Smart park energy management method and system

Abstract

The invention discloses a smart park energy management method and system, and particularly relates to the field of smart park energy distributed storage management, and the method comprises the steps: obtaining state data through collecting the energy state parameters of energy storage equipment, dividing the state data into equal-length time slices according to a time sequence, and storing the equal-length time slices; the power change rate, the load offset and the output difference value are counted in each equal-length time slice, and the statistical result is combined with the charging moment, the discharging moment, the power value and the write-in time to generate an operation record; according to the method, the charging power and the discharging power of the distributed energy storage equipment are uniformly planned according to the equal-length time slices, the scheduling matrix is constructed in combination with the capacity boundary condition, and the operation intentions of the equipment are synchronized before execution so as to quickly identify and eliminate the cross-node conflicts; therefore, the problems of energy exchange bus contention, storage queue blockage and log loss caused by a multi-autonomous-equipment parallel triggering strategy in a traditional scheme are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of distributed storage management of smart park energy, more particularly, the present application relates to a smart park energy management method and system. BACKGROUND

[0002] In the energy management system of the smart park, the distributed energy storage device gradually has local autonomy capability, can independently decide the charging and discharging time and power distribution according to voltage, current and load prediction parameters, and persistently stores the operation data to the distributed storage system. However, when the park power demand curve and the renewable energy output curve fluctuate sharply at the same time, multiple autonomous devices will trigger local emergency strategies in parallel, almost synchronously compete for the energy exchange bus and storage write channel. In the absence of unified plan sharing and arbitration mechanism, power distribution priority inversion, storage queue blocking and log loss problems may occur in the millisecond time window. Currently, there is a lack of a mechanism that can synchronize the operation intentions of each device in time at the decision-making front and quickly resolve cross-node conflicts. Therefore, the concurrent competition of energy and storage resources is often difficult to be perceived and processed in time, thus becoming a key bottleneck restricting the stability of smart park energy management. Therefore, it is urgent to propose a smart park energy management method and system to realize the collaborative operation of multiple autonomous energy storage devices and the scheduling of distributed storage resources. SUMMARY

[0003] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a smart park energy management method and system, which unifies the charging power and discharging power of the distributed energy storage device according to equal-length time slices, constructs a scheduling matrix combined with capacity boundary conditions, and synchronizes the operation intentions of each device before execution to quickly identify and resolve cross-node conflicts, thereby solving the problems of energy exchange bus competition, storage queue blocking and log loss caused by multiple autonomous devices triggering strategies in parallel in the traditional scheme.

[0004] To achieve the above purpose, the present application provides the following technical scheme: a smart park energy management method, comprising the following steps: S1, obtaining state data by collecting energy state parameters of the energy storage device, dividing the state data into equal-length time slices according to time sequence, and in each equal-length time slice, counting the power change rate, load offset and output difference, combining the statistical results with the charging time, discharging time, power value and write time to generate operation records; S2, obtaining trigger signals by receiving operation records and detecting energy state parameter change amount, arranging equal-length time slices from high to low according to power change rate by using difference compression algorithm, and selecting equal-length time slices with power change rate higher than a preset threshold to generate broadcast data frames; S3, obtain the running record set by receiving the local running record and the external running record, align the running record set according to the starting time of the equal-length time slice, accumulate the power value in the sliding window, compare with the upper limit of the energy exchange channel power, identify the over-limit equal-length time slice, and combine to solve the conflict priority table; S4, obtain the priority order by receiving the conflict priority table, delay the charging time or discharging time of the low-priority running record by the duration of the conflict equal-length time slice, add a delay compensation value in the writing time, and generate an adjusted running record according to the smoothing strategy; S5, obtain the cooperative execution parameter by receiving the adjusted running record, execute the charging, discharging and data writing operations in parallel, calculate the difference between the actual power and the planned power to generate a deviation curve after each operation is completed, and output the deviation curve and the storage state to the central management system.

