Elevator energy consumption analysis method and system

Abstract

The invention relates to the technical field of elevator energy consumption analysis, and discloses an elevator energy consumption analysis method and system.The elevator energy consumption analysis method comprises the steps that elevator operation data are obtained, anchor point events are detected based on the elevator operation data, time alignment processing is conducted on the elevator operation data, and a synchronous data sequence with a unified time axis is generated; based on the synchronous data sequence, elevator running states are recognized, regeneration running stages are marked, and time segments corresponding to the elevator running states are output; carrying out integral calculation on the active power of the line in a time segment, realizing bottom consumption stripping in combination with a standby power reference, and outputting segment energy consumption through positive and negative power decomposition; and in the regeneration operation stage, feedback energy and braking energy are calculated according to the elevator operation data, feedback efficiency is calculated, and an energy consumption analysis result is output. According to the method, a reliable basis is provided for energy efficiency evaluation, abnormal early warning and operation optimization of the elevator system.

Description

Technical Field

[0001] The present invention relates to the technical field of elevator energy consumption analysis, and in particular to an elevator energy consumption analysis method and system. Background Art

[0002] Current elevator energy consumption assessment methods primarily rely on total power consumption data collected through energy meters, or simple state segmentation followed by power integration. While these methods can provide a macroscopic view of total power consumption, they suffer from significant deficiencies in detailed segmentation, energy consumption attribution, and the identification of the destination of regenerative energy. For one thing, elevator operation involves multiple state transitions (such as starting, acceleration, leveling, standby, and door operator operation), resulting in highly fluctuating power curves. A single integral often fails to accurately capture the energy consumption structure of each sub-stage. Furthermore, modern elevators generally incorporate energy regeneration mechanisms, but existing technologies lack effective means to distinguish the distribution and destination of regenerative energy, making it impossible to distinguish the actual proportion of energy losses due to feeder network, resistor dissipation, or unidentified energy losses.

[0003] Furthermore, in practical applications, there are numerous energy consumption analysis deviations caused by data alignment errors, ambiguous state boundary determination, and interference from base consumption. This makes the system output results unreproducible and unreliable, and it is difficult to provide high-quality support for energy-saving transformation or operation and maintenance decisions. Therefore, a unified modeling and energy consumption decomposition method for elevator operation data is urgently needed, which can achieve a systematic calculation framework for base consumption stripping, regenerative energy identification, and robust state segmentation. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: an elevator energy consumption analysis method, comprising: acquiring elevator operation data, detecting anchor events based on the elevator operation data, performing time alignment processing on the elevator operation data, and generating a synchronized data sequence with a unified time axis; Based on the synchronous data sequence, identify the elevator operation status and mark the regeneration operation stage, and output the time segment corresponding to each elevator operation status; In each time segment, the active power of the line is integrated and calculated, and the base power is stripped off by combining it with the standby power benchmark. The segmented energy consumption is then output by decomposing the positive and negative power. During the regenerative operation phase, the feedback energy and braking energy are calculated based on the elevator operation data, and the feedback efficiency is calculated to output the energy consumption analysis results.

[0006] As a preferred embodiment of the elevator energy consumption analysis method of the present invention, the elevator operation data includes line active power, DC bus voltage, DC bus current, traction motor angular velocity, motor electromagnetic torque, door machine operation status, brake resistor relay status, feedback device operation status, operation quadrant mark and time data; The anchor point event detection based on elevator operation data includes retrieving line active power, DC bus voltage and traction motor angular velocity from the elevator operation data, and setting power change threshold, bus voltage change threshold and angular acceleration threshold through on-site calibration; Detect anchor point events. When the line active power change amplitude exceeds the power change threshold, it is determined to be a power anchor point.

[0007] When the DC bus voltage changes by a threshold value, it is determined to be the bus voltage anchor point.

[0008] When the traction motor angular velocity change amplitude exceeds the speed change threshold, it is determined to be a speed anchor point.

