the state change information in each arrangement position based on the temporal reorganization interaction fragment sequence, and connect them sequentially according to the arrangement order to form the charging pile available state evolution sequence. Determine the charging pile available state by reading the state information corresponding to the end position in the charging pile available state evolution sequence.

[0009] Preferably, S203 is as follows: Based on the temporal reassembly of interactive fragment sequences, the instruction sending behavior and response behavior in each arrangement position are analyzed item by item. According to the preset state mapping relationship, the behavior data in each arrangement position is converted into the corresponding state change information, and a one-to-one mapping relationship is established between the state change information and the corresponding arrangement position. The state change information in each arrangement position is sequentially connected according to the arrangement order, and the state change information in adjacent arrangement positions is spliced ​​together in turn to form a charging pile available state evolution sequence arranged continuously in time order, while keeping the original order of the state change information unchanged during the connection process; After forming the evolution sequence of the available states of the charging pile, the state change information corresponding to the end position in the sequence is located and extracted, and the state change information corresponding to the end position is used as the available state of the charging pile.

[0010] Preferably, S3 specifically includes the following steps: S301. Based on the available state evolution sequence of charging piles, each state change information is broken down item by item according to the order of arrangement, and the corresponding state constraint elements are extracted from each state change information according to the preset state constraint generation relationship. The state constraint elements are then combined in order of arrangement to form a state constraint sequence. S302. After forming the state constraint sequence, embed the state constraint sequence into the scheduling input sequence according to the arrangement structure of the scheduling input sequence, align each state constraint element in the state constraint sequence with the corresponding arrangement position in the scheduling input sequence, and establish a correspondence between the state constraint element and the scheduling input sequence element at the corresponding arrangement position. S303. Based on the state constraint sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence. Correct each original state segment in the scheduling input sequence that does not conform to the corresponding state constraint element, and replace the corrected original state segment with the corresponding state constraint element. Recombine all elements according to the arrangement order of the scheduling input sequence to form an updated scheduling input sequence.

[0011] Preferably, S302 is as follows: After forming the state constraint sequence, the index order of each arrangement position is obtained according to the arrangement structure of the scheduling input sequence, and the position mapping of each state constraint element in the state constraint sequence is performed according to the index order, and each state constraint element is assigned to the mapping position set that corresponds one-to-one with the arrangement position of the scheduling input sequence. The state constraint sequence is embedded into the scheduling input sequence based on the mapping position set. Each state constraint element is written into the corresponding arrangement position of the scheduling input sequence one by one, while keeping the original arrangement structure in the scheduling input sequence unchanged, so that the state constraint elements and the elements of the scheduling input sequence form a corresponding relationship in the same arrangement position. After embedding is completed, consistency checks are performed on each position in the scheduling input sequence. Elements that do not meet the correspondence are marked according to the correspondence between the state constraint elements and the elements in the scheduling input sequence, and the association between the marked position and the corresponding state constraint element is kept unchanged.

[0012] Preferably, S303 is as follows: Based on the state constraint sequence, the original state segments in the scheduling input sequence are compared item by item. According to the arrangement order of the scheduling input sequence, the original state segment in each position is matched with the state constraint element at the corresponding position, and the original state segment that does not meet the state constraint element is marked. Perform consistency correction and replacement on the original state fragments after identification. Adjust the content of the original state fragments that do not meet the conditions according to the corresponding state constraint elements, and replace the adjusted original state fragments with the corresponding state constraint elements, while keeping the arrangement position unchanged during the replacement process. After completing the consistency correction and replacement, the elements in all positions are recombined according to the order of the scheduling input sequence. The replaced elements are then connected sequentially to form a continuous arrangement structure, thus obtaining the updated scheduling input sequence.

[0013] Preferably, S4 is as follows: Based on the updated scheduling input sequence, the state change features in the available state evolution sequence of the charging pile are analyzed item by item, and each state change feature is compared with the state constraint elements in the corresponding arrangement position in the scheduling input sequence. Parts of the state change features that are inconsistent with the corresponding state constraint element identifier are deleted, and parts of the state change features that are consistent with the corresponding state constraint element identifier are retained, forming a set of filtered state change features. After forming the set of state change features after screening, the set of state change features is re-sorted according to the order and position of each state change feature in the evolution sequence of available charging pile states. The corresponding charging piles are sorted according to the order of their positions in the evolution sequence of available charging pile states, forming a sequence of charging piles arranged by priority. Based on the priority-arranged charging pile sequence, the scheduling object is reselected according to the availability status of the charging pile. The status change characteristics of each charging pile are read in sequence according to the priority order, and the status change characteristics of the corresponding charging pile are extracted from the filtered status change characteristic set. The extracted charging piles are connected in sequence according to the reading order to generate a scheduling object sequence.

[0014] Preferably, S5 is as follows: The scheduling object sequence and the scheduling trajectory sequence are associated and updated. The identifiers of each charging pile are extracted according to the arrangement order of the scheduling object sequence. Based on the corresponding time sequence identifier string in the scheduling trajectory sequence, each charging pile identifier is written into the same arrangement position in the scheduling trajectory sequence as the corresponding instruction sending behavior. At the same time, the correspondence between the charging pile identifier and the time sequence identifier string is established in the same arrangement position, forming a scheduling trajectory sequence containing the mapping relationship of the scheduling object sequence. After completing the association update, subsequent charging pile status changes are continuously written into the scheduling trajectory sequence. The subsequent charging pile status changes are sequentially appended according to the time sequence identifier string. The newly added status changes are written to the end of the scheduling trajectory sequence according to the order of the time sequence identifier string. Each status change is compared item by item along the arrangement order of the scheduling trajectory sequence. The status constraint elements corresponding to the status changes are written into the corresponding arrangement position of the scheduling input sequence. At the same time, the scheduling object sequence is rearranged according to the arrangement position of the status changes in the scheduling trajectory sequence. Thus, the scheduling input sequence and scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