[0005] In a preferred embodiment, in S1, the state data is obtained by collecting the energy state parameters of the energy storage device in the preset sampling interval, the energy state parameters include voltage value, current value, predicted load value and predicted output value, the state data is divided into equal-length time slices in time sequence, and each equal-length time slice is assigned a unique equal-length time slice index; The power change rate, load offset and output difference are calculated in each equal-length time slice respectively, each calculation result is bound to the corresponding equal-length time slice index, and the binding result is recorded to the equal-length time slice data table; The equal-length time slice data table is corresponded to the charging time, discharging time, power value and writing time of the energy storage device, forming a running record segment with the equal-length time slice index as the primary key and the charging and discharging parameters and calculation results as the combined fields; All running record segments are combined to generate complete running records in the time sequence of the equal-length time slice index and output.

[0006] In a preferred embodiment, in S1, the state data is obtained by collecting the energy state parameters of the energy storage device in the preset sampling interval, the energy state parameters include voltage value, current value, predicted load value and predicted output value, the state data is divided into equal-length time slices in time sequence, and each equal-length time slice is assigned a unique equal-length time slice index; The power change rate, load offset and output difference are calculated in each equal-length time slice respectively, each calculation result is bound to the corresponding equal-length time slice index, and the binding result is recorded to the equal-length time slice data table; The equal-length time slice data table is corresponded to the charging time, discharging time, power value and writing time of the energy storage device, forming a running record segment with the equal-length time slice index as the primary key and the charging and discharging parameters and calculation results as the combined fields; All running record segments are combined in time sequence according to the equal-length time slice index to generate a complete running record and output.

[0007] In a preferred embodiment, in S3, by receiving the local running record and the external running record, the two types of running records are merged in time sequence to generate a running record set, and each running record in the running record set is assigned an equal-length time slice index, while the power value and the write time are recorded to form a running record table; According to the running record table, the running record set is subjected to a start time alignment operation to aggregate equal-length time slices with the same start time, establish a mapping relationship between the equal-length time slices and the power values, and generate a power mapping table; A sliding window is set on the power mapping table, and the window is gradually slid according to the window span. The cumulative operation is performed on the power values in each window range. The cumulative result is compared with the upper limit of the energy exchange channel power. The equal-length time slice index that exceeds the power upper limit is identified and marked as an over-limit state. The equal-length time slice index that does not exceed the power upper limit is marked as a normal state, and a power comparison table is formed; The power comparison table is read, and the equal-length time slice index marked as the over-limit state is filtered therefrom, sorted according to the amplitude of the corresponding power value exceeding the power upper limit, and sorted in the equal-length time slice with the same exceeding amplitude according to the write time sequence. Based on the sorting result, a conflict priority table is generated.

[0008] In a preferred embodiment, in S4, by receiving the conflict priority table, the equal-length time slice index and the corresponding priority order are parsed therefrom. The parsed result is constructed as a priority sequence, and the corresponding relationship between the running record and the charging time, the discharging time, and the write time is maintained in the priority sequence; In the priority sequence, the low-priority running record is identified one by one. The charging time or the discharging time of the low-priority running record is delayed by an interval of one conflict equal-length time slice duration, and the delayed time is recorded to a rearrangement time table; The write time and the original write time of each running record in the rearrangement time table are compared, the time difference value between the two is calculated to solve the delay compensation value, and the delay compensation value is added to the write time of the corresponding running record to form a compensated running time sequence table; According to the preset smoothing strategy, the power values of adjacent equal-length time slices in the running time sequence table are subjected to weighted allocation to generate a continuous power curve, and the continuous power curve and the running time sequence table are combined to generate an adjusted running record.

[0009] In a preferred embodiment, in S5, by receiving the adjusted operation record, extracting the timestamp field, power flow direction flag field and state of charge field therein, then time series is formed by time stamp field, power direction label is decoded from power flow direction flag field, available margin value is converted from state of charge field, and the parsed results are written into parameter buffer area; By reading the time series, power direction label and available margin value in the parameter buffer area, the scheduling matrix is constructed by combining the capacity boundary condition, the equal-length time slice information is written in the row vector of the scheduling matrix, the power instruction value is written in the column vector, and the correction operation is performed on the entries exceeding the capacity upper limit or below the capacity lower limit in the matrix calculation process; By calling the power collector on the energy exchange channel to obtain the actual power value of each equal-length time slice, and performing difference calculation between the actual power value and the power instruction value in the scheduling matrix at each time, a deviation sequence is formed, and then the deviation sequence is combined with the capacity boundary condition to perform constraint correction, and the corrected deviation curve is output and written into the deviation buffer; By reading the deviation curve in the deviation buffer, combining it with the margin value in the operation record, performing feedback index calculation to form a feedback data set, and outputting the feedback data set to the central management step.