[0009] As a preferred solution of the elevator energy consumption analysis method described in the present invention, the time alignment process includes taking the time data of the electric energy meter as the reference time, and the devices other than the electric energy meter as the non-reference devices, and establishing an affine mapping from the local time of the non-reference devices to the reference time; Will As a reference anchor sequence, the window length is determined according to the elevator operation data. ,exist Find the closest one on the axis ,when When creating a candidate pair , assign physical consistency confidence weight to each candidate pair and establish a candidate pair set, where, represents the reference anchor sequence; Indicates the timestamp of the mth power anchor point; Representation device The local timeline; Indicates non-reference device The first detected The timestamps of the anchor points, including the bus voltage anchor point and the speed anchor point; Indicates the window length; Based on the candidate pair set, the residual between the reference anchor point timestamp and the non-reference device anchor point timestamp is used as the regression target. According to the physical consistency confidence weight, the global correction parameter is calculated through weighted robust linear regression. Non-reference devices The original elevator operation data is mapped to the reference time through the global correction parameters to obtain the synchronized data sequence.

[0010] As a preferred solution of the elevator energy consumption analysis method described in the present invention, the identification of elevator operating states includes six states: standby, door machine operation, starting acceleration, uniform speed operation, regeneration operation, leveling alignment and door open hold. The time axis of the entire elevator operation cycle is divided into several time segments according to the synchronous data sequence, and each time segment corresponds to a unique elevator operating state.

[0011] As a preferred embodiment of the elevator energy consumption analysis method of the present invention, the output of segmented energy consumption by decomposing positive and negative power includes taking the median of the line active power within a fixed time window for the synchronous data sequence corresponding to the time segment of the standby operation state and removing 10% of abnormalities at both ends to obtain the base consumption power. The full time series power is corrected by the base consumption power to obtain an incremental power sequence stripped of the base consumption, which is expressed as: ; in, represents the incremental power; Indicates taking the maximum value; Indicates the line active power; Indicates base power consumption; Energy integration is performed for each operating state, and the original energy without stripping the base consumption and the incremental energy after stripping the base consumption are calculated respectively, and the total base consumption energy is calculated; Decompose the line active power into positive power and negative power and integrate them separately to obtain positive energy and negative energy; Using two sets of calibers with segmented sum consistency and hierarchical caliber consistency and bipolar closure to form a triangulation check, it can self-prove consistency without relying on external measurement devices and automatically locate the source of the problem; Make a micro-displacement perturbation on each state boundary, recalculate the original energy and incremental energy respectively, and calculate the sensitivity index to measure the sensitivity of the segmented result to the boundary perturbation, which is expressed as: ; in, The boundary sensitivity index of the elevator operation state s; represents the positive energy after disturbance; represents incremental energy; represents the negative energy after disturbance; Represents a small constant that prevents division by zero; represents the amplitude of boundary micro-displacement disturbance.

[0012] As a preferred embodiment of the elevator energy consumption analysis method of the present invention, the calculation of the regenerative energy and the braking energy based on the elevator operation data includes calculating the instantaneous DC side power using the DC bus voltage and current, determining the positive and negative directions of the instantaneous power through sign factor self-calibration, selecting the sign factor that maximizes the correlation between the DC side power and the line side negative power during the regenerative operation phase, and obtaining a DC side power sequence with consistent directions; During the regeneration operation phase, the non-negative part of the DC side power sequence is integrated over time to obtain the total regenerative energy value; At each sampling moment of the synchronous data sequence, the brake resistor status and feedback device status are obtained based on the elevator operation data, and the energy destination is determined according to the priority rules: When the braking resistor is connected, the regenerative power at the corresponding moment is included in the braking energy; When the braking resistor is not connected and the regenerative device is in operation, the regenerative power at the corresponding moment is included in the regenerative energy; When the feedback device signal is missing, the energy not connected to the braking resistor is counted as feedback energy by default; When the braking resistor and the feedback device are both connected, the braking resistor takes priority, and the negative power on the line side is used as the upper limit of the feedback energy. The braking energy and regenerative energy are accumulated separately and compared with the total regenerative energy. If there is an unattributable difference, it is marked as unknown energy.

[0013] As a preferred embodiment of the elevator energy consumption analysis method of the present invention, the output energy consumption analysis results include statistics on the duration, number of occurrences, segmented energy values ​​and their proportions of each operating state, and calculation of the energy consumption intensity per unit time for horizontal comparison; Summarize the energy consumption analysis results, output the total energy consumption of the original energy and incremental energy respectively, and compare them; The total value and destination of regenerative energy are counted, including feedback energy, braking energy, and energy with unknown destination, and the proportion of the three energy components is calculated. The regenerated energy is mapped to the state interval, so that the energy consumption results of each operation stage and the regeneration destination results are output together to form a complete energy consumption analysis summary result.

