Park carbon coordination early warning control method

Abstract

The application discloses a park energy-carbon coordination early warning management and control method, relates to the technical field of energy saving and emission reduction and intelligent decision support, and comprises the following steps: establishing a unified atomic time reference, setting a unified time reference for a plurality of energy subsystems, generating a cross-source time anchor set under the unified time reference, and using the time anchor set to calibrate the sampling start time of each energy subsystem. The application realizes time alignment and real time sequence restoration of energy consumption data of multiple energy subsystems by establishing a unified atomic time reference and a cross-source time anchor set, and improves energy consumption fusion accuracy. By introducing conflict isolation and breathing time domain patching mechanism, the time distribution and load balance of peak value aggregation section are dynamically controlled, the energy consumption superposition amplification effect is inhibited, and the accuracy and stability of carbon emission reduction simulation and economic analysis results are ensured.

Description

Technical Field

[0001] This invention relates to the fields of energy conservation, emission reduction, and intelligent decision support technology, specifically to a method for early warning and control of energy and carbon synergy in industrial parks. Background Technology

[0002] Intelligent generation of campus carbon reduction schemes based on cost-benefit analysis refers to the process of automatically generating emission reduction schemes that balance energy-saving potential and economic returns, based on campus energy system and carbon emission data, using big data analysis, knowledge base rule matching, and optimization algorithms. This method first structures basic data such as campus building types, equipment energy consumption, and operational characteristics, and then selects suitable combinations of energy-saving and energy-generating schemes from a pre-set emission reduction knowledge base. Subsequently, it uses a cost-benefit analysis model to quantitatively simulate the input costs, energy-saving potential, carbon reduction, and investment payback period of each candidate scheme. Finally, an optimization algorithm selects the scheme that achieves the optimal balance between economic efficiency and emission reduction effect, realizing an automated closed loop from data collection and scheme design to economic evaluation, thereby providing the campus with a scientific, accurate, and feasible carbon reduction path.

[0003] The existing technology has the following shortcomings: In existing technologies, different energy subsystems (such as power supply, heating and air conditioning, and lighting control) often rely on their own independent time bases during energy consumption data collection, lacking a globally unified time synchronization mechanism. When there are slight offsets in the sampling times of each subsystem, energy consumption peaks are misaligned and superimposed on the time axis, forming pseudo-synchronous peak intervals. When the system performs energy consumption data merging simulation, it misjudges these misaligned peaks as superimposed high-energy-consuming events at the same moment, resulting in a resonant amplification effect on the energy curve. Because this resonant superposition phenomenon is misidentified as a concentration of real energy consumption at the computational level, the emission reduction simulation results will output abnormally high emission reduction intensity values, causing serious deviations in the assessment of energy-saving potential and distorting the investment allocation and economic judgment in the subsequent scheme generation stage.

[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 method for early warning and control of energy and carbon synergy in industrial parks, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for early warning and control of energy and carbon synergy in industrial parks, comprising the following steps: Establish a unified atomic time reference, set a unified time reference for multiple energy subsystems, generate a cross-source time anchor set under the unified time reference, and use the time anchor set to mark the sampling start time of each energy subsystem; Misalignment detection is performed based on cross-source time anchor sets. The arrival order of energy consumption peaks in each energy subsystem is compared according to a unified time reference, and misalignment chain markers are generated in continuous time periods to describe the time misalignment relationship of energy consumption peaks. A phase calibration trajectory is constructed based on the misalignment chain markers. Fine-grained time offset adjustments are made to the corresponding time anchors in the time anchor set along the phase calibration trajectory so that the energy consumption peaks can be restored to the true time sequence under a unified time reference. By setting a conflict isolation window based on the phase calibration trajectory, identifying and segmenting time segments containing pseudo-synchronization peaks, and eliminating the energy consumption values ​​that are misaligned and superimposed between various energy subsystems, a net energy consumption peak sequence is obtained. A breathing-style time-domain patching control is performed on the net energy consumption peak sequence. Combined with an anti-resonance gating mechanism, the time anchor position is dynamically adjusted and the superposition window is contracted when the peaks converge, thereby achieving time synchronization and load stability control during the energy consumption merging process across energy subsystems.

[0007] Preferably, the steps for generating the cross-source time anchor set are as follows: A unified atomic time reference is established, and the unified atomic time signal is distributed to multiple energy collection points through a communication network, so that each energy collection point establishes a sampling time structure consistent with the unified time reference; Under a unified atomic time reference, the time axis is divided to generate a cross-source time anchor set with a fixed time interval, and the time anchor set is matched with the sampling period of different energy subsystems. The sampling start anchor point of each energy collection point is determined based on the cross-source time anchor set, and the sampling start anchor point is bound to the sampling period to trigger periodic sampling; During the sampling process, new time anchors are continuously generated based on a unified atomic time reference, and the sampling behavior of each energy collection point is kept synchronized through the extension of the time anchor set.

[0008] Preferably, the steps for generating misaligned chain markers are as follows: Under a unified atomic time standard, energy consumption sampling data from multiple energy subsystems are organized, and a unified time axis is established using a cross-source time anchor set. Based on a unified time axis, the energy consumption time series of each energy subsystem is scanned to identify and mark the peak energy consumption time anchor position within a continuous time anchor segment. By comparing the peak time anchors of multiple energy subsystems over a continuous time period, the arrival order of the energy consumption peaks of each energy subsystem is determined. A peak offset path is constructed based on the arrival order and time interval of energy consumption peaks, and the peak offset path is recorded as a misalignment chain marker for the corresponding time period to describe the time misalignment relationship of energy consumption peaks.

[0009] Preferably, the generation of misaligned chain markers includes segmenting and identifying energy consumption peaks according to continuous time anchor segments, and constructing a directed offset relationship between the energy subsystem sequence and the peak time interval within each time anchor segment, so that each misaligned chain marker uniquely corresponds to a time anchor segment for subsequent continuous construction of phase calibration trajectories.