[0015] Preferably, the cross-platform remote management and scheduling system for charging piles includes a time sequence identifier construction module, a state evolution analysis module, a constraint input reconstruction module, a scheduling object decision module, and a scheduling feedback control module; The timing identifier construction module assigns a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and records the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. It then determines whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. The state evolution analysis module, in the event of a scheduling retry, extracts the interaction segments of the corresponding charging piles in the scheduling trajectory sequence based on the time sequence identifier string, and performs time sequence reorganization and conflict resolution on the interaction segments to form a charging pile available state evolution sequence to determine the available state of the charging pile. The constraint input reconstruction module constructs a state constraint sequence based on the available state evolution sequence of the charging pile, embeds the state constraint sequence into the scheduling input sequence, performs consistency correction and replacement on the original state segments in the scheduling input sequence, and forms an updated scheduling input sequence. The scheduling object decision module performs constraint filtering and priority reconstruction sorting on the state change characteristics in the charging pile availability state evolution sequence based on the updated scheduling input sequence, so as to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. The scheduling feedback and control module associates and updates the scheduling object sequence with the scheduling trajectory sequence, and continuously writes subsequent changes in the charging pile status into the scheduling trajectory sequence. Based on the changes in the scheduling trajectory sequence, it cyclically corrects the scheduling input sequence and the scheduling object sequence.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention addresses the issues of state failure and inability to dynamically update scheduling objects during scheduling retry scenarios in cross-platform remote management and scheduling of charging piles. It constructs a scheduling trajectory sequence based on a time-series identifier string to accurately identify scheduling retry behavior. Furthermore, it extracts interaction fragments, reassembles the time sequence, and resolves conflicts to form an evolution sequence of the available state of the charging pile, thus replacing single-point state determination with continuous state changes and improving the accuracy of state acquisition. Building upon this, it transforms the available state evolution sequence into a state constraint sequence and embeds it into the scheduling input sequence, achieving structured correction of the original scheduling input. This ensures that the scheduling basis aligns with the actual operating state. Constraint filtering and priority reconstruction sorting then complete the reselection of scheduling objects, preventing scheduling retry from continuously affecting unavailable or state-changed charging piles. Simultaneously, by associating and updating the scheduling object sequence with the scheduling trajectory sequence and continuously writing subsequent state changes, it achieves cyclical correction of the scheduling input sequence and scheduling object sequence, forming a dynamic closed-loop scheduling process. This allows the scheduling strategy to adjust in real time according to changes in the charging pile state, thereby improving the accuracy and success rate of scheduling execution, reducing invalid interactions, and enhancing the overall stability and response efficiency of cross-platform remote management and scheduling. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a schematic diagram of the process of the present invention.

[0019] Figure 2 This is a schematic diagram of the modules of the present invention. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0021] This invention provides, for example Figure 1 The cross-platform remote management and scheduling method for charging piles shown includes the following steps: S1. Assign a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and record the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. Determine whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. In this embodiment, S1 specifically refers to: Based on the generation time order of remote management and scheduling instructions in the cross-platform remote management and scheduling process and the transmission order in the cross-platform remote management and scheduling link, the remote management and scheduling instructions are sequentially encoded to generate a time sequence identifier string corresponding to the generation time and transmission path, and the time sequence identifier string is embedded in the remote management and scheduling instructions to form an identifiable instruction. After the remote management and scheduling command is sent to the charging pile, the response behavior generated by the charging pile is bound with the corresponding time sequence identifier string, and the command sending behavior and response behavior are arranged item by item according to the order of the time sequence identifier string. Each command sending behavior and corresponding response behavior are combined and written into the same sequence position to form a continuously arranged scheduling trajectory sequence. The command sending behavior and response behavior corresponding to each time sequence identifier string are matched one by one along the arrangement order of the scheduling trajectory sequence. When there is a command sending behavior that does not match the corresponding response behavior and a new time sequence identifier string corresponding to the same remote management scheduling command appears in the subsequent arrangement position, the command sending behavior corresponding to the new time sequence identifier string is determined as a scheduling retry behavior, thereby determining the situation of scheduling retry of the charging pile.

[0022] In cross-platform remote management and scheduling, sequential encoding can be achieved by introducing unified timestamp collection and link tagging records on the scheduling server. For example, in a real-world experimental environment, scheduling requests from both platform A and platform B exist simultaneously in an urban public charging network. A charging pile receives a start charging command from platform A at 10:00:01 and a power adjustment command from platform B at 10:00:03. In this case, the generation time, platform source, and link node number can be combined into an encoding field. For example, “100001-A-01” and “100003-B-02” can be constructed as identifiers and embedded in the scheduling command for transmission, thus forming identifier data with a clear time sequence and path source. This can be achieved by adding an identifier field to the scheduling command data structure. The specific calculation process involves collecting the current millisecond-level time and combining it with the link node identifier to ensure that the identifier has global uniqueness and sequence. This is done to solve the problem of complex command sources and difficulty in unifying the execution order in cross-platform scheduling, providing a foundation for subsequent behavior analysis.

[0023] After the remote management scheduling command is sent to the charging pile, the return data from the charging pile can be captured in the communication callback interface and associated with the corresponding identifier for storage. For example, in the same experimental environment, the response to the start command sent at 10:00:01 returns "charging started" at 10:00:02, while the power adjustment command sent at 10:00:03 does not receive a response. In this case, "100001-A-01" can be associated with "charging started", and "100003-B-02" can be associated with an empty response. This type of data can be written into an array structure in the order of the identifiers, for example, forming an arrangement structure of [send 100001-A-01 → successful response, send 100003-B-02 → no response]. The specific implementation can be accomplished by combining key-value pair mapping with a sequential container. First, establish the mapping relationship between the identifier and the response, and then sort and write the sequence according to the time field in the identifier. This can ensure that the command sending and response behavior are combined and expressed in the same position, thereby forming a complete scheduling trajectory.

[0024] Following the formed scheduling trajectory sequence, scheduling retries can be identified by traversing the sequence and checking each item to see if there is a sending action without a corresponding response, and by detecting whether the same instruction is sent again later. For example, in the above experiment, if the same power adjustment instruction as "100003-B-02" is sent again at 10:00:05 and a new identifier "100005-B-03" is generated, then the sequence will show the continuous features of "100003-B-02 no response" and "100005-B-03 sending". At this time, a logical judgment can be made: when a certain identifier corresponds to a sending action but the response is empty and a new identifier of the same type of instruction appears later, the behavior corresponding to the new identifier is determined to be a retry behavior. Specifically, this can be achieved by traversing the array and comparing the instruction type field with the identifier order field, which can accurately identify repeated scheduling behavior triggered by no response.

[0025] Remote management and scheduling commands can be understood as control data units issued by the platform to the charging pile. The cross-platform remote management and scheduling process represents the operational environment where different platforms jointly participate in scheduling. The generation time sequence indicates the chronological order of command creation. The cross-platform remote management and scheduling link represents the transmission path of the command from the platform to the charging pile. The transmission order indicates the flow order of the command in the link. Sequential encoding processing represents numbering the commands based on time and path. The time sequence identifier string represents a unique identifier containing time and path information. Identified commands represent scheduling commands with embedded identifiers. The response behavior generated by the charging pile represents the data returned by the device after executing the command. Binding represents associating the response with the identifier. The sequential relationship of the timing identifier strings indicates the chronological order of the identifiers. The instruction sending behavior indicates the action of issuing the instruction, the response behavior indicates the corresponding feedback, the same sequence position indicates the pairing position of sending and response, the consecutively arranged scheduling trajectory sequence indicates the set of behaviors ordered by time, the one-by-one matching means judging the sending and response relationship one by one, the instruction sending behavior does not match the corresponding response behavior, it means there is a situation of sending without feedback, the appearance of a new timing identifier string corresponding to the same remote management scheduling instruction in the subsequent arrangement position indicates that the same type of instruction is sent again, the instruction sending behavior corresponding to the new timing identifier string indicates the retransmission operation, the scheduling retry behavior indicates the scheduling action that is executed again because the previous attempt failed.