[0010] In a preferred embodiment, a smart park energy management system includes an intention construction module, an intention synchronization module, a conflict detection module, an intention adjustment module, and a collaborative execution module; The intention construction module acquires state data by collecting energy state parameters of energy storage devices, divides the state data into equal-length time slices according to time sequence, and calculates power change rate, load offset and output difference in each equal-length time slice, and combines the statistical results with charging time, discharging time, power value and writing time to generate operation records; The intention synchronization module acquires trigger signals by receiving operation records and detecting energy state parameter changes, arranges equal-length time slices from high to low according to power change rate using differential compression algorithm, and selects equal-length time slices with power change rate higher than a preset threshold to generate broadcast data frames; The conflict detection module acquires a set of operation records by receiving local operation records and external operation records, aligns the set of operation records according to the starting time of equal-length time slices, accumulates power values in a sliding window, and compares them with the power upper limit of the energy exchange channel to identify over-limit equal-length time slices and solve the conflict priority table in combination with the writing time sequence; The intention adjustment module acquires priority order by receiving the conflict priority table, delays the charging time or discharging time of low-priority operation records by the duration of a conflict equal-length time slice, adds a delay compensation value in the writing time, and adjusts the power value according to the smoothing strategy to generate an adjusted operation record; The cooperative execution module obtains cooperative execution parameters by receiving the adjusted operation record, performs charging, discharging and data writing operations in parallel, calculates the difference between actual power and planned power to generate a deviation curve after each operation is completed, and outputs the deviation curve and storage state to the central management system.

[0011] Technical effects and advantages of the present application: The present application unifies the charging and discharging power of distributed energy storage devices in the time dimension by constructing a scheduling matrix, and introduces a capacity boundary constraint condition, so that each device obtains consistent power instructions before execution, avoiding the problems of energy exchange bus contention and storage queue blocking caused by autonomous strategy parallel triggering, and fundamentally solving the key problem of timely elimination of cross-node conflicts in smart park energy management. The present application uses time series segmentation calculation to distribute charging power and discharging power in each time slice, ensuring that the system can still operate stably under the condition of demand curve and renewable energy output fluctuation; The present application introduces an operation feedback mechanism based on the scheduling matrix, so that the power distribution is dynamically corrected during execution, thereby improving the adaptive ability of the scheduling strategy to real-time abnormalities; The present application integrates distributed storage resources into the unified framework of energy scheduling, so that the charging and discharging instructions are consistent with the data storage process, thereby reducing the risk of log loss and write blocking, and realizing the cooperative optimization of energy management and storage management. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 The method step flowchart of the present application.

[0013] Figure 2 The system module schematic diagram of the present application.

[0014] Figure 3 The operation record generation and broadcast flowchart of the present application.

[0015] Figure 4 The conflict detection and priority generation flowchart of the present application.

[0016] Figure 5 The adjusted operation record execution and feedback flowchart of the present application. DETAILED DESCRIPTION

[0017] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0018] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application. Figures 1-5 An energy management method of a smart park, comprising the following steps: S1, obtaining state data by collecting energy state parameters of energy storage equipment, dividing the state data into equal-length time slices according to time sequence, and counting power change rate, load offset and output difference in each equal-length time slice, and combining the statistical results with charging time, discharging time, power value and writing time to generate operation records; S2, obtaining a trigger signal by receiving operation records and detecting energy state parameter change amount, arranging the equal-length time slices from high to low according to power change rate by using a differential compression algorithm, and selecting equal-length time slices with power change rate higher than a preset threshold to generate broadcast data frames; S3, obtaining an operation record set by receiving local operation records and external operation records, aligning the operation record set according to the starting time of the equal-length time slices, accumulating power values in a sliding window, and comparing with an energy exchange channel power upper limit, wherein the energy exchange channel power upper limit includes a static upper limit and a dynamic upper limit, identifying over-limit equal-length time slices and solving a conflict priority table in combination with writing time sequence; S4, obtaining a priority order by receiving the conflict priority table, delaying the charging time or discharging time of the low-priority operation records by the duration of a conflict equal-length time slice, adding a delay compensation value in the writing time, and generating adjusted operation records according to a smoothing strategy; S5, obtaining cooperative execution parameters by receiving the adjusted operation records, performing charging, discharging and data writing operations in parallel, calculating the difference between actual power and planned power to generate a deviation curve after each operation is completed, and outputting the deviation curve and storage state to a central management system.