[0010] Preferably, the steps for constructing the phase calibration trajectory and adjusting the time anchor based on the misalignment chain markers are as follows: The continuous time segments are divided according to the misalignment chain markers, and the arrival order and time interval of energy consumption peaks are extracted from the time segments where energy consumption peaks are misaligned, and a phase calibration path is constructed. Based on the phase calibration path, the peak energy consumption time points of each energy subsystem are mapped to the time anchor set to form a correspondence between peak values ​​and time anchors; Based on the peak order determined in the phase calibration path, fine-grained time offset adjustment is performed on the mapped misaligned time anchors to rearrange the energy consumption peaks according to a unified time reference. The time anchors after time offset adjustment are solidified to generate a set of calibrated time anchors, and a continuous time series of energy consumption peaks is formed accordingly.

[0011] Preferably, the steps for setting a conflict isolation window based on the phase calibration trajectory and generating a net energy consumption peak sequence are as follows: Based on the phase calibration trajectory and time anchor set, a conflict isolation window is constructed with the energy consumption peak time anchor as the center under a unified time reference, and the conflict isolation windows are numbered consecutively. Energy consumption records of multiple energy subsystems are extracted within the conflict isolation window, and pseudo-synchronization peaks that are misaligned and superimposed in time are identified by combining phase calibration trajectory. The peak arrival order is determined according to the phase calibration trajectory. Within the conflict isolation window, misaligned and superimposed energy consumption values ​​are eliminated, and only the first arriving energy consumption peak is retained. The retained energy consumption peaks are sorted according to a unified time reference to form a continuous sequence of net energy consumption peaks.

[0012] Preferably, based on the phase calibration trajectory under a unified time reference, a symmetrical time interval is set with the energy consumption peak time anchor as the center, and adjacent conflict isolation windows are sequentially connected on a unified time axis so that each conflict isolation window only covers the influence range of a single peak, thereby avoiding the cross-over of different energy consumption peaks in the time dimension.

[0013] Preferably, the steps for performing breathing-type time-domain patching control and load stabilization regulation on the net energy consumption peak sequence are as follows: Based on a unified time anchor set, the peak sequence of net energy consumption is scanned to identify peak clusters where peaks are densely distributed in the time dimension; Within the peak clustering section, adjacent time anchors are extended based on the central time anchor to construct a time-elastic temporal patching buffer structure; Within the temporal patching buffer structure, fine-grained time position adjustments are performed on the time anchors corresponding to the peaks, so that adjacent peaks are dispersed on the time axis; After the time anchor adjustment is completed, an anti-resonance gating mechanism is introduced to implement contraction control on the time window when the peak total exceeds the set load limit, forming a stable energy consumption merging sequence.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention introduces a unified atomic time reference across multiple energy subsystems and establishes a cross-source time anchor set, providing a unified time reference for different energy acquisition processes and fundamentally eliminating the energy consumption data misalignment problem caused by sampling time differences. By performing misalignment detection, phase calibration, and time anchor offset adjustment on a unified time axis, the true time-series reconstruction of energy consumption peaks is achieved, enabling energy consumption curves to accurately reflect the actual load changes of each energy subsystem. This improves the accuracy and reliability of energy consumption data fusion, providing a real and effective data foundation for subsequent emission reduction simulations and energy-saving potential analysis.

[0015] This invention introduces conflict isolation and breathing-style time-domain weaving mechanisms based on the calibrated time anchor. By dynamically identifying pseudo-synchronization peaks and implementing load buffering and window contraction, it achieves time-series balance control of energy consumption accumulation sections, ensuring that the merged energy consumption curves of cross-energy subsystems remain time-synchronized and load-stable. This method effectively suppresses the resonance amplification effect caused by peak superposition, avoids the phenomenon of artificially inflated energy-saving intensity in emission reduction simulations, and guarantees the stability and feasibility of carbon emission reduction schemes in economic assessment and investment allocation decisions. Attached Figure Description

[0016] 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.

[0017] Figure 1 This is a flowchart of the method for early warning and control of energy and carbon synergy in industrial parks according to the present invention. Detailed Implementation

[0018] 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.

[0019] This invention provides, for example Figure 1 The energy and carbon synergy early warning and control method for industrial parks shown includes the following steps: Establish a unified atomic time reference, set a unified time reference for multiple energy subsystems, generate a cross-source time anchor set under the unified time reference, and use the time anchor set to mark the sampling start time of each energy subsystem; To address the data misalignment issue caused by inconsistent sampling time references across multiple energy subsystems, a unified atomic time reference needs to be established across the entire campus before energy consumption data collection begins. Based on this, a cross-source time anchor set should be created, and then this time anchor set should be used to determine the sampling start time for each energy subsystem. The specific implementation steps are as follows: Before commencing carbon reduction data collection on campus, a unified atomic time reference must be established as the starting point for all energy sampling processes. This time reference is provided by a time source device with high stability and high-precision time retention capabilities, and its output standard time signal is continuously broadcast and distributed through a dedicated campus communication network. During propagation, the time signal must reach specific energy collection points, such as the power supply collection unit, heating and air conditioning collection unit, lighting control collection unit, elevator energy consumption collection unit, fresh air exchange equipment collection unit, water pump system collection unit, and hot water system collection unit, through a multi-node cascade method. Each collection point must be equipped with a clock synchronization component, capable of using the received atomic time signal as the basis for judging the time of sampling activities, and establishing a local sampling time structure in the local equipment that is strictly consistent with the unified time reference. To ensure the consistency of time signal transmission between energy collection points, a point-to-point delay compensation mechanism is adopted during signal broadcasting, eliminating line transmission delays channel by channel to ensure that the time reference reaching each energy collection point does not shift due to path differences. After this step is completed, all energy collection processes on campus will use this unified atomic time reference as a reference, providing a unified and accurate sampling time framework and a stable time basis for the construction of subsequent time anchors.