[0026] S2. In the event of a scheduling retry, the interaction segment of the corresponding charging pile in the scheduling trajectory sequence is extracted based on the time sequence identifier string, and the interaction segment is reorganized in time and conflict resolution is performed to form the charging pile availability state evolution sequence to determine the charging pile availability state. In this embodiment, S2 specifically includes the following steps: S201. In the event of a scheduling retry, the interaction segments of the corresponding charging pile in the scheduling trajectory sequence are extracted based on the timing identifier string. According to the association between the timing identifier string and the charging pile identifier, the instruction sending behavior and response behavior corresponding to the same charging pile are selected in the scheduling trajectory sequence, and a continuous set of interaction segments is formed according to the continuity of the timing identifier string. In the event of a scheduling retrieval, interaction segment extraction can be achieved by maintaining an association index table containing time sequence identifier strings and charging pile identifiers on the scheduling service side. For example, in a real experimental environment, the charging pile number is CP-01. Three remote management scheduling commands are received at 10:00:01, 10:00:03, and 10:00:06, respectively, generating corresponding time sequence identifier strings T100001, T100003, and T100006. These are recorded in the scheduling trajectory sequence as "Send T100001 → Successful Response", "Send T100003 → No Response", and "Send T100006 → Successful Response". At this point, the interaction segment can be extracted first based on... The charging pile identifier CP-01 filters out all relevant records, sorts them according to the time sequence identifier string, and then extracts them based on the continuity of the time sequence identifier string. For example, when it is detected that T100003 does not respond and T100006 is a subsequent instruction of the same type, the behavior data between T100001 and T100006 can be extracted as a whole to form an interaction fragment set. Specifically, a table structure can be established in the database with the time sequence identifier string as the primary key and the charging pile identifier as the index, and filtering can be performed by sorting by time and matching by type. This can ensure that complete and continuous behavior trajectories are extracted in the scheduling retry scenario, thereby avoiding judgment based on only a single point state.

[0027] The timing identifier string represents a unique identifier formed after encoding each remote management scheduling instruction, used to describe the temporal order and transmission path of the instruction. The scheduling trajectory sequence represents a set of instruction sending and response behaviors arranged in the order of the timing identifier string. The interaction segments corresponding to the charging piles in the scheduling trajectory sequence represent continuous behavior data related to the same charging pile selected from the sequence. The association between the timing identifier string and the charging pile identifier represents the binding of the instruction to the specific device through the identifier. The instruction sending behavior represents the record of issuing control instructions to the charging pile. The response behavior represents the feedback data of the charging pile after executing the instruction. The continuity relationship of the timing identifier string represents the sequential connection relationship between the identifiers in the time dimension. The set of continuous interaction segments represents a group of sending and response data combinations that meet the continuity relationship within the same time interval. Through the synergistic effect of these elements, the complete extraction and structured expression of the behavior before and after scheduling retry can be achieved.

[0028] S202. Perform time-series reorganization and conflict resolution on the set of interaction segments. Rearrange the set of interaction segments according to the order of the time sequence identifier strings. Resolve conflicts between interaction records with different response behaviors corresponding to multiple instruction sending behaviors in the same time interval. By retaining the response behaviors with later time sequence and removing conflicting response behaviors, a conflict-free time-series reorganized interaction segment sequence is formed. When processing a set of interaction segments, time sequence reorganization and conflict resolution can be achieved by sorting the time sequence identifier strings and combining them with time window division. For example, in a real test environment, a charging pile receives three remote management and scheduling commands of the same type within a continuous time period, with corresponding time sequence identifier strings T100010, T100012, and T100013. T100010 corresponds to a response of "startup failed," T100012 corresponds to a response of "no response," and T100013 corresponds to a response of "startup successful." First, the time sequence identifier strings are sorted according to the time field to form a sequence arranged in ascending order of time. Then, the sequence is divided into segments with fixed time intervals. In a time interval, when multiple command sending behaviors and their responses are detected with differences within the same time interval, the response behaviors are compared in chronological order, and the later response behavior is taken as the valid record. For example, in this example, the "startup successful" corresponding to T100013 is retained, and the conflict response records corresponding to T100010 and T100012 are removed, finally obtaining a conflict-free sequence containing only "send T100013 → response successful". This implementation can be achieved by grouping the sorted data and performing time comparison within each group, thereby ensuring that only the final valid execution result is retained in the case of multiple scheduling superposition, and avoiding interference from old responses to state judgment.

[0029] Temporal reordering refers to re-sorting the set of interaction segments based on the time information contained in the temporal identifier string, so that the data is arranged in the actual order of occurrence. Conflict resolution refers to filtering records with multiple response results within the same time interval. The order relationship of the temporal identifier string indicates the temporal correspondence between different identifiers. Interaction records with multiple command sending behaviors corresponding to different response behaviors within the same time interval indicate the situation of multiple scheduling initiations to the same charging pile in a short period of time with inconsistent return results. Conflict resolution means filtering out a valid response from these inconsistent records. The response behavior with a later time sequence indicates the feedback record generated last in the time dimension. Conflicting response behavior indicates historical response data that has been judged to be invalid. The conflict-free temporal reordered interaction segment sequence indicates a continuous data sequence that retains only a single valid response result after sorting and filtering. By combining these elements, complex multiple scheduling behaviors can be transformed into a clear and consistent state expression.

[0030] S203. Extract the state change information in each arrangement position based on the temporal reorganization interaction fragment sequence, and connect them sequentially according to the arrangement order to form the charging pile available state evolution sequence. Determine the charging pile available state by reading the state information corresponding to the end position in the charging pile available state evolution sequence.

[0031] In this embodiment, S203 specifically refers to: Based on the temporal reassembly of interactive fragment sequences, the instruction sending behavior and response behavior in each arrangement position are analyzed item by item. According to the preset state mapping relationship, the behavior data in each arrangement position is converted into the corresponding state change information, and a one-to-one mapping relationship is established between the state change information and the corresponding arrangement position. The state change information in each arrangement position is sequentially connected according to the arrangement order, and the state change information in adjacent arrangement positions is spliced ​​together in turn to form a charging pile available state evolution sequence arranged continuously in time order, while keeping the original order of the state change information unchanged during the connection process; After forming the evolution sequence of the available states of the charging pile, the state change information corresponding to the end position in the sequence is located and extracted, and the state change information corresponding to the end position is used as the available state of the charging pile.