[0014] An elevator energy consumption analysis system using any of the methods described in the present invention, wherein: an acquisition module acquires elevator operation data, detects anchor point events based on the elevator operation data, performs time alignment processing on the elevator operation data, and generates a synchronized data sequence with a unified time axis; The segmentation module identifies the elevator operation state and marks the regeneration operation phase based on the synchronous data sequence, and outputs the time segment corresponding to each elevator operation state; The calculation module integrates the active power of the line within the time segment, combines it with the standby power benchmark to achieve base consumption separation, and outputs the segmented energy consumption through positive and negative power decomposition; The output module calculates the feedback energy and braking energy according to the elevator operation data during the regeneration operation phase, calculates the feedback efficiency, and outputs the energy consumption analysis results.

[0015] Beneficial effects of the present invention: The method of the present invention completes operation clock alignment, state identification, energy segmentation and feedback destination discrimination based on operation data. By introducing a unified time axis with the electric energy meter as a reference, a segmented integration method based on bottom consumption stripping, positive and negative power deconstruction and consistency closure verification mechanism, the attribution bias and result instability problems existing in traditional analysis are effectively avoided. The introduction of feedback energy destination modeling and boundary sensitivity assessment mechanism realizes the quantitative decomposition of the regenerative energy flow and the accurate characterization of the state boundary stability. Finally, through a unified indicator system and regularized anomaly judgment, structured energy consumption characteristics and multi-dimensional diagnostic results are output, providing a reliable basis for energy efficiency evaluation, anomaly warning and operation optimization of elevator systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is an overall flow chart of an elevator energy consumption analysis method provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0018] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0019] Example 1, with reference to Figure 1 , as an embodiment of the present invention, provides an elevator energy consumption analysis method, comprising: S1: Acquire elevator operation data, detect anchor events based on the elevator operation data, perform time alignment on the elevator operation data, and generate a synchronized data sequence with a unified time axis.

[0020] In a preferred embodiment of the present invention, the elevator operation data is first collected and cached to provide a complete and synchronized raw data basis for subsequent state recognition, energy consumption decomposition and determination of the destination of recovered energy.

[0021] Specifically, a three-phase electronic energy meter is connected to the power distribution side of the elevator drive circuit. Line active power is read in real time via a standard communication interface (such as RS485 / Modbus RTU or Ethernet / Modbus TCP), with the sampling time recorded internally by the energy meter. Simultaneously with line-side power acquisition, the elevator inverter's monitoring interface periodically reads the DC bus voltage, DC bus current, traction motor angular velocity, and motor electromagnetic torque or stator q-axis current. The DC bus voltage and current are used to calculate energy during the regeneration phase, while the traction motor angular velocity and electromagnetic torque are used to determine the operating state and operating quadrant.

[0022] To identify the door operator's operating status, the door operator's operating status signal is collected at the door operator controller's output. To determine the destination of regenerative energy, the brake resistor relay status signal is collected at the inverter's control terminals or external I / O module, and preferably, the feedback device's operational status signal is collected. Furthermore, the operating quadrant flag is directly read from the inverter's status bits. If this information is not directly available, the operating quadrant flag is calculated based on the sign of the product of angular velocity and electromagnetic torque.

[0023] All of the above-mentioned acquisition channels sample data at the highest stable sampling frequency supported by their respective devices, and maintain the correspondence between the device's internal time and the acquired value. The collected data is written to a circular buffer in local memory as a key-value pair consisting of "timestamp + signal value." The cache capacity should cover at least one complete elevator operation cycle to ensure the time span required for subsequent processing. This circular buffer supports fast retrieval by time interval, ensuring efficient access to the required raw data for steps such as state identification, time alignment, and energy consumption integration.

[0024] Furthermore, in order to establish a unified time reference between different acquisition devices, it is necessary to extract anchor events with physical synchronization significance from the elevator operation data. These events will show obvious changes simultaneously on multiple signal channels during the elevator operation process and can serve as reference points for subsequent multi-source time alignment.