[0020] After establishing a unified atomic time reference, a cross-source time anchor set is generated around this time reference to guide different energy collection activities to sample at the same temporal rhythm. The construction process of this time anchor set includes three steps: sampling period abstraction, time node division, and matching of anchor points to corresponding energy subsystems. First, based on the sampling needs of various energy types on campus, specific sampling period durations are set, such as 1 minute for power supply sampling, 3 minutes for heating and air conditioning sampling, 5 minutes for lighting control sampling, 2 minutes for water pump equipment sampling, and 4 minutes for hot water equipment sampling. Then, starting from the unified atomic time reference, the time axis is divided according to the smallest time granularity, and anchor points on each time slice are marked one by one. These anchor point sets are organized into a time anchor set with a fixed structure and progressive rules. The time interval between anchor points can be set as the smallest sampling unit, such as 30 seconds or 60 seconds, to ensure that different energy collection units can find corresponding alignment points in this anchor set. Next, after the cross-source time anchor set is established, each time anchor identifier in the anchor set is mapped and matched with the sampling period of the corresponding energy subsystem. For example, if a power acquisition device has a sampling period of 1 minute, it will select every other time anchor point in the time anchor set as the sampling start anchor point; if a lighting control device has a sampling period of 5 minutes, it will sample every 5 anchor points. This enables the sharing of the same anchor set by various energy subsystems under different sampling rhythms, and ensures the logical synchronization of sampling time through a unified anchor structure.

[0021] After constructing the cross-source time anchor set, this set needs to be used to calibrate the sampling start time of each energy subsystem, ensuring that the data acquisition process of each energy source starts on time under a unified time reference. The specific steps are as follows: First, before data acquisition, each energy acquisition point obtains its current absolute time by receiving a unified atomic time signal. Then, it finds the first anchor point in the anchor set that is equal to or greater than this absolute time as the starting anchor point. Second, this starting anchor point is bound to the sampling period of the energy acquisition point, forming an "anchor point-period" correspondence table to guide the time triggering rules for sampling behavior. Then, according to this binding relationship, during actual operation, each energy acquisition point continuously samples from the calibrated start time using a periodic triggering mechanism, according to its "anchor point-period" mapping. For example, if a power supply device identifies a time anchor t0 as its starting point at 08:00:00 under a unified atomic time reference, and the sampling period is 1 minute, then subsequent sampling times will be 08:01:00, 08:02:00, 08:03:00, etc.; if a lighting control device's starting anchor under the same reference time is 08:00:00, and the sampling period is 5 minutes, then its sampling points will be 08:05:00, 08:10:00, 08:15:00, etc. Through this refined time anchor calibration process, it is ensured that the starting point of each energy collection behavior is based on a unified anchor point definition, making the energy consumption data of different energy types consistent and comparable on the time axis, providing a stable and reliable foundation for subsequent energy consumption data comparison and peak identification.

[0022] After calibrating the sampling start time of each energy subsystem, to ensure the time consistency of the entire energy consumption acquisition system during long-term operation, the time anchor set needs to be continuously extended and synchronized to maintain structural consistency and time synchronization in future periods. This extension process is based on the time progression characteristics of a unified atomic time reference. After each sampling cycle, the next time anchor point is automatically generated and incorporated into the time anchor set structure, making the time anchor set a continuously growing time sequence structure. Each newly generated time anchor point maintains a constant interval with the previous anchor point, forming a periodically increasing anchor point chain. In this anchor point chain structure, different energy acquisition points continuously read the latest anchor point from the anchor point chain according to their respective "anchor point-cycle" binding relationships, triggering the corresponding sampling behavior. To further improve the tracking performance of each acquisition point to the anchor point structure, an anchor point synchronization buffer mechanism is added to the anchor point chain structure. This mechanism adjusts the anchor point read advance based on the differences in sampling delays between different energy subsystems, giving sampling triggering time flexibility. For example, for data collection from slow-responding hot water equipment, anchor points two cycles in advance can be extracted from the anchor chain as the next trigger target to address the issue of long preparation times for internal sampling within the equipment. Through this continuous extension and synchronization mechanism, the campus energy collection network can maintain the consistency of its time anchor structure during long-term operation, ensuring the stable temporal correlation and synchronization of subsequent energy consumption data.

[0023] Misalignment detection is performed based on cross-source time anchor sets. The arrival order of energy consumption peaks in each energy subsystem is compared according to a unified time reference, and misalignment chain markers are generated in continuous time periods to describe the time misalignment relationship of energy consumption peaks. To achieve precise alignment of energy consumption data from multiple energy subsystems across the time dimension, it is necessary to further compare the peak energy consumption data of each energy subsystem under a unified time reference, based on the established unified atomic time reference and cross-source time anchor set, and identify their time offset relationships. This process involves analyzing consecutive anchor segments to construct a structured marker on the time axis representing the arrival order and time interval of the peak values ​​of each energy subsystem, which is used for subsequent time phase calibration and pseudo-synchronization identification. The specific implementation steps are as follows: After collecting energy consumption data from all energy subsystems, the sampled data recorded by different subsystems under a unified atomic time reference needs to be organized into time series, and a unified time axis needs to be established based on the time anchor set. The energy subsystems involved here include the power supply subsystem, heating and air conditioning subsystem, lighting control subsystem, water pump operation subsystem, fresh air exchange subsystem, and hot water supply subsystem. The sampled data of each subsystem is time-labeled according to the correspondence between its sampling period and the time anchor set, thus forming a time-series energy consumption data curve with the time anchor point as the x-axis and energy consumption value as the y-axis.

[0024] In this curve, by scanning the energy consumption trend within continuous time anchor segments, the portion where short-term energy consumption values ​​are significantly higher than those of adjacent time periods is extracted to identify the energy consumption peak representing the subsystem during that time period. For example, in the energy consumption curve of the power supply subsystem, if a series of power increases continuously between 08:10 and 08:20 and reaches a local maximum at 08:15 before falling back, then 08:15 can be marked as an independent peak. In the heating and air conditioning subsystem, if the power rapidly jumps to a high level at 08:13 and continues for two time anchor points before rapidly decreasing, then 08:13 can be taken as the peak position for that time period. By sequentially performing the above positioning process on the energy consumption time series of each subsystem, a complete list of subsystem peak time anchor distributions can be formed, providing a basis for sequential comparison in the next stage.

[0025] After locating the peak energy consumption of all subsystems by time anchor, it is necessary to perform a horizontal comparison of the order in which the peaks of each subsystem occur within the same time period to extract the relative order of occurrence of each subsystem within the same time window. This process is carried out in units of fixed-length continuous time anchor segments, for example, 30 minutes per segment, with each segment containing 60 one-minute time anchor points. Within each time segment, all peak anchor points of each subsystem are summarized, arranged in chronological order, and the time of occurrence of the peak is numbered.