[0019] In S1, state data is obtained by collecting energy state parameters of energy storage equipment in a preset sampling interval, the energy state parameters include voltage value, current value, predicted load value and predicted output value, the state data is divided into equal-length time slices according to time sequence, and each equal-length time slice is assigned a unique equal-length time slice index; The power change rate, the load offset and the output difference value are calculated in each equal-length time slice respectively, each calculation result is bound to the corresponding equal-length time slice index, and the bound result is recorded to the equal-length time slice data table, wherein the power change rate is calculated by extracting the power values of adjacent sampling time points in the equal-length time slice, the power change rate sequence of the equal-length time slice is obtained by dividing the power difference value of the adjacent sampling time points by the sampling interval time, and the equal-length time slice power change rate is generated by averaging the power change rate sequence; the load offset is calculated by extracting the load prediction value and the load reference value in the equal-length time slice, the average load offset of the equal-length time slice is obtained by accumulating the difference value between the load prediction value and the load reference value at the sampling time points and then dividing by the sampling number; the output difference value is calculated by extracting the predicted output value and the target output value in the equal-length time slice, and the average output difference value of the equal-length time slice is obtained by accumulating the difference value between the predicted output value and the target output value at the sampling time points and then dividing by the sampling number; The equal-length time slice data table is corresponded to the charging time, the discharging time, the power value and the writing time of the energy storage device to form the operation record segment with the equal-length time slice index as the primary key and the charging and discharging parameters and the calculation results as the combined fields; All the operation record segments are combined in the time sequence of the equal-length time slice index to generate the complete operation record and output.

[0020] In S2, the equal-length time slice data in the operation record is extracted, the energy state parameter change amount of each equal-length time slice is calculated, the energy state parameter change amount includes the power change rate and the power change trend, and each energy state parameter change amount is associated with the corresponding equal-length time slice index to form the change amount mapping table; The change amount mapping table is read, the equal-length time slice index is prioritized from high to low according to the power change rate, and the power change trend is marked in the sorting process to preserve the correspondence between the equal-length time slice power fluctuation mode and the sorting priority; The equal-length time slices after prioritization are compressed using the difference compression algorithm, the complete energy state parameters of the first equal-length time slice are stored in the reference data area, the energy state parameter change amounts of the remaining equal-length time slices are stored in the difference form, and the reference data area and the difference form are organized into the compressed equal-length time slice set; Equal-length time slices with power change rate higher than a preset threshold and continuous and consistent power change trend are screened from the compressed equal-length time slice set, the screening result and the corresponding equal-length time slice index are reorganized to construct the broadcast data frame; for equal-length time slices with power change rate lower than or equal to the preset threshold, the equal-length time slices are merged according to the compressed order to generate the summary equal-length time slice and stored in the low-priority buffer.

[0021] In S3, by receiving the local running record and the external running record, the two types of running records are merged in chronological order to generate a running record set, and each running record in the running record set is assigned an equal-length time slice index, and the power value and the write time are recorded to form a running record table; According to the running record table, a start time alignment operation is performed on the running record set, equal-length time slices with the same start time are aggregated, a mapping relationship between the equal-length time slices and the power values is established, and a power mapping table is generated; A sliding window is set on the power mapping table, and the window is gradually slid according to the window span. The cumulative operation is performed on the power values in each window range. The cumulative result is compared with the upper limit of the energy exchange channel power, wherein the upper limit of the energy exchange channel power includes the channel reference power upper limit determined according to the rated power value of the park energy bus and the dynamic power upper limit formed during the operation according to the safety margin. Both are used as the judgment basis for power comparison. The equal-length time slice index that exceeds the power upper limit is identified and marked as an over-limit state. The equal-length time slice index that does not exceed the power upper limit is marked as a normal state. A power comparison table containing all equal-length time slice indexes and their comparison states is formed; The power comparison table is read, and the equal-length time slice indexes marked as the over-limit state are filtered therefrom. The corresponding power values exceeding the power upper limit are sorted according to the exceeding amplitude, and the equal-length time slices with the same exceeding amplitude are sorted according to the write time sequence. Based on the sorting result, a conflict priority table is generated and output to the running intention adjustment step.