[0025] Line active power, DC bus voltage, and traction motor angular velocity were selected as candidate anchor point signals. These three types of signals exhibit distinct and repeatable variations during elevator startup, acceleration, deceleration, and regenerative braking, making them suitable physical markers for time alignment.

[0026] On the line active power signal channel, when the line active power rises or falls significantly within a short period of time, and the magnitude of the change exceeds a preset power change threshold, this moment is identified as a power anchor point event. This type of event typically occurs during elevator startup, acceleration, deceleration, or regenerative braking, and is the most representative change point on the power channel.

[0027] On the DC bus voltage signal channel, when the DC bus voltage fluctuates significantly within a short period of time, and the fluctuation exceeds a preset voltage change threshold, this moment is identified as a bus voltage anchor event. This event often occurs during the energy exchange phase, such as when regenerative energy is fed back or when a braking resistor absorbs energy, causing the bus voltage to rise or fall rapidly.

[0028] On the traction motor angular velocity signal channel, when the rate of change of the traction motor angular velocity increases or decreases significantly within a short period of time, and the magnitude of the change exceeds a preset velocity change threshold, this moment is identified as a velocity anchor point event. This type of event often occurs at velocity turning points during acceleration, deceleration, or leveling, and accurately reflects changes in the elevator's operating phase.

[0029] For the detected power anchor points, bus voltage anchor points, and speed anchor points, their occurrence times and signal sources are recorded separately and stored in a unified anchor event set. In the subsequent multi-source time alignment step, the power anchor point is preferentially used as the reference anchor point for time alignment, while the bus voltage anchor point and speed anchor point are used as auxiliary matching information to achieve time consistency of cross-device data. Through the anchor event detection process, even if there are deviations in the internal time of different acquisition devices, the data time base can be unified through events with consistent physical characteristics, providing an accurate time alignment foundation for subsequent segmented energy consumption calculations and regenerative energy destination analysis.

[0030] Furthermore, the time data of the energy meter is used as the reference time, and the devices other than the energy meter are non-reference devices (including inverters, door controllers, I / O modules, etc.). An affine mapping is established from the local time of the non-reference devices to the reference time.

[0031] To calculate the mapping parameters, As a reference anchor sequence, the window length is determined according to the elevator operation data. ,exist Find the closest one on the axis ,when When creating a candidate pair , assign physical consistency confidence weight to each candidate pair and establish a candidate pair set, where, represents the reference anchor sequence; Indicates the timestamp of the mth power anchor point; Representation device The local timeline; Indicates non-reference device The first detected The timestamps of the anchor points, including the bus voltage anchor point and the speed anchor point; Indicates the window length.

[0032] It should be noted that the time data of the electricity meter refers to the real-time clock data used for measurement and event recording inside the electronic three-phase electricity meter. It is the direct time reference for power data, with high accuracy, good stability, and small long-term drift. It is located at the energy entrance and is directly related to the energy consumption integral. This makes it possible to use its time axis as a unified reference to reduce the cumulative errors and misalignment problems in the subsequent energy consumption decomposition.

[0033] Based on the candidate pair set, the residual between the reference anchor point timestamp and the non-reference device anchor point timestamp is used as the regression target. According to the physical consistency confidence weight, the global correction parameter is calculated by weighted robust linear regression, which is expressed as: ; in, Indicates the time offset between device i and the reference time; Indicates the scaling factor of device i's clock relative to the reference time; Indicates the parameter value that minimizes the sum in the brackets; Indicates the anchor point index on the reference clock side; Indicates the anchor point index on the signal source side; represents the set of candidate pairs; represents the weight coefficient; represents the residual metric function; represents the overall translation correction; Indicates rate correction.

[0034] Getting global parameters Finally, to address the clock drift problem that may occur during long-term operation, the above matching and estimation process is further repeated within a sliding time window to obtain local parameters that change with time, and a continuous time mapping function is constructed through linear interpolation or piecewise affine method to eliminate the relative drift between devices.

[0035] After completing the time mapping parameter calculation for all non-reference devices, their original data sequences are mapped to a unified time axis. Continuous signals (such as DC bus voltage, DC bus current, traction motor angular velocity, and motor electromagnetic torque) are calculated using linear interpolation, while discrete or binary signals (such as door operator operating status, brake resistor relay status, and feedback device operation status) are calculated using the zero-order hold method to ensure that all signal values ​​correspond to the same physical time point at any time.