[0026] In practice, the peak anchor points of the power supply subsystem within this time period, such as 08:15, 08:29, and 08:43, are listed as the first column; the peak anchor points of the heating and air conditioning subsystem, such as 08:13, 08:32, and 08:44, are listed as the second column; the peak anchor points of the lighting control subsystem, such as 08:16, 08:33, and 08:46, are listed as the third column, and so on, forming a multi-column peak sequence table. By comparison, it can be seen that within the short period from 08:13 to 08:16, the peaks of multiple subsystems occur at relatively small intervals, and their order of occurrence overlaps. Therefore, the relative positions of each peak on the time axis need to be marked as their priority and categorized. For example, 08:13 is the first arriving peak, 08:15 is the second, and 08:16 is the third, thus confirming the staggered peak order of the three different energy subsystems within this time window.

[0027] After determining the specific occurrence time and relative order of peak values ​​for each energy subsystem, it is necessary to construct a staggered trend structure for each time period based on a unified time axis to describe the time offset between subsystems. This process quantifies the peak intervals between adjacent subsystems one by one, based on the relative distance between the peak times of each subsystem.

[0028] Specifically, within the time period from 08:13 to 08:16, if the peak value of the heating and air conditioning subsystem occurs at 08:13, the peak value of the power supply subsystem occurs at 08:15, and the peak value of the lighting control subsystem occurs at 08:16, the following offset paths are constructed: Heating and Air Conditioning → Power Supply, with an offset time of 2 minutes; Power Supply → Lighting Control, with an offset time of 1 minute. These paths are recorded as a directed chain, assigned a path number and a corresponding time period number, indicating that this path structure only applies to the current continuous time period. Continuing to slide the time window forward, the relative order and offset relationship of peak values ​​in the next time period are compared in the same way, continuously extracting new offset paths. Finally, a set of offset trends consisting of time period numbers, subsystem order, and time intervals is obtained, comprehensively reflecting the differences and variation patterns of energy consumption peak values ​​of different subsystems in each continuous time period.

[0029] The extracted peak offset trend needs to be recorded in a structured form to form a misalignment chain marker that can be called upon in subsequent phase calibration processing. This marker needs to clearly define the time range, participating subsystems, arrival order, and relative time difference. In specific implementation, each continuous time window is first assigned a unique number, for example, the first segment is D001, the second segment is D002. Then, in each segment, the sequential chain extracted according to the offset trend is organized into a structured record item. For example, in D001, the offset is 2 minutes between the heating and air conditioning subsystem and the power supply subsystem, and 1 minute between the power supply subsystem and the lighting control subsystem. The marker content can be written as: D001: [Heating and Air Conditioning → Power Supply (2 minutes) → Lighting Control (1 minute)].

[0030] In this way, the peak offset paths identified across all time periods are standardized and represented as a set of misalignment chain markers, with each marker corresponding to an independent time anchor segment. The resulting misalignment chain markers not only fully express the peak misalignment relationships between various energy subsystems within specific time periods but also possess a clear structural format and time-series index, facilitating subsequent precise calibration and pseudo-synchronization segmentation of the time axis. Through the unified management of misalignment chain markers, the multi-source alignment problem of the entire campus's energy consumption data in the time domain gains a clear and controllable entry point.

[0031] A phase calibration trajectory is constructed based on the misalignment chain markers. Fine-grained time offset adjustments are made to the corresponding time anchors in the time anchor set along the phase calibration trajectory so that the energy consumption peaks can be restored to the true time sequence under a unified time reference. To achieve accurate time-series reconstruction of energy consumption peaks in each energy subsystem, it is necessary to construct a continuous and directional phase calibration trajectory based on the previously generated misalignment chain marker information. Using this trajectory as the path, fine-grained adjustments are then made to specific time anchors in the time anchor set that exhibit peak offsets. This adjustment process rearranges multiple energy consumption peaks that were originally misaligned on the time axis due to sampling reference deviations onto a unified time reference according to their actual occurrence order, thereby reconstructing the true time-series logic of energy consumption events. The specific implementation steps are as follows: After generating the misalignment chain markers, calibration paths that can be used for time anchor adjustment need to be extracted. The misalignment chain markers are organized by time period, with each marker containing the arrival order information of energy consumption peaks for each energy subsystem and their time offset relationships. Before calibration, the monitoring time range needs to be divided into several continuous, non-overlapping time segments based on the total energy consumption data, and target time periods with obvious energy consumption peak misalignment characteristics should be selected. The judgment criterion is that the peak records of multiple energy subsystems within the same time period exhibit asynchronous peak phenomena, i.e., peaks appear but their recording times are interleaved and cannot be aligned.

[0032] After filtering, the misalignment chain markers corresponding to the target time period are read, and the arrival order and time interval of the energy consumption peaks are extracted to form a sequential path. For example, in the time period from 08:00 to 08:30, if the peak of the power supply subsystem occurs at 08:10, the peak of the heating and air conditioning subsystem occurs at 08:12, and the peak of the lighting control subsystem occurs at 08:13, with differences of 2 minutes and 1 minute respectively, then a time sequence path consisting of the power supply subsystem → heating and air conditioning subsystem → lighting control subsystem is constructed. Subsequently, the same or similar sequential structures are identified in the time period from 08:30 to 09:00. If they exist, they are connected into a continuous calibration path spanning a longer time range. This path serves as the logical main line for subsequent adjustment of the time anchor point, clarifying the proper order and target arrangement of the peaks of each energy subsystem.

[0033] After extracting the phase calibration path, a unified mapping needs to be performed on the energy consumption peak anchor points of all energy subsystems involved in the path. Specifically, this involves constructing a continuous time axis from all anchor points in the time anchor set at a fixed time granularity (e.g., one minute), and sequentially reading the energy consumption data sequences of the lighting control, heating and air conditioning, power supply, water pump operation, fresh air exchange, and hot water supply subsystems. Within each data sequence, the identified energy consumption peak time point is extracted and located to a specific time anchor number within the unified time anchor set. For example, if the heating and air conditioning subsystem has a peak at 08:12, this peak is mapped to the time anchor numbered T812.