[0022] In S4, by receiving the conflict priority table, the equal-length time slice index and the corresponding priority order are parsed, the parsing result is constructed as a priority sequence, and the corresponding relationship between the running record and the charging time, the discharging time and the write time is maintained in the priority sequence; In the priority sequence, the low-priority running record is identified one by one. The charging time or discharging time of the low-priority running record is delayed by an interval of one conflict equal-length time slice duration, and the delayed time is recorded to a rearrangement time table; In the rearrangement time table, the write time and the original write time of each running record are compared, the time difference between the two is calculated to solve the delay compensation value, and the delay compensation value is added to the write time of the corresponding running record to form a compensated running time sequence table; According to the preset smoothing strategy, the power values in the adjacent equal-length time slices in the running time sequence table are weighted and distributed to generate a continuous power curve. The continuous power curve and the running time sequence table are combined to generate an adjusted running record, which is output to the collaborative execution step.

[0023] In S5, by receiving the adjusted operation record, the timestamp field, power flow direction flag field and state of charge field are extracted, then the timestamp field is continuous to form a time sequence, the power flow direction flag field is decoded into a power direction label, and the state of charge field is converted into an available margin value, wherein the available margin value refers to the remaining execution space allowed under the joint action of the capacity boundary condition and the upper limit of the energy exchange channel power, the calculation method of the available margin value is to subtract the current storage capacity value from the upper limit of the storage capacity to obtain the capacity margin, and the power margin determined according to the upper limit of the energy exchange channel power is compared, and the smaller one of the two is taken as the available margin value, and the parsed result is written into the parameter buffer area; By reading the time sequence, power direction label and available margin value in the parameter buffer area, a scheduling matrix is constructed in combination with the capacity boundary condition, wherein the capacity boundary condition includes the upper limit and lower limit of the storage capacity, which is used to correct the instruction when charging or discharging to prevent exceeding the upper limit or being lower than the lower limit, the equal-length time slice information is written in the row vector of the scheduling matrix, the power instruction value is written in the column vector, and the correction operation is performed on the items exceeding the capacity upper limit or being lower than the capacity lower limit in the matrix calculation process; By calling the power collector on the energy exchange channel to obtain the actual power value of each equal-length time slice, and performing difference calculation on the actual power value and the power instruction value in the scheduling matrix at each time, a deviation sequence is formed, and then the deviation sequence is combined with the capacity boundary condition to perform constraint correction, and the corrected deviation curve is output and written into the deviation buffer; By reading the deviation curve in the deviation buffer, it is combined with the margin value in the operation record to perform feedback index calculation to form a feedback data set, and the feedback data set is output to the central management step for subsequent call of scheduling correction.