[0036] Finally, the mapping parameters, weighted residual root mean square, number of paired anchor points and elimination ratio of each device are output. These results will be used for subsequent state identification and segmented energy consumption calculation.

[0037] It should be noted that the method of the present invention is not limited to global fixed mapping, but obtains local time mapping parameters through a sliding time window to form a continuous changing , thereby eliminating synchronization errors caused by clock drift during long-term operation. Without modifying the existing hardware clock system or relying on dedicated synchronization protocols, a high-precision, unified time base for elevator operation data can be achieved at the analysis layer. This provides physically consistent signal boundaries for subsequent state-based segmented energy consumption integration, significantly improving the reproducibility and credibility of energy consumption attribution results.

[0038] S2: Based on the synchronous data sequence, identify the elevator operation status and mark the regeneration operation stage, and output the time segment corresponding to each elevator operation status.

[0039] Furthermore, after completing the multi-source time alignment, based on the elevator operation data on the unified time axis, the finite state machine method is used to perform state identification and time segmentation on the entire elevator operation process.

[0040] Specifically, we first establish a set of elevator operation states, including standby, door operator operation, start-up acceleration, constant speed operation, regeneration operation, leveling alignment, and door hold. This state set covers the main physical links in an elevator operation cycle and provides complete semantic support for energy consumption attribution.

[0041] In the state judgment process, the signals on the unified time axis are mainly used, including the traction motor angular velocity, angular velocity derivative, door machine operation status signal and operation quadrant mark.

[0042] By defining judgment thresholds for various states, different operating stages can be identified: When the absolute value of the traction motor angular velocity is lower than the preset threshold and the door crane is stationary, it is determined to be in standby state; When the door machine controller state is action, it is determined to be the door machine action state; When the angular velocity derivative is greater than the acceleration threshold and the quadrant flag is positive, it is determined to be in the starting acceleration state; When the angular velocity derivative is close to zero and the angular velocity is greater than the minimum operating value, it is determined to be in a uniform speed running state; When the angular velocity derivative is less than the negative acceleration threshold and the quadrant flag is negative, it is determined to be in the regeneration operation state; When the angular velocity gradually approaches zero and is detected to be close to the floor position, it is determined to be in the leveling alignment state; when the door remains open after the door machine action is completed, it is determined to be in the door open holding state.

[0043] Using these rules, the elevator's operation is divided into several time intervals, each corresponding to a unique state label, resulting in a complete set of state intervals. This state sequence not only reflects the physical logic of the elevator's operation but also provides accurate time boundaries for the segmented energy consumption integration in subsequent steps.

[0044] S3: In the time segment, the line active power is integrated and calculated, and the base consumption is stripped by combining it with the standby power benchmark. The segmented energy consumption is output through positive and negative power decomposition.

[0045] After completing state identification and time segmentation, the energy consumption of the entire elevator operation process is calculated and verified in segments. The purpose of this step is to attribute energy consumption to each operating state interval based on line power data. On this basis, the base power consumption is removed, while the positive and negative power decomposition is retained. At the same time, a consistency verification and boundary sensitivity assessment mechanism are established to ensure the interpretability and reproducibility of the energy consumption analysis results.

[0046] First, the state interval set is normalized. Specifically, if there is a small time gap between adjacent intervals that is less than a preset threshold, the gap is merged into the previous interval. If there is overlap, only one interval is retained according to the established priority rules. This preprocessing ensures that the entire timeline is uniquely covered, without gaps or overlaps.

[0047] For the synchronous data sequence corresponding to the time segment of the standby operation state, within a fixed time window, the median of the line active power is taken and 10% of the abnormality at both ends is removed to obtain the base consumption power. The full time series power is corrected by the base consumption power to obtain the incremental power sequence stripped of the base consumption, which is expressed as: ; in, represents the incremental power; Indicates taking the maximum value; Indicates the line active power; Indicates base power consumption.