[0034] Through the above operations, a peak-anchor mapping table across subsystems can be obtained. Each row in the table corresponds to a subsystem, and each column corresponds to an anchor point number within a time period. Next, the anchor point positions that are inconsistent with the path order extracted in the first step need to be found in this table, i.e., those anchor points whose positions on the time axis are not logically consistent with the actual peak order. These inconsistent anchor points are misaligned anchor points, and precise time offset operations need to be performed in subsequent steps. This mapping process provides a structured representation of the positions of energy consumption peaks of different subsystems on a unified time axis, providing a specific target for adjusting the accuracy of time anchors.

[0035] After completing the anchor point mapping and identifying misaligned anchor points, fine-grained adjustments to their time and position are required according to the sequence and time interval requirements outlined in the calibration path. The basic principle of offset adjustment is to shift each misaligned anchor point to its proper logical position based on the peak arrival order and a unified time reference. For example, if the misalignment chain marker indicates that anchor point T810 in the power supply subsystem should precede T812 in the heating and air conditioning subsystem, then T810 needs to be moved forward by a certain amount of time to satisfy the sequence relationship.

[0036] During implementation, the offset adjustment of each misaligned anchor point involves the following operations: First, determine the current time position of the anchor point; second, calculate the time span by which the anchor point should be offset based on the sequence difference between adjacent anchor points in the calibration path; third, move the anchor point forward or backward within the time anchor set; fourth, reload the corresponding sampling data onto the adjusted anchor point. All operations are conducted without disrupting the overall structure of the anchor set, ensuring that the adjusted time anchor set retains its continuity, uniqueness, and integrity.

[0037] The above adjustments can be implemented in parallel across multiple subsystems. For misalignments involving multiple time periods, the anchor point offset process can be extended to multiple adjacent time anchor sets, maintaining the continuity of the time logic chain. Through offset adjustment, the originally misaligned energy consumption peaks of each energy subsystem are rearranged in true order on a unified time reference, thereby constructing a peak arrangement structure with time consistency.

[0038] The results of the offset adjustment need to be solidified to establish a complete, continuous, and accurate post-calibration time anchor sequence. The solidification process includes the following aspects: First, reassign anchor point numbers to all adjusted locations, constructing a new set of time anchors; second, ensure that the time intervals between anchor points in the new set maintain the original granularity, for example, each anchor point still represents one minute, and time overlaps or breaks are not allowed; third, organize the adjusted peak data of each energy subsystem into a new energy consumption time series according to the new anchor point locations; fourth, generate a calibration mapping table to record the correspondence between the original anchor points and the adjusted anchor points, facilitating subsequent data tracking and error management.

[0039] Once solidified, the new time anchor set will become the primary time-series reference in the energy consumption data processing workflow. Its structure reflects the actual occurrence order of peak values ​​in each subsystem, eliminating superposition biases caused by time misalignments. This time structure not only improves the accuracy of subsequent energy consumption merging simulations but also provides reliable data support for energy-saving potential assessment and carbon emission reduction pathway selection.

[0040] By setting a conflict isolation window based on the phase calibration trajectory, identifying and segmenting time segments containing pseudo-synchronization peaks, and eliminating the energy consumption values ​​that are misaligned and superimposed between various energy subsystems, a net energy consumption peak sequence is obtained. To prevent misjudgment of energy consumption peaks due to peak misalignment and superposition between different energy subsystems during energy consumption data merging, a conflict isolation window needs to be constructed using a unified time anchor set after phase calibration. Within these windows, abnormal overlapping of energy consumption data is identified and eliminated, ultimately generating a net energy consumption peak sequence containing only real physical events. The specific implementation steps are as follows: After completing the phase calibration of the peak time anchors for each energy subsystem, a conflict isolation window needs to be set under a unified time reference as the basic operating area for identifying the superposition of misaligned energy consumption data. The basis for setting the conflict isolation window is the peak occurrence time of each energy subsystem in the calibration trajectory. Taking each peak as the time center, a symmetrical time interval is constructed as the independent analysis area for that peak.

[0041] The specific operations include: First, extracting the time anchor points for all peak occurrences in the calibrated power supply subsystem, heating and air conditioning subsystem, lighting control subsystem, water pump drive subsystem, fresh air exchange subsystem, and hot water heating subsystem; Second, setting a symmetrical window with a duration of five minutes centered on each anchor point, with the start time of the window set to two and a half minutes before the anchor point time and the end time set to two and a half minutes after the anchor point time; Third, arranging the above time windows continuously on a unified time axis to ensure that there is no time overlap or blank areas between the windows; Fourth, numbering each window and recording the energy subsystem where its central peak occurs and the specific time anchor number.

[0042] Within the constructed conflict isolation window, all energy consumption records are meticulously analyzed to identify potential pseudo-synchronous peak phenomena. Pseudo-synchronous peaks refer to the phenomenon where the energy consumption peaks of different energy subsystems are physically misaligned, but are incorrectly identified as occurring at the same time in the timeline mapping. This is often caused by time base offsets or inconsistent sampling periods.

[0043] The specific identification process is as follows: First, for each conflict isolation window, extract the energy consumption records of all energy subsystems within that time period, including actual power values, peak duration, and slope changes; Second, within the window time interval, identify fluctuation characteristics in all energy consumption curves that are rapidly rising, short in duration, and have peak heights significantly higher than the average, and preliminarily locate them as peak events; Third, combine the logical order relationship between peaks of different subsystems in the calibration trajectory to compare whether these peaks overlap in time; Fourth, when the peak time interval of two or more different subsystems is detected to be less than the time anchor granularity (e.g., one minute), and this interval does not match the calibration order, it is determined that the overlap is a pseudo-synchronous peak, forming a misaligned superposition phenomenon.

[0044] After identifying pseudo-synchronization peaks, it is necessary to process the abnormal energy consumption superposition caused by them within the time window, removing energy consumption values ​​that lack actual physical basis, so that the final energy consumption data only retains the energy consumption events that actually occurred. The removal process is based on the "first-come, first-served" principle, that is, among multiple misaligned peaks, only the earliest subsystem peak appearing in the calibration order is retained, and the peaks of other time periods are determined to be non-real high consumption data caused by misalignment and are removed.