[0032] When processing a sequence of temporally reconstructed interactive fragments, a behavior parsing rule table can be established to convert each instruction sending behavior and response behavior into state change information. For example, in a real test environment, a charging pile might be recorded as "send start command → response failure", "send start command → response success", and "send stop command → response success" within a continuous time period. A preset mapping relationship can be used to convert "send start command and response failure" into "not started", "send start command and response success" into "started", and "send stop command and response success" into "stopped". The data is then parsed item by item according to its position in the sequence, converting each behavior data into corresponding state change information. The position index of each state change information is recorded, thus forming a structure where state change information corresponds one-to-one with its position. This transforms complex behavior data into a unified state description, facilitating subsequent processing.

[0033] After completing the item-by-item analysis, the state change information can be sequentially connected according to the arrangement order. For example, in the experimental data above, the state change information is "not started → started → stopped". By traversing the arrangement positions and splicing them in order, a continuous state sequence can be formed. At the same time, the original arrangement order is kept unchanged during the splicing process to avoid state logic errors caused by order adjustment. This can be achieved by array or linked list structure, written in the order of index, thus forming a complete evolution sequence of the available state of the charging pile. This can reflect the complete change path of the charging pile from the initial state to the current state.

[0034] After forming the evolution sequence of the available state of the charging pile, the final state can be extracted by locating the last position in the sequence. For example, in the above sequence "not started → started → stopped", the last position corresponds to "stopped". The state corresponding to this position can be directly read as the current available state of the charging pile. This can be achieved by obtaining the sequence length and accessing the last index position. This ensures that the latest state is selected, thus accurately reflecting the current availability of the charging pile.

[0035] In this process, the temporal reorganization interaction fragment sequence represents the set of behavioral data after sorting and conflict handling; the instruction sending and response behaviors in each arrangement position represent the operation and feedback corresponding to each time point; item-by-item parsing represents the individual processing of data at each position; the preset state mapping relationship represents the corresponding rules for converting behavioral data into states; behavioral data represents the original sending and response records; state change information represents the converted state description; one-to-one mapping relationship represents the correspondence between state and position; sequential connection represents the sequential splicing of states according to the arrangement position; the charging pile available state evolution sequence represents the set of state changes arranged in chronological order; the original order of state change information represents maintaining the original chronological order; the state change information corresponding to the last position in the arrangement order represents the last state record in the sequence; location extraction represents obtaining the data at that position through indexing; and the charging pile available state represents the final determined current state of the device.

[0036] S3. Construct a state constraint sequence based on the available state evolution sequence of charging piles, embed the state constraint sequence into the scheduling input sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence, and form an updated scheduling input sequence. In this embodiment, S3 specifically includes the following steps: S301. Based on the available state evolution sequence of charging piles, each state change information is broken down item by item according to the order of arrangement, and the corresponding state constraint elements are extracted from each state change information according to the preset state constraint generation relationship. The state constraint elements are then combined in order of arrangement to form a state constraint sequence. In this process, a two-layer mapping table for state parsing and constraint extraction can be established to achieve item-by-item decomposition and constraint construction. For example, in a real experimental environment, the available state evolution sequence of a charging pile over a period of time is "idle state → occupied state → charging state → fault state → restored idle state". Each state change information in the sequence can be decomposed into an independent state unit. Then, each state unit is mapped according to a preset state constraint generation relationship. For example, "idle state" is mapped to "allowed scheduling constraint", "occupied state" is mapped to "prohibited scheduling constraint", "charging state" is mapped to "delayed scheduling constraint", "fault state" is mapped to "masked scheduling constraint", and "restored idle state" is mapped to "allowed scheduling constraint". Subsequently, the state constraint elements are combined in the original order to form a state constraint sequence of "allowed → prohibited → delayed → masked → allowed". Specifically, a state mapping dictionary can be established in memory and the state change information can be traversed item by item for table lookup and transformation, thereby completing the structural transformation from state change to constraint expression. The reason for doing this is to transform descriptive state information into constraint information that can participate in scheduling decisions, so that subsequent scheduling inputs have clear constraint basis.

[0037] A charging pile can be represented by a state evolution sequence, which is a set of state changes arranged in chronological order. Each state change information represents the specific operating state at each moment in the sequence. Item-by-item decomposition means that the continuous state sequence is decomposed into independent state units. The preset state constraint generation relationship represents the set of mapping rules between states and constraints. The state constraint element represents the constraint identifier obtained by converting the state change information. The state constraint sequence represents the set of constraints formed by combining them in the original order. Through the synergistic effect of these elements, the original state change process can be transformed into a structured constraint expression sequence, providing basic data support for subsequent scheduling input correction.

[0038] S302. After forming the state constraint sequence, embed the state constraint sequence into the scheduling input sequence according to the arrangement structure of the scheduling input sequence, align each state constraint element in the state constraint sequence with the corresponding arrangement position in the scheduling input sequence, and establish a correspondence between the state constraint element and the scheduling input sequence element at the corresponding arrangement position. S303. Based on the state constraint sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence. Correct each original state segment in the scheduling input sequence that does not conform to the corresponding state constraint element, and replace the corrected original state segment with the corresponding state constraint element. Recombine all elements according to the arrangement order of the scheduling input sequence to form an updated scheduling input sequence.

[0039] In this embodiment, S302 specifically refers to: After forming the state constraint sequence, the index order of each arrangement position is obtained according to the arrangement structure of the scheduling input sequence, and the position mapping of each state constraint element in the state constraint sequence is performed according to the index order, and each state constraint element is assigned to the mapping position set that corresponds one-to-one with the arrangement position of the scheduling input sequence. The state constraint sequence is embedded into the scheduling input sequence based on the mapping position set. Each state constraint element is written into the corresponding arrangement position of the scheduling input sequence one by one, while keeping the original arrangement structure in the scheduling input sequence unchanged, so that the state constraint elements and the elements of the scheduling input sequence form a corresponding relationship in the same arrangement position. After embedding is completed, consistency checks are performed on each position in the scheduling input sequence. Elements that do not meet the correspondence are marked according to the correspondence between the state constraint elements and the elements in the scheduling input sequence, and the association between the marked position and the corresponding state constraint element is kept unchanged.

[0040] When embedding state constraint sequences, position mapping can be achieved by constructing a unified index system. For example, in a real experimental environment, a scheduling input sequence contains five permutation positions, corresponding to five charging pile candidate objects, with an index order of 1 to 5. The corresponding generated state constraint sequence is "Allow, Prohibit, Delay, Mask, Allow". We can first obtain the permutation structure of the scheduling input sequence, assign a corresponding index to each permutation position, and then map the position of each state constraint element in the state constraint sequence according to the index order. For example, map "Allow" to index 1, "Prohibit" to index 2, and so on, forming a set of mapped positions containing the correspondence between indices and constraint elements. The specific implementation can be accomplished through array indexes or key-value pair structures, so that the state constraint elements and the positions in the scheduling input sequence form a one-to-one correspondence, which can ensure that the constraint information is accurately located in the subsequent embedding process.