[0024] It should be noted that for the formula structure involved in the present scheme, the dimensionless term can be used as a proportional or structural adjustment factor, which only plays a numerical scaling role when combined with quantities with units, without introducing new physical dimensions, so it will not change or confuse the unit system of the whole expression; Such combination of "dimensionless term and quantity unit term" can be understood as the commonly used composite structure expression form in mathematical and physical modeling, which conforms to the principle of dimensional consistency and has a clear physical interpretation basis; Secondly, in the formula structure of the present scheme, if multiple variable terms with different physical units are involved, including but not limited to time, mass or energy variables, their joint occurrence is to express the cooperative modeling relationship of multiple physical mechanisms, and each variable can be mapped by a function, combined by a ratio or adjusted by a unit, to form a unified structure with clear units and meanings, and the whole expression conforms to the principle of dimensional consistency and the common norm of engineering modeling; If the present scheme involves constants, weights, adjustment factors, threshold parameters, proportionality coefficients, etc., they are all adjustable control parameters for different application environments, the values of which depend on the target device configuration, data input characteristics, and performance optimization goals, and are set within a reasonable range through model verification, performance constraints, or engineering calibration during the implementation stage. Although these parameters do not have a unique value, they have a clear adjustment logic and calculation path, and belong to the deterministic setting process in engineering implementation. The purpose of such setting is to ensure that the scheme has both general adaptability and reproducibility and operability, without affecting its technical clarity and implementability. Definitions available margin value in the time slice ; wherein is the lower capacity constraint; is the upper capacity constraint; is the continuous evolution variable of time; is the power direction label at time ; is the actual power value at time ; is the mapping function of power and direction, used to calculate the energy increase or decrease; is the capacity boundary constraint function, used to ensure that the integral result does not exceed the upper and lower limits; is the power instruction value of the scheduling matrix in the th row and the th column; is the row vector of the scheduling matrix, corresponding to the time information of the equal-length time slice; is the column vector of the scheduling matrix, corresponding to the index of the power instruction; is the available margin value in the time slice ; is the scheduling function, combining the time slice, power instruction, and capacity condition to generate a scheduling entry; is the power deviation value in the time slice ; is the actual power value obtained by the power collector in the time slice ; is the scheduling matrix in the time slice ;The corresponding power command value; For time slices The corresponding power command index function; in For time slices The corrected power deviation value; For time slices The original power deviation value; For time slices Available margin value; ( ) represents the capacity boundary condition; This is a constraint correction function, used to correct deviations that exceed boundary conditions. For time slices The generated feedback dataset entries; For time slices The correction deviation value; For time slices Available margin value; For time slices The remaining value of the running record; For feedback indexing functions, Used to combine the correction deviation with the operating margin to generate feedback data; Furthermore, firstly through and The integral result, combined with the capacity boundary conditions ( ) Generated in time slice Available margin value Then utilize the available margin value With time index Power Command Index Constructing the scheduling matrix This establishes a correspondence between time slices and power commands; during the execution phase, power is actually collected... With the scheduling matrix in time slice Corresponding power command value The power deviation was calculated based on the difference. Combined with capacity margin With boundary conditions ( The deviation value is corrected to form the corrected deviation. The deviation will eventually be corrected. Available margin With running records Merge and generate feedback dataset This achieves a complete closed loop of capacity boundary constraints, scheduling matching, deviation correction, and feedback output.

[0025] A smart park energy management system includes an intent construction module, an intent synchronization module, a conflict detection module, an intent adjustment module, and a collaborative execution module; The intent building module acquires state data by collecting energy state parameters of energy storage devices, divides the state data into equal time slices according to the time series, and statistically analyzes the power change rate, load offset and output difference in each equal time slice. The statistical results are combined with the charging time, discharging time, power value and writing time to generate operation records. The intent synchronization module obtains the trigger signal by receiving the operation record and detecting the change in energy status parameters. It uses a differential compression algorithm to arrange equal-length time slices from high to low according to the power change rate, and selects equal-length time slices with a power change rate higher than a preset threshold to generate broadcast data frames. The conflict detection module obtains a set of operation records by receiving local operation records and external operation records, aligns the set of operation records according to the start time of equal-length slices, accumulates the power value within a sliding window, compares it with the upper limit of the power of the energy exchange channel, identifies the over-limit equal-length slices, and solves the conflict priority table by combining the writing time order. The intent adjustment module obtains the priority order by receiving the conflict priority table, delays the charging or discharging time of the low-priority running record by the duration of a conflict-equal-length slice, adds a delay compensation value to the write time, and adjusts the power value according to the smoothing strategy to generate the adjusted running record. The collaborative execution module obtains collaborative execution parameters by receiving the adjusted operation records, performs charging, discharging and data writing operations in parallel, calculates the difference between the actual power and the planned power after each operation to generate a deviation curve, and outputs the deviation curve and storage status to the central management system.

[0026] In practical implementation, firstly, in the energy management of the smart park, the charging and discharging power data of distributed storage devices are continuously acquired, and upper and lower limits of storage capacity are set as constraints. Secondly, these power data are organized in chronological order and, combined with capacity boundary conditions, feasible power allocation results are calculated for each time period. Then, the allocation results are combined into a scheduling matrix, so that there is a clear power command at each time position. Finally, in actual operation, power commands are output step by step according to the scheduling matrix, and power allocation is corrected in combination with operational feedback, so as to always meet the capacity limit. The scheme solves the resource grabbing problem that is prone to occur when the distributed energy storage devices in the smart park energy management run independently, especially when the electricity demand and renewable energy generation fluctuate sharply, multiple devices may start local strategies at the same time, causing power distribution chaos, storage write congestion and even data loss. The scheme synchronizes the operation intention of each device before decision making, and uses a scheduling matrix to quickly coordinate and resolve conflicts, allowing each energy storage device to operate cooperatively while reasonably using distributed storage resources, thereby avoiding the management instability problem caused by concurrent contention.