[0045] The specific steps are as follows: First, in each conflict isolation window where pseudo-synchronization exists, determine the subsystem to which the main peak should be retained according to the order of the calibration trajectory; Second, outside of this subsystem, mark all other subsystem peaks that appear in the same time window as misaligned peaks; Third, set the energy consumption value recorded at the time anchor points corresponding to these misaligned peaks to zero, or remove them from the total dataset so that they do not participate in energy consumption merging, load calculation, and emission reduction simulation; Fourth, reorganize the remaining peak data to ensure that only one physically meaningful peak event is retained in each time window, and there is no duplicate superposition.

[0046] After eliminating pseudo-synchronous energy consumption within the conflict isolation window, the remaining true peak data needs to be reorganized into a complete net energy consumption peak sequence according to a unified time reference. This sequence will serve as the data foundation for subsequent emission reduction assessments, energy-saving path deductions, and economic simulation calculations, and is required to have characteristics such as a clear time structure, a clear source of peaks, and continuous and readable data.

[0047] The construction process is as follows: First, extract the peak data retained in each conflict isolation window, including the peak time anchor number, peak size, duration, and the name of the energy subsystem to which the peak belongs; Second, arrange all peak data in chronological order to form a complete ascending sequence; Third, label each peak data item to clarify its source subsystem and attach phase calibration information to ensure subsequent traceability; Fourth, write the sequence into a dedicated peak index structure and align it with a unified time anchor set to form a net peak structure for cross-subsystem simulation.

[0048] This net energy consumption peak sequence will replace all high-consumption event descriptions in the original sampling sequence, possessing the ability to eliminate misalignment interference and reflecting the true energy consumption pattern. It has extremely high data value in cost-benefit calculations and carbon emission reduction path optimization.

[0049] A breathing-style time-domain patching control is performed on the net energy consumption peak sequence. Combined with the anti-resonance gating mechanism, the time anchor position is dynamically adjusted and the superposition window is contracted when the peaks converge, thereby achieving time synchronization and load stability control during the energy consumption merging process across energy subsystems. To ensure the integrity of time alignment and the stability of load curves when merging the net energy consumption peak data of multi-energy subsystems under a unified time reference, a breathing-style time-domain patching control operation must be performed after generating the net energy consumption peak sequence, along with an anti-resonance gating mechanism. During periods of high peak density, the anchor point position and peak carrying window width in the time anchor set are dynamically adjusted to avoid energy consumption amplification caused by short-term energy consumption concentration. This achieves dynamic balance control of energy consumption data throughout the entire cycle. The specific implementation steps are as follows: After constructing the net energy consumption peak sequence, a horizontal scan of the sequence is required based on a unified time anchor set to identify clustered segments where peaks are densely distributed over time. These segments often correspond to multiple energy subsystems experiencing peaks at approximately the same time. Although the effects of misalignment have been removed, a trend of concentrated energy consumption still exists at the statistical level. If left untreated, this could lead to misjudgments of phased load overload in simulation calculations.

[0050] The specific implementation method is as follows: A time sliding window is set with a granularity of one minute to divide the net peak sequence into continuous time observation segments. For each five-minute window, the number of energy subsystems exhibiting peaks within it, as well as the corresponding peak intensity changes, are counted. If three or more energy subsystems record peaks within a window, and the time interval between adjacent peaks is less than two minutes, the window is marked as a "peak clustering segment." All time periods meeting the above criteria are consecutively numbered, and their starting anchor point number, ending anchor point number, involved subsystem names, and peak times are recorded for subsequent structural initialization and anchor point adjustment.

[0051] After identifying the peak clustering sections, a patch buffer structure with time flexibility and adjustability needs to be constructed within these time periods. This structure is used to temporarily expand the representational capability of the time anchor set in the current section, allowing multiple high-intensity peaks to have sufficient temporal distribution space on the time axis, thereby reducing the load concentration caused by the mutual influence of peaks.

[0052] The specific implementation includes: using the central time anchor point of each cluster segment as a reference point, extending two time anchor points before and after it to form an initial patch structure covering five consecutive anchor points; in this structure, each anchor point is given adjustment permissions, that is, it is allowed to undergo small-range time offsets without affecting the continuity of the preceding and following data; at the same time, a total buffer capacity upper limit is marked for this structure, which is used to determine whether there is a peak excess; finally, the buffer structure is associated with the original set of time anchors, so that all anchor point offset operations are based on a unified time reference, ensuring that the adjustment behavior is logically continuous.

[0053] In the completed patch structure, a fine-grained time position adjustment operation is performed on all time anchor points within the peak clustering section, so that multiple peak events that originally occurred adjacently can be appropriately expanded on the time axis to form a more dispersed peak sequence structure, thereby alleviating the problem of short-term high load.

[0054] The specific operational steps are as follows: First, analyze the order and intensity of peak occurrences of each energy subsystem within the cluster segment; based on the order of intensity from weakest to strongest, prioritize adjusting the anchor points with smaller peak intensities; second, according to the original interval relationship between time anchor points, stagger the time anchor points of adjacent peaks, for example, adjust two anchor points with a one-minute interval to a two-minute interval, forming a buffer zone for load distribution; third, after each anchor point adjustment, update the index position of the anchor point in the time anchor set and rebind the peak data to ensure that the sampling time is consistent with the anchor point position; finally, throughout the entire adjustment process, ensure that the anchor point position does not cross the boundary of the cluster segment to guarantee the closure of the data structure and the controllability of the processing range.

[0055] Through the above adjustments, the originally highly concentrated peak data is dispersed over a wider time period, thereby reducing the instantaneous load peak and improving the statistical balance of the energy consumption sequence.

[0056] During anchor point adjustment, to further enhance the ability to suppress abnormal load concentration, an anti-resonance gating mechanism needs to be introduced within the clustering section. This mechanism is used to detect and handle short-term high load phenomena that may still occur after the peak offset. By compressing the effective time window in the patch structure, the total amount of simultaneous peaks is controlled.