[0041] After completing the position mapping, the state constraint sequence can be embedded into the scheduling input sequence by writing to each position. For example, in the same experiment, the initial state of the scheduling input sequence is "schedulable, schedulable, schedulable, schedulable, schedulable". During the embedding process, the sequence is written one by one according to the mapping position set. "Allowed" is written to position 1 and "prohibited" is written to position 2. In this way, without changing the original arrangement structure, each arrangement position contains the correspondence between the original element and the state constraint element. This can be achieved by adding additional fields to the original data structure or by creating a parallel array, thereby maintaining the stability of the scheduling input sequence structure while introducing constraint information.

[0042] After embedding, consistency verification can be achieved by comparing each position. For example, in the above experiment, when verifying the index 2 position, it was found that the original element was "schedulable" while the corresponding state constraint element was "prohibited". It was then determined that the correspondence was not satisfied and the position was marked, for example, as "conflict position 2". At the same time, the association between the mark and the corresponding state constraint element was kept unchanged. The specific implementation can be completed by traversing the index positions and comparing each item. The inconsistent positions are recorded in a separate mark set, thus providing a basis for subsequent correction.

[0043] The scheduling input sequence represents the set of candidate data used for scheduling computation. The permutation structure represents the arrangement of data in the sequence. The index order of each permutation position represents the position number of each data unit in the sequence. Position mapping represents the process of establishing a correspondence between state constraint elements and index positions. The mapped position set represents a data structure containing the correspondence between all positions and constraint elements. Embedding the state constraint sequence into the scheduling input sequence represents the process of introducing constraint information into the original data structure. The original permutation structure in the scheduling input sequence represents that the original permutation order remains unchanged. Consistency check represents the constraint compliance judgment for each permutation position. The correspondence between state constraint elements and scheduling input sequence elements represents the matching relationship between the two types of data at the same position. Elements that do not satisfy the correspondence represent data items that are inconsistent with the constraints. The association between the marker position and the corresponding state constraint element represents that the marker information and the constraint information maintain a fixed correspondence. Through the collaborative processing of these elements, the precise fusion of constraint information and scheduling input can be achieved.

[0044] In this embodiment, S303 specifically refers to: Based on the state constraint sequence, the original state segments in the scheduling input sequence are compared item by item. According to the arrangement order of the scheduling input sequence, the original state segment in each position is matched with the state constraint element at the corresponding position, and the original state segment that does not meet the state constraint element is marked. Perform consistency correction and replacement on the original state fragments after identification. Adjust the content of the original state fragments that do not meet the conditions according to the corresponding state constraint elements, and replace the adjusted original state fragments with the corresponding state constraint elements, while keeping the arrangement position unchanged during the replacement process. After completing the consistency correction and replacement, the elements in all positions are recombined according to the order of the scheduling input sequence. The replaced elements are then connected sequentially to form a continuous arrangement structure, thus obtaining the updated scheduling input sequence.

[0045] When processing the original state segments in the scheduling input sequence, a position alignment comparison table can be constructed to achieve item-by-item matching and judgment. For example, in a real experimental environment, a scheduling input sequence contains five permutation positions, corresponding to the original state segments "schedulable, schedulable, unschedulable, schedulable, schedulable", while the state constraint sequence is "allowed, prohibited, prohibited, allowed, masked". They can be compared one by one according to the permutation order. For example, if "schedulable" and "prohibited" are inconsistent in the second permutation position, and "unschedulable" and "prohibited" are consistent in the third permutation position, then only the second position is marked, for example, marked as "conflict position 2". Specifically, this can be achieved by traversing the array and establishing a comparison rule table to mark and record the original state segments that do not conform to the state constraint elements, thus providing a clear target for subsequent correction. The reason for doing this is to pre-screen the data positions that are inconsistent with the constraints, avoiding the computational redundancy caused by full processing.

[0046] After the identification process is completed, consistency correction and replacement of the original state fragments that do not meet the conditions can be performed by replacing the rule table. For example, in the above experiment, the original state fragment "schedulable" of "conflict position 2" is adjusted and directly replaced with the corresponding state constraint element "prohibited". The arrangement position that already meets the constraint remains unchanged. Specifically, the identification set can be traversed and the replacement operation can be performed to replace the original state fragment at the corresponding index position with the state constraint element. At the same time, it is ensured that the replacement process does not change the arrangement position order. This ensures that the corrected data fully meets the state constraint requirements, thereby eliminating the inconsistency in the original state.

[0047] After completing consistency correction and replacement, a new scheduling input sequence can be generated by sequential recombination. For example, in the above experiment, the new sequence obtained after replacement is "allow, prohibit, prohibit, allow, block". Then, the elements in all positions are connected in the original order to form a continuous arrangement structure. Specifically, the replacement array can be traversed sequentially and rewritten into the data structure to obtain the updated scheduling input sequence. This ensures that the new input data remains structurally stable and fully complies with the state constraints in terms of content.

[0048] The state constraint sequence represents the set of rules used to constrain scheduling behavior. The original state fragments in the scheduling input sequence represent the original scheduling condition data. The matching judgment represents a comparison between the original state fragments and the state constraint elements item by item. The original state fragments that do not conform to the state constraint elements represent data items that are inconsistent with the constraint rules. The identification processing represents recording the inconsistent positions. The consistency correction and replacement represents adjusting the data that does not conform to the conditions to conform to the constraints. The original state fragments that do not conform to the conditions represent the data that needs to be adjusted. The content adjustment represents the modification operation on the original data. The elements in all permutation positions represent all data units in the scheduling input sequence. The replaced elements represent the corrected data content. The continuous permutation structure represents the data form connected in the original order. The updated scheduling input sequence represents the final set of input data used for scheduling calculation.

[0049] S4. Based on the updated scheduling input sequence, constrain and filter the state change characteristics in the charging pile availability state evolution sequence and re-sort the priority to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. In this embodiment, S4 specifically refers to: Based on the updated scheduling input sequence, the state change features in the available state evolution sequence of the charging pile are analyzed item by item, and each state change feature is compared with the state constraint elements in the corresponding arrangement position in the scheduling input sequence. Parts of the state change features that are inconsistent with the corresponding state constraint element identifier are deleted, and parts of the state change features that are consistent with the corresponding state constraint element identifier are retained, forming a set of filtered state change features. After forming the set of state change features after screening, the set of state change features is re-sorted according to the order and position of each state change feature in the evolution sequence of available charging pile states. The corresponding charging piles are sorted according to the order of their positions in the evolution sequence of available charging pile states, forming a sequence of charging piles arranged by priority. Based on the priority-arranged charging pile sequence, the scheduling object is reselected according to the availability status of the charging pile. The status change characteristics of each charging pile are read in sequence according to the priority order, and the status change characteristics of the corresponding charging pile are extracted from the filtered status change characteristic set. The extracted charging piles are connected in sequence according to the reading order to generate a scheduling object sequence.