[0027] Finally: the above only for the preferred embodiments of the present application, and not for limiting the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A smart park energy management method, characterized in that, Includes the following steps: S1. Obtain status data by collecting energy status parameters of energy storage devices, divide the status data into equal time segments according to time series, and statistically analyze the power change rate, load offset and output difference in each equal time segment. Combine the statistical results with charging time, discharging time, power value and writing time to generate operation record. S2. By receiving the operation record and detecting the change in energy status parameters, a trigger signal is obtained. The time slices are arranged in order of power change rate from high to low using a differential compression algorithm. Time slices with power change rate higher than a preset threshold are selected to generate broadcast data frames. S3. Obtain the set of operation records by receiving local operation records and external operation records, align the set of operation records according to the start time of equal time slices, accumulate the power value within the sliding window, compare it with the upper limit of the power of the energy exchange channel, identify the over-limit equal time slices, and solve the conflict priority table by combining the writing time order. S4. Obtain the priority order by receiving the conflict priority table, delay the charging or discharging time of the low-priority running record by the duration of a conflict-equal-length slice, add a delay compensation value to the writing time, and adjust the power value according to the smoothing strategy to generate the adjusted running record. S5. Obtain collaborative execution parameters by receiving the adjusted operation records, and perform charging, discharging and data writing operations in parallel. After each operation, calculate the difference between the actual power and the planned power to generate a deviation curve, and output the deviation curve and storage status to the central management system.

2. The smart park energy management method according to claim 1, characterized in that: In S1, state data is obtained by collecting energy state parameters of the energy storage device within a preset sampling interval. The energy state parameters include voltage value, current value, predicted load value and predicted output value. The state data is divided into equal time slices in chronological order, and a unique equal time slice index is assigned to each equal time slice. Calculate the power change rate, load offset and output difference in each equal-length segment, bind the calculation results with the corresponding equal-length segment index, and record the binding results in the equal-length segment data table. The data table of equal-length time slices is mapped to the charging time, discharging time, power value and writing time of the energy storage device to form a running record segment with the equal-length time slice index as the primary key and the charging and discharging parameters and calculation results as combined fields. All runtime record fragments are combined according to the time order of the equally long slice index to generate a complete runtime record and output it.

3. The smart park energy management method according to claim 2, characterized in that: In S2, the data of equal-length time slices in the running record are extracted, and the change of energy state parameters for each equal-length time slice is calculated. The change of energy state parameters includes the power change rate and the power change trend. Each change of energy state parameters is associated with the corresponding equal-length time slice index to form a change mapping table. Read the change mapping table, perform priority sorting on the equal-length slice index according to the power change rate from high to low, and mark the power change trend during the sorting process; The differential compression algorithm is used to compress the priority sorted equal-length slices. The complete energy state parameters of the first equal-length slice are stored in the reference data area, and the changes in energy state parameters of the remaining equal-length slices are stored in differential form. The reference data area and the differential form are organized into a set of compressed equal-length slices. From the set of compressed equal-length segments, select equal-length segments with a power change rate higher than a preset threshold and a continuous and consistent power change trend. Reassemble the selection results with their corresponding equal-length segment indices to construct broadcast data frames. For equal-length segments with a power change rate lower than or equal to the preset threshold, merge them in the order after compression to generate summary equal-length segments and store them in a low-priority buffer.