[0057] The specific implementation method is as follows: First, a peak load limit for each aggregation segment is set, which is based on the maximum power change in historical operating data and does not exceed 80% of the total load capacity of each subsystem; Second, after the time anchor point adjustment is completed, the total peak value of the current aggregation segment is counted. If it exceeds the set limit, a gating mechanism is triggered; Third, after the gating mechanism is activated, the original five-anchor-point-width time window is compressed to a three-anchor-point-width time window, and only the data of the two subsystems with the highest peak intensity are retained, while other peak data are removed from the peak sequence; Finally, the compressed time window is remapped to a unified time reference, and the peak data index is updated to make it time-series independent.

[0058] This strategy can effectively prevent the formation of new local peak impacts during anchor point adjustment, enhance the stability of the overall merged load curve, and improve the credibility of subsequent simulation modeling.

[0059] This invention introduces a unified atomic time reference across multiple energy subsystems and establishes a cross-source time anchor set, providing a unified time reference for different energy acquisition processes and fundamentally eliminating the energy consumption data misalignment problem caused by sampling time differences. By performing misalignment detection, phase calibration, and time anchor offset adjustment on a unified time axis, the true time-series reconstruction of energy consumption peaks is achieved, enabling energy consumption curves to accurately reflect the actual load changes of each energy subsystem. This improves the accuracy and reliability of energy consumption data fusion, providing a real and effective data foundation for subsequent emission reduction simulations and energy-saving potential analysis.

[0060] This invention introduces conflict isolation and breathing-style time-domain weaving mechanisms based on the calibrated time anchor. By dynamically identifying pseudo-synchronization peaks and implementing load buffering and window contraction, it achieves time-series balance control of energy consumption accumulation sections, ensuring that the merged energy consumption curves of cross-energy subsystems remain time-synchronized and load-stable. This method effectively suppresses the resonance amplification effect caused by peak superposition, avoids the phenomenon of artificially inflated energy-saving intensity in emission reduction simulations, and guarantees the stability and feasibility of carbon emission reduction schemes in economic assessment and investment allocation decisions. Specific implementation examples: In multi-park operation scenarios, to achieve coordinated management and dynamic control of energy consumption and carbon emissions, the first step is to systematically collect energy consumption and carbon emission data from the past three to five years. The collected data covers various energy consumption types, including electricity, natural gas, water resources, and heat, as well as basic information directly related to carbon emission accounting, such as fuel consumption and operating load. Addressing the differences in statistical methods and collection frequencies among different parks and energy types, the data source channels, collection cycles, and time stamp methods are clearly defined during the data collection phase. All data is then uniformly integrated into the aforementioned atomic time reference system, ensuring that both historical and real-time data can be processed and accessed under a unified time reference.

[0062] After data collection, a full lifecycle electronic ledger was established for all types of energy-consuming equipment within the park. This ledger operates on a one-equipment-one-file principle, recording for each piece of equipment its model, installation location, park and building affiliation, operating parameters, maintenance records, design energy consumption threshold, and corresponding carbon emission coefficient. By linking the equipment ledger information with metering points and time anchor numbers, energy consumption data collected at any given time can be traced back to the specific equipment, achieving a precise mapping between energy consumption data and the actual equipment. This ledger structure provides a stable data foundation for subsequent energy consumption analysis, carbon emission accounting, and anomaly identification.

[0063] Based on the aforementioned data and records, a functional application system for energy and carbon collaborative management is constructed. This system uses a unified time anchor set as its main thread, mapping real-time collected multi-source energy consumption data onto the time anchor structure. Through processes such as misalignment detection, phase calibration, and conflict isolation, a net energy consumption peak sequence and a stable merged energy consumption sequence are formed. Based on the calibrated data results, statistical analysis is supported across multiple dimensions, including park, campus, building, department, and equipment type, continuously tracking energy consumption, carbon emissions, and their trends over time. Simultaneously, based on aligned data from historical time periods, year-on-year changes, month-on-month changes, and periodic comparison results are automatically generated, providing managers with a multi-faceted understanding of the energy and carbon operation situation.

[0064] At the management and presentation level, an energy and carbon management dashboard for the park is constructed to visualize calibrated real-time energy consumption, total carbon emissions, phased changes, and carbon emission quota usage progress. All indicators in the dashboard are derived from purification data results under a unified time reference, avoiding statistical biases caused by time misalignment and ensuring that management decisions are based on accurate and traceable data.

[0065] Building upon this foundation, a dual early warning management mechanism for safety and carbon emissions is further introduced. In the construction of the park's metering system, the hierarchical deployment of the park's main meter, building-level sub-meters, and dedicated meters for key equipment is clearly defined, and the data interfaces collected by each level of metering point are uniformly connected to the time anchor set mapping process. For newly installed or subsequently expanded metering instruments, only time reference alignment and anchor point binding need to be completed to integrate them into the overall energy consumption and carbon emission monitoring system, ensuring the system's continuous scalability.

[0066] Regarding the setting of early warning indicators, in response to carbon emission management needs, based on historical operating data and carbon quota targets, carbon emission threshold ranges are set for different industrial parks and different equipment types, and corresponding early warning levels are defined. For equipment operation safety needs, operating thresholds such as current and energy consumption fluctuation amplitude are set around high-energy-consuming key equipment. All early warning judgments are based on the net energy consumption peak sequence after time calibration and misalignment removal to avoid false alarms or missed alarms caused by pseudo-synchronous peaks.

[0067] When real-time monitoring data triggers preset threshold conditions, an early warning message is generated and simultaneously transmitted to the corresponding management and maintenance responsible parties through management interface pop-ups, information pushes, and other means. The early warning message clearly identifies the park location where the anomaly occurred, the associated equipment, the triggering indicators, and the suggested handling direction, facilitating rapid identification of the problem's source. After an early warning is triggered, the system records the entire process of early warning reception, on-site verification, handling operations, and result feedback according to a predetermined procedure, ensuring that each early warning event forms a complete time record chain and is linked to the corresponding time anchor and equipment ledger information.