[0050] When filtering state change features, a state comparison matrix can be established to achieve item-by-item analysis and filtering. For example, in a real experimental environment, an updated scheduling input sequence is "Allow, Prohibit, Allow, Block", corresponding to four charging pile locations. The state change features extracted from the charging pile availability state evolution sequence are "Idle, Occupied, Idle, Fault". The state change features can be analyzed item by item, and "Idle" can be matched with "Allow", "Occupied" with "Prohibited", and "Fault" with "Block". Then, they can be compared item by item with the state constraint elements in the scheduling input sequence. For example, "Occupied" and "Prohibited" are consistent in the second position, and "Fault" and "Block" are consistent in the fourth position. If "Idle" is matched with "Prohibited", it is determined that the identifier is inconsistent and is deleted. Only the part with consistent identifier is retained. Finally, the filtered set of state change features is obtained, such as "Idle, Occupied, Fault". The specific implementation can be achieved by traversing the array and performing string or code matching, thereby ensuring that the data and constraints involved in scheduling are completely consistent.

[0051] After the screening is completed, priority reconstruction can be achieved by sorting by position weight. For example, in the same experiment, the set of state change features after screening corresponds to three charging piles. Their positions in the original available state evolution sequence of the charging piles are index 1, index 2, and index 4, respectively. They can be sorted according to their position order, and the positions with smaller indices can be given higher priority, thus forming a charging pile sequence arranged by priority. For example, the sorting result is "charging pile 1, charging pile 2, charging pile 4". The specific implementation can be completed by recording the original index of the state change features and performing the sorting operation. This can ensure that the charging piles with earlier state change times and those that meet the constraints are selected first.

[0052] When generating scheduling objects, the sequence of scheduling objects can be constructed by sequential reading and extraction. For example, in the above experiment, "charging pile 1, charging pile 2, charging pile 4" are read in order of priority, and the corresponding state change features are extracted from the filtered set of state change features. The corresponding charging piles are then connected in the order of reading to form the sequence of scheduling objects "charging pile 1 → charging pile 2 → charging pile 4". The specific implementation can be completed by inserting the charging pile identifiers in order through a queue structure. This ensures that the generation process of scheduling objects is consistent with the priority sorting.

[0053] The updated scheduling input sequence represents the corrected set of scheduling constraints. The available state evolution sequence of charging piles represents the set of state changes arranged in chronological order. State change features represent individual state information extracted from the sequence. Item-by-item parsing means processing each state change feature individually. State constraint elements in the scheduling input sequence represent constraint rules. Comparison processing means matching state change features with state constraint elements one by one. Parts of state change features that do not match the corresponding state constraint element identifier represent data that does not meet the constraints and are deleted. Parts of state change features that match the corresponding state constraint element identifier represent data that meets the constraints and are retained. The filtered set of state change features represents the filtered set of valid data. Priority reconstruction sorting represents the process of reordering according to the arrangement position. The charging pile sequence arranged by priority represents the sorted set of devices. The available state of charging piles represents the current state of the device. The scheduling object represents the selected device. The state change features corresponding to each charging pile represent the state information corresponding to the device. Connecting them sequentially according to the reading order represents combining data in sequence. The scheduling object sequence represents the final set of devices used for scheduling execution.

[0054] S5. The scheduling object sequence and the scheduling trajectory sequence are associated and updated, and subsequent changes in the charging pile status are continuously written into the scheduling trajectory sequence. The scheduling input sequence and the scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

[0055] In this embodiment, S5 specifically refers to: The scheduling object sequence and the scheduling trajectory sequence are associated and updated. The identifiers of each charging pile are extracted according to the arrangement order of the scheduling object sequence. Based on the corresponding time sequence identifier string in the scheduling trajectory sequence, each charging pile identifier is written into the same arrangement position in the scheduling trajectory sequence as the corresponding instruction sending behavior. At the same time, the correspondence between the charging pile identifier and the time sequence identifier string is established in the same arrangement position, forming a scheduling trajectory sequence containing the mapping relationship of the scheduling object sequence. After completing the association update, subsequent charging pile status changes are continuously written into the scheduling trajectory sequence. The subsequent charging pile status changes are sequentially appended according to the time sequence identifier string. The newly added status changes are written to the end of the scheduling trajectory sequence according to the order of the time sequence identifier string. Each status change is compared item by item along the arrangement order of the scheduling trajectory sequence. The status constraint elements corresponding to the status changes are written into the corresponding arrangement position of the scheduling input sequence. At the same time, the scheduling object sequence is rearranged according to the arrangement position of the status changes in the scheduling trajectory sequence. Thus, the scheduling input sequence and scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

[0056] When updating the sequence of scheduled objects and the sequence of scheduled trajectories, data alignment can be achieved by establishing a location index mapping table. For example, in a real experimental environment, the sequence of scheduled objects is "charging pile A, charging pile B, charging pile C", corresponding to positions 1, 2, and 3. The sequence of scheduled trajectories contains three instruction sending actions with time sequence identifiers T2001, T2002, and T2003. We can first extract the charging pile identifiers according to the order of the sequence of scheduled objects, and then update the sequence of scheduled trajectories based on the position of the instruction sending action corresponding to each time sequence identifier in the sequence of scheduled trajectories. The charging pile A is written to the corresponding position of T2001, the charging pile B is written to the corresponding position of T2002, and the charging pile C is written to the corresponding position of T2003. At the same time, the correspondence between "charging pile identifier - time sequence identifier string" is recorded at the same position, for example, forming a mapping structure of "T2001→A, T2002→B, T2003→C". The specific implementation can be completed through array subscripts or key-value pair structures, binding the scheduling object sequence with the scheduling trajectory sequence position by position, so that the scheduling object information can be embedded in the original scheduling trajectory, providing an association basis for subsequent state tracking.

[0057] After completing the associated update, dynamic updates and cyclic corrections can be achieved through append writing and sequential comparison. For example, in the same experiment, when new charging pile status changes occur in subsequent times, such as T2004 corresponding to "charging pile B status becomes occupied" and T2005 corresponding to "charging pile A status becomes idle", a new time sequence identifier string can be generated based on time and the status change can be written to the end of the scheduling trajectory sequence to form an extended sequence "T2001→A, T2002→B, T2003→C, T2004→B occupied, T2005→A idle". Then, the status changes are compared item by item along the sequence order, mapping "occupied" to "prohibited" and "idle" to "allowed", and written to the corresponding arrangement position of the scheduling input sequence. For example, the position corresponding to charging pile B is updated to "prohibited" and the position corresponding to charging pile A is updated to "allowed". At the same time, the order of the scheduling object sequence is readjusted according to the new arrangement position. For example, charging pile A is moved forward and charging pile B is moved backward to form a new scheduling object sequence. In this way, the scheduling results can be adjusted in real time after the status change occurs, ensuring that the scheduling process continuously adapts to the changes in equipment status.