4. The smart park energy management method according to claim 3, characterized in that: In S3, by receiving local and external running records, the two types of running records are merged in chronological order to generate a running record set. Each running record in the running record set is assigned an equal-length time slice index. At the same time, the power value and write time are recorded to form a running record table. Based on the operation record table, perform a start time alignment operation on the operation record set, aggregate equal-length slices with the same start time, establish a mapping relationship between equal-length slices and power values, and generate a power mapping table. A sliding window is set on the power mapping table. The window is slid up step by step according to the window span. The cumulative calculation is performed on the power value within each window range. The cumulative result is compared with the power limit of the energy exchange channel. The index of the same length slice that exceeds the power limit is identified and marked as over-limit state. The index of the same length slice that does not exceed the power limit is marked as normal state, thus forming a power comparison table. Read the power comparison table, filter out the indexes of equal-length slices marked as exceeding the limit, sort them according to the magnitude by which the corresponding power value exceeds the power limit, and sort them according to the write time order within equal-length slices with the same magnitude of exceedance. Generate a conflict priority table based on the sorting results.

5. The smart park energy management method according to claim 4, characterized in that: In S4, by receiving the conflict priority table, parsing the equal time slice index and the corresponding priority order, constructing the parsing result into a priority sequence, and maintaining the correspondence between the running record and the charging time, discharging time and writing time in the priority sequence; In the priority sequence, identify the low-priority operation record one by one, postpone the charging or discharging time of the low-priority operation record by an interval equal to the duration of a conflict-prone long slice, and record the postponed time in the rearranged timetable. Compare the write time of each running record with the original write time in the rearranged timetable, calculate the time difference between the two to solve for the delay compensation value, and add the delay compensation value to the write time of the corresponding running record to form a compensated running sequence table. For adjacent time slice power values ​​in the runtime sequence table, a weighted allocation is performed on the power values ​​according to a preset smoothing strategy to generate a continuous power curve. The continuous power curve is then combined with the runtime sequence table to generate an adjusted runtime record.

6. The smart park energy management method according to claim 5, characterized in that: In S5, by receiving the adjusted operation record, the timestamp field, power flow direction flag field and state of charge field are extracted. Then, the timestamp field is made continuous to form a time series, the power flow direction flag field is decoded into a power direction label, the state of charge field is converted into an available margin value, and the parsed results are written to the parameter buffer. By reading the time series, power direction label and available margin value in the parameter buffer, and combining them with the capacity boundary conditions, a scheduling matrix is ​​constructed. Equal time slice information is written into the row vector of the scheduling matrix, and power command values ​​are written into the column vector. During the matrix calculation process, correction operations are performed on entries that exceed the capacity upper limit or fall below the capacity lower limit. The actual power value of each equal-length time slice is obtained by calling the power harvester on the energy exchange channel. The difference between the actual power value and the power command value in the scheduling matrix is ​​calculated at each time step to form a deviation sequence. The deviation sequence is then combined with the capacity boundary conditions to perform constraint correction, and the corrected deviation curve is output and written to the deviation buffer. By reading the deviation curve from the deviation cache, combining it with the residual value in the running record, performing feedback index calculation to form a feedback dataset, and outputting the feedback dataset to the central management step.

7. A smart park energy management system, characterized in that, It includes an intent building module, an intent synchronization module, a conflict detection module, an intent adjustment module, and a collaborative execution module; The intent building module acquires state data by collecting energy state parameters of energy storage devices, divides the state data into equal time slices according to the time series, and statistically analyzes the power change rate, load offset and output difference in each equal time slice. The statistical results are combined with the charging time, discharging time, power value and writing time to generate operation records. The intent synchronization module obtains the trigger signal by receiving the operation record and detecting the change in energy status parameters. It uses a differential compression algorithm to arrange equal-length time slices from high to low according to the power change rate, and selects equal-length time slices with a power change rate higher than a preset threshold to generate broadcast data frames. The conflict detection module obtains a set of operation records by receiving local operation records and external operation records, aligns the set of operation records according to the start time of equal-length slices, accumulates the power value within a sliding window, compares it with the upper limit of the power of the energy exchange channel, identifies the over-limit equal-length slices, and solves the conflict priority table by combining the writing time order. The intent adjustment module obtains the priority order by receiving the conflict priority table, delays the charging or discharging time of the low-priority running record by the duration of a conflict-equal-length slice, adds a delay compensation value to the write time, and adjusts the power value according to the smoothing strategy to generate the adjusted running record. The collaborative execution module obtains collaborative execution parameters by receiving the adjusted operation records, performs charging, discharging and data writing operations in parallel, calculates the difference between the actual power and the planned power after each operation to generate a deviation curve, and outputs the deviation curve and storage status to the central management system.

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