[0068] Through the above implementation methods, a unified time benchmark, time anchor calibration mechanism, and energy-carbon collaborative management, along with dual early warning and control, are organically combined. This enables the park to achieve full-process traceability management of energy consumption and carbon emission data during long-term operation, and to promptly trigger early warnings and complete closed-loop handling when anomalies occur. This embodiment fully demonstrates the invention's comprehensive control capabilities over time consistency, data authenticity, and operational stability in multi-energy scenarios, providing reliable support for energy conservation and emission reduction decisions and operational safety assurance at the park level.

[0069] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for early warning and control of energy and carbon synergy in industrial parks, characterized in that, Includes the following steps: Establish a unified atomic time reference, set a unified time reference for multiple energy subsystems, generate a cross-source time anchor set under the unified time reference, and use the time anchor set to mark the sampling start time of each energy subsystem; Misalignment detection is performed based on cross-source time anchor sets. The arrival order of energy consumption peaks in each energy subsystem is compared according to a unified time reference, and misalignment chain markers are generated in continuous time periods to describe the time misalignment relationship of energy consumption peaks. A phase calibration trajectory is constructed based on the misalignment chain markers. Fine-grained time offset adjustments are made to the corresponding time anchors in the time anchor set along the phase calibration trajectory so that the energy consumption peaks can be restored to the true time sequence under a unified time reference. Based on the phase calibration trajectory, a conflict isolation window is set to identify and segment time segments containing pseudo-synchronization peaks, and the energy consumption values ​​of misalignment and superposition between energy subsystems are eliminated to obtain the net energy consumption peak sequence. A breathing-style time-domain patching control is performed on the net energy consumption peak sequence, and the time anchor position is dynamically adjusted and the superposition window is shrunk when the peaks converge, combined with the anti-resonance gating mechanism.

2. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 1, characterized in that, The steps for generating a cross-source time anchor set are as follows: A unified atomic time reference is established, and the unified atomic time signal is distributed to multiple energy collection points through a communication network, so that each energy collection point establishes a sampling time structure consistent with the unified time reference; Under a unified atomic time standard, time axes are divided to generate a cross-source time anchor set, and the time anchor set is matched with the sampling period of different energy subsystems. The sampling start anchor point of each energy collection point is determined based on the cross-source time anchor set, and the sampling start anchor point is bound to the sampling period to trigger periodic sampling; During the sampling process, new time anchors are continuously generated based on a unified atomic time reference, and the sampling behavior of each energy collection point is kept synchronized through the extension of the time anchor set.

3. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 2, characterized in that, The steps for generating misaligned chain markers are as follows: Under a unified atomic time standard, energy consumption sampling data from multiple energy subsystems are organized, and a unified time axis is established using a cross-source time anchor set. Based on a unified time axis, the energy consumption time series of each energy subsystem is scanned to identify and mark the peak energy consumption time anchor position within a continuous time anchor segment. By comparing the peak time anchors of multiple energy subsystems over a continuous time period, the arrival order of the energy consumption peaks of each energy subsystem is determined. Construct peak offset paths based on the arrival order and time interval of energy consumption peaks, and record the peak offset paths as misalignment chain markers for the corresponding time periods.

4. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 3, characterized in that, The generation of misaligned chain markers involves segmenting and identifying energy consumption peaks according to continuous time anchor segments, and constructing a directed offset relationship between the energy subsystem sequence and the peak time interval within each time anchor segment, so that each misaligned chain marker uniquely corresponds to a time anchor segment for subsequent continuous construction of phase calibration trajectories.

5. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 3, characterized in that, The steps for constructing a phase calibration trajectory and adjusting the time anchor based on the misalignment chain markers are as follows: The continuous time segments are divided according to the misalignment chain markers, and the arrival order and time interval of energy consumption peaks are extracted from the time segments where energy consumption peaks are misaligned, and a phase calibration path is constructed. Based on the phase calibration path, the peak energy consumption time points of each energy subsystem are mapped to the time anchor set to form a correspondence between peak values ​​and time anchors; Based on the peak order determined in the phase calibration path, fine-grained time offset adjustment is performed on the mapped misaligned time anchors to rearrange the energy consumption peaks according to a unified time reference. The time anchors after time offset adjustment are solidified to generate a set of calibrated time anchors, and a continuous time series of energy consumption peaks is formed accordingly.

6. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 5, characterized in that, The steps for setting a conflict isolation window and generating a net energy consumption peak sequence based on the phase calibration trajectory are as follows: Based on the phase calibration trajectory and time anchor set, a conflict isolation window is constructed with the energy consumption peak time anchor as the center under a unified time reference, and the conflict isolation windows are numbered consecutively. Energy consumption records of multiple energy subsystems are extracted within the conflict isolation window, and pseudo-synchronization peaks that are misaligned and superimposed in time are identified by combining phase calibration trajectory. The peak arrival order is determined according to the phase calibration trajectory. Within the conflict isolation window, misaligned and superimposed energy consumption values ​​are eliminated, and only the first arriving energy consumption peak is retained. The retained energy consumption peaks are sorted according to a unified time reference to form a continuous sequence of net energy consumption peaks.

7. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 6, characterized in that, Based on the phase calibration trajectory under a unified time reference, symmetrical time intervals are set with the energy consumption peak time anchor as the center, and adjacent conflict isolation windows are sequentially connected on a unified time axis so that each conflict isolation window only covers the influence range of a single peak, thereby avoiding the cross-over of different energy consumption peaks in the time dimension.

8. The method for early warning and control of energy and carbon synergy in industrial parks according to claim 6, characterized in that, The steps for performing breathing-type time-domain patching control and load stabilization regulation on the net energy consumption peak sequence are as follows: Based on a unified time anchor set, the peak sequence of net energy consumption is scanned to identify peak clusters where peaks are densely distributed in the time dimension; Within the peak clustering section, adjacent time anchors are extended based on the central time anchor to construct a time-elastic temporal patching buffer structure; Within the temporal patching buffer structure, fine-grained time position adjustments are performed on the time anchors corresponding to the peaks, so that adjacent peaks are dispersed on the time axis; After the time anchor adjustment is completed, an anti-resonance gating mechanism is introduced to implement contraction control on the time window when the peak total exceeds the set load limit, forming a stable energy consumption merging sequence.

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