[0058] The scheduling object sequence represents the set of charging piles participating in the scheduling selection; the scheduling trajectory sequence represents a time-series data structure recording scheduling instructions and state changes; the association update represents embedding the charging pile identifier into the corresponding position in the scheduling trajectory sequence and establishing a mapping relationship; the time sequence identifier string represents coded data used to identify the time sequence; the instruction sending behavior represents the record of the scheduling instruction being issued; the arrangement position represents the index position of the data in the sequence; the correspondence between the charging pile identifier and the time sequence identifier string represents the binding relationship between the device and the time node; subsequent charging pile state changes represent new state data generated after scheduling execution; sequential append represents writing data to the end of the sequence in chronological order; item-by-item comparison represents processing state changes sequentially; the state constraint element represents the constraint identifier obtained by mapping state changes; writing to the scheduling input sequence represents updating the constraint data to the scheduling input; rearranging represents adjusting the order of charging piles according to state changes; and cyclic correction represents repeating the update process after each state change, thus forming a dynamic scheduling mechanism.

[0059] like Figure 2 The charging pile cross-platform remote management and scheduling system shown includes a time sequence identifier construction module, a state evolution analysis module, a constraint input reconstruction module, a scheduling object decision module, and a scheduling feedback control module; The timing identifier construction module assigns a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and records the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. It then determines whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. The state evolution analysis module, in the event of a scheduling retry, extracts the interaction segments of the corresponding charging piles in the scheduling trajectory sequence based on the time sequence identifier string, and performs time sequence reorganization and conflict resolution on the interaction segments to form a charging pile available state evolution sequence to determine the available state of the charging pile. The constraint input reconstruction module constructs a state constraint sequence based on the available state evolution sequence of the charging pile, embeds the state constraint sequence into the scheduling input sequence, performs consistency correction and replacement on the original state segments in the scheduling input sequence, and forms an updated scheduling input sequence. The scheduling object decision module performs constraint filtering and priority reconstruction sorting on the state change characteristics in the charging pile availability state evolution sequence based on the updated scheduling input sequence, so as to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. The scheduling feedback and control module associates and updates the scheduling object sequence with the scheduling trajectory sequence, and continuously writes subsequent changes in the charging pile status into the scheduling trajectory sequence. Based on the changes in the scheduling trajectory sequence, it cyclically corrects the scheduling input sequence and the scheduling object sequence.

[0060] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or 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 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 includes one or more sets of 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. The semiconductor medium can be a solid-state drive.

[0061] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0062] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0063] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0064] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0065] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0066] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A cross-platform remote management and scheduling method for charging piles, characterized in that, Specifically, the following steps are included: S1. Assign a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and record the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. Determine whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. S2. In the event of a scheduling retry, the interaction segment of the corresponding charging pile in the scheduling trajectory sequence is extracted based on the time sequence identifier string, and the interaction segment is reorganized in time and conflict resolution is performed to form the charging pile availability state evolution sequence to determine the charging pile availability state. S3. Construct a state constraint sequence based on the available state evolution sequence of charging piles, embed the state constraint sequence into the scheduling input sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence, and form an updated scheduling input sequence. S4. Based on the updated scheduling input sequence, constrain and filter the state change characteristics in the charging pile availability state evolution sequence and re-sort the priority to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. S5. The scheduling object sequence and the scheduling trajectory sequence are associated and updated, and subsequent changes in the charging pile status are continuously written into the scheduling trajectory sequence. The scheduling input sequence and the scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

2. The cross-platform remote management and scheduling method for charging piles according to claim 1, characterized in that, S1 specifically refers to: Based on the generation time order of remote management and scheduling instructions in the cross-platform remote management and scheduling process and the transmission order in the cross-platform remote management and scheduling link, the remote management and scheduling instructions are sequentially encoded to generate a time sequence identifier string corresponding to the generation time and transmission path, and the time sequence identifier string is embedded in the remote management and scheduling instructions to form an identifiable instruction. After the remote management and scheduling command is sent to the charging pile, the response behavior generated by the charging pile is bound with the corresponding time sequence identifier string, and the command sending behavior and response behavior are arranged item by item according to the order of the time sequence identifier string. Each command sending behavior and corresponding response behavior are combined and written into the same sequence position to form a continuously arranged scheduling trajectory sequence. The command sending behavior and response behavior corresponding to each time sequence identifier string are matched one by one along the arrangement order of the scheduling trajectory sequence. When there is a command sending behavior that does not match the corresponding response behavior and a new time sequence identifier string corresponding to the same remote management scheduling command appears in the subsequent arrangement position, the command sending behavior corresponding to the new time sequence identifier string is determined as a scheduling retry behavior, thereby determining the situation of scheduling retry of the charging pile.

3. The cross-platform remote management and scheduling method for charging piles according to claim 1, characterized in that, S2 specifically includes the following steps: S201. In the event of a scheduling retry, the interaction segments of the corresponding charging pile in the scheduling trajectory sequence are extracted based on the timing identifier string. According to the association between the timing identifier string and the charging pile identifier, the instruction sending behavior and response behavior corresponding to the same charging pile are selected in the scheduling trajectory sequence, and a continuous set of interaction segments is formed according to the continuity of the timing identifier string. S202. Perform time-series reorganization and conflict resolution on the set of interaction segments. Rearrange the set of interaction segments according to the order of the time sequence identifier strings. Resolve conflicts between interaction records with different response behaviors corresponding to multiple instruction sending behaviors in the same time interval. By retaining the response behaviors with later time sequence and removing conflicting response behaviors, a conflict-free time-series reorganized interaction segment sequence is formed. S203. Extract the state change information in each arrangement position based on the temporal reorganization interaction fragment sequence, and connect them sequentially according to the arrangement order to form the charging pile available state evolution sequence. Determine the charging pile available state by reading the state information corresponding to the end position in the charging pile available state evolution sequence.

4. The cross-platform remote management and scheduling method for charging piles according to claim 3, characterized in that, S203 specifically refers to: Based on the temporal reassembly of interactive fragment sequences, the instruction sending behavior and response behavior in each arrangement position are analyzed item by item. According to the preset state mapping relationship, the behavior data in each arrangement position is converted into the corresponding state change information, and a one-to-one mapping relationship is established between the state change information and the corresponding arrangement position. The state change information in each arrangement position is sequentially connected according to the arrangement order, and the state change information in adjacent arrangement positions is spliced ​​together in turn to form a charging pile available state evolution sequence arranged continuously in time order, while keeping the original order of the state change information unchanged during the connection process; After forming the evolution sequence of the available states of the charging pile, the state change information corresponding to the end position in the sequence is located and extracted, and the state change information corresponding to the end position is used as the available state of the charging pile.

5. The cross-platform remote management and scheduling method for charging piles according to claim 1, characterized in that, S3 specifically includes the following steps: S301. Based on the available state evolution sequence of charging piles, each state change information is broken down item by item according to the order of arrangement, and the corresponding state constraint elements are extracted from each state change information according to the preset state constraint generation relationship. The state constraint elements are then combined in order of arrangement to form a state constraint sequence. S302. After forming the state constraint sequence, embed the state constraint sequence into the scheduling input sequence according to the arrangement structure of the scheduling input sequence, align each state constraint element in the state constraint sequence with the corresponding arrangement position in the scheduling input sequence, and establish a correspondence between the state constraint element and the scheduling input sequence element at the corresponding arrangement position. S303. Based on the state constraint sequence, perform consistency correction and replacement on the original state segments in the scheduling input sequence. Correct each original state segment in the scheduling input sequence that does not conform to the corresponding state constraint element, and replace the corrected original state segment with the corresponding state constraint element. Recombine all elements according to the arrangement order of the scheduling input sequence to form an updated scheduling input sequence.

6. The cross-platform remote management and scheduling method for charging piles according to claim 5, characterized in that, S302 specifically refers to: After forming the state constraint sequence, the index order of each arrangement position is obtained according to the arrangement structure of the scheduling input sequence, and the position mapping of each state constraint element in the state constraint sequence is performed according to the index order, and each state constraint element is assigned to the mapping position set that corresponds one-to-one with the arrangement position of the scheduling input sequence. The state constraint sequence is embedded into the scheduling input sequence based on the mapping position set. Each state constraint element is written into the corresponding arrangement position of the scheduling input sequence one by one, while keeping the original arrangement structure in the scheduling input sequence unchanged, so that the state constraint elements and the elements of the scheduling input sequence form a corresponding relationship in the same arrangement position. After embedding is completed, consistency checks are performed on each position in the scheduling input sequence. Elements that do not meet the correspondence are marked according to the correspondence between the state constraint elements and the elements in the scheduling input sequence, and the association between the marked position and the corresponding state constraint element is kept unchanged.

7. The cross-platform remote management and scheduling method for charging piles according to claim 5, characterized in that, S303 specifically refers to: Based on the state constraint sequence, the original state segments in the scheduling input sequence are compared item by item. According to the arrangement order of the scheduling input sequence, the original state segment in each position is matched with the state constraint element at the corresponding position, and the original state segment that does not meet the state constraint element is marked. Perform consistency correction and replacement on the original state fragments after identification. Adjust the content of the original state fragments that do not meet the conditions according to the corresponding state constraint elements, and replace the adjusted original state fragments with the corresponding state constraint elements, while keeping the arrangement position unchanged during the replacement process. After completing the consistency correction and replacement, the elements in all positions are recombined according to the order of the scheduling input sequence. The replaced elements are then connected sequentially to form a continuous arrangement structure, thus obtaining the updated scheduling input sequence.

8. The cross-platform remote management and scheduling method for charging piles according to claim 1, characterized in that, S4 specifically refers to: Based on the updated scheduling input sequence, the state change features in the available state evolution sequence of the charging pile are analyzed item by item, and each state change feature is compared with the state constraint elements in the corresponding arrangement position in the scheduling input sequence. Parts of the state change features that are inconsistent with the corresponding state constraint element identifier are deleted, and parts of the state change features that are consistent with the corresponding state constraint element identifier are retained, forming a set of filtered state change features. After forming the set of state change features after screening, the set of state change features is re-sorted according to the order and position of each state change feature in the evolution sequence of available charging pile states. The corresponding charging piles are sorted according to the order of their positions in the evolution sequence of available charging pile states, forming a sequence of charging piles arranged by priority. Based on the priority-arranged charging pile sequence, the scheduling object is reselected according to the availability status of the charging pile. The status change characteristics of each charging pile are read in sequence according to the priority order, and the status change characteristics of the corresponding charging pile are extracted from the filtered status change characteristic set. The extracted charging piles are connected in sequence according to the reading order to generate a scheduling object sequence.

9. The cross-platform remote management and scheduling method for charging piles according to claim 1, characterized in that, S5 specifically refers to: The scheduling object sequence and the scheduling trajectory sequence are associated and updated. The identifiers of each charging pile are extracted according to the arrangement order of the scheduling object sequence. Based on the corresponding time sequence identifier string in the scheduling trajectory sequence, each charging pile identifier is written into the same arrangement position in the scheduling trajectory sequence as the corresponding instruction sending behavior. At the same time, the correspondence between the charging pile identifier and the time sequence identifier string is established in the same arrangement position, forming a scheduling trajectory sequence containing the mapping relationship of the scheduling object sequence. After completing the association update, subsequent charging pile status changes are continuously written into the scheduling trajectory sequence. The subsequent charging pile status changes are sequentially appended according to the time sequence identifier string. The newly added status changes are written to the end of the scheduling trajectory sequence according to the order of the time sequence identifier string. Each status change is compared item by item along the arrangement order of the scheduling trajectory sequence. The status constraint elements corresponding to the status changes are written into the corresponding arrangement position of the scheduling input sequence. At the same time, the scheduling object sequence is rearranged according to the arrangement position of the status changes in the scheduling trajectory sequence. Thus, the scheduling input sequence and scheduling object sequence are cyclically corrected based on the changes in the scheduling trajectory sequence.

10. A cross-platform remote management and scheduling system for charging piles, used to implement the cross-platform remote management and scheduling method for charging piles as described in any one of claims 1-9, characterized in that, It includes a timing identifier construction module, a state evolution analysis module, a constraint input reconstruction module, a scheduling object decision module, and a scheduling feedback control module; The timing identifier construction module assigns a timing identifier string to each remote management and scheduling instruction generated during the cross-platform remote management and scheduling process, and records the charging pile response behavior based on the timing identifier string to form a scheduling trajectory sequence. It then determines whether the charging pile has retried the scheduling based on the matching relationship between the instruction sending behavior and the response behavior in the scheduling trajectory sequence. The state evolution analysis module, in the event of a scheduling retry, extracts the interaction segments of the corresponding charging piles in the scheduling trajectory sequence based on the time sequence identifier string, and performs time sequence reorganization and conflict resolution on the interaction segments to form a charging pile available state evolution sequence to determine the available state of the charging pile. The constraint input reconstruction module constructs a state constraint sequence based on the available state evolution sequence of the charging pile, embeds the state constraint sequence into the scheduling input sequence, performs consistency correction and replacement on the original state segments in the scheduling input sequence, and forms an updated scheduling input sequence. The scheduling object decision module performs constraint filtering and priority reconstruction sorting on the state change characteristics in the charging pile availability state evolution sequence based on the updated scheduling input sequence, so as to reselect scheduling objects according to the charging pile availability state and generate a scheduling object sequence. The scheduling feedback and control module associates and updates the scheduling object sequence with the scheduling trajectory sequence, and continuously writes subsequent changes in the charging pile status into the scheduling trajectory sequence. Based on the changes in the scheduling trajectory sequence, it cyclically corrects the scheduling input sequence and the scheduling object sequence.

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