[0048] It should be noted that the elevator system has a relatively stable "base consumption" component, that is, the basic electrical energy required by the elevator when in standby mode (including control systems, lighting, ventilation, etc.). This part of energy will continue to exist in any operating state. If the original power is directly integrated, the base consumption will be evenly distributed among all operating states, thereby masking the actual incremental differences in different states. Therefore, the present invention introduces the idea of ​​"base consumption stripping" in the segmented energy consumption calculation: by robustly estimating the power signal in the standby interval, the base consumption power value is obtained, and it is stripped from the full-process data to construct an incremental power sequence, so that the energy consumption structure consists of two parts: base consumption and incremental. In this way, the energy consumption of short-term states such as door machine movement or leveling can be presented separately after eliminating the base consumption, which is more in line with physical reality.

[0049] After obtaining the power sequence, energy is integrated for each state interval. Integrating the original power yields the original value segment energy, while integrating the incremental power yields the incremental segment energy. The total base energy is also calculated. The original value approach ensures consistency with traditional energy accounting methods, while the incremental approach better reflects energy consumption that can be optimized.

[0050] Furthermore, the line power is decomposed into positive power and negative power: when the power is greater than zero, it is recorded as positive power, and when the power is less than zero, it is recorded as the absolute value of negative power. These two values ​​are then integrated to obtain positive energy and negative energy. The negative energy reflects the possible regenerative feedback during elevator operation and serves as an auxiliary indicator for subsequent energy destination determination.

[0051] To ensure the accuracy of the segmented energy consumption results, the present invention incorporates three consistency checks in this step: first, checking whether the sum of the segmented energies is equal to the overall power integration result; second, checking whether the sum of the incremental segmented energy and the base energy is equal to the overall power integration result; and third, checking whether the positive and negative energy differences are consistent with the overall power integration result. If any of these conditions are not met, a backtracking mechanism is triggered, re-adjusting the state interval segmentation or base energy estimation.

[0052] Finally, to prevent the segmentation results from being too sensitive to boundary divisions, the present invention introduces a boundary sensitivity evaluation mechanism. Specifically, a small perturbation is applied to the boundaries of each state interval, the energy results are recalculated, and the boundary sensitivity index is obtained: ; in, The boundary sensitivity index of the elevator operation state s; represents the positive energy after disturbance; represents incremental energy; represents the negative energy after disturbance; represents a small constant that prevents division by zero; Represents the amplitude of boundary micro-displacement disturbance.

[0053] If the sensitivity exceeds a preset threshold, the state interval is marked as a boundary unstable interval, triggering parameter correction in the previous step. Through the above steps, the present invention can form a clear "base consumption + incremental" hierarchical energy consumption structure without relying on additional hardware. At the same time, it utilizes positive and negative power decomposition and multiple consistency checks to ensure the reliability of the results. It also provides a quantitative robustness measure through the boundary sensitivity index, making elevator energy consumption analysis explainable, reproducible, and auditable.

[0054] S4: During the regenerative operation phase, the feedback energy and braking energy are calculated based on the elevator operation data, and the feedback efficiency is calculated, and the energy consumption analysis results are output.

[0055] Furthermore, to identify whether the energy generated by the elevator during regeneration is fed back into the grid or dissipated as heat via the braking resistor, and to assess the efficiency of regeneration, we perform the regeneration energy destination identification and efficiency assessment steps. This step, based on multi-source data on a unified timeline, follows the process of "identifying regeneration → calibrating DC calibers → allocating destinations according to rules → cross-caliber consistency verification → calculating efficiency ratios → state-by-state mapping → quality control and output traceability."

[0056] The directional consistency of the instantaneous DC power is established. The DC power is obtained by multiplying the DC bus voltage and the DC bus current. Taking into account the differences in the definition of current direction among different brands of devices, the present invention automatically calibrates the DC power sign factor within the regeneration mask based on the correlation of the line-side negative power sequence. Specifically, the sign factor that maximizes the correlation between the DC power and the line-side negative power within the regeneration interval is selected as the result of a one-time on-site calibration, and the DC power direction is corrected accordingly. This correction ensures that the caliber of "DC regenerative power is positive" is consistent with the caliber of "line-side negative power is positive", providing a unified benchmark for subsequent energy distribution.

[0057] After the DC caliber is unified, the DC-side regenerative energy is calculated. This calculation method involves discretely integrating the non-negative portion of the corrected DC-side regenerative power along the unified time axis over the time segments corresponding to the regenerative operation phase to obtain the total regenerative energy for the entire process. This energy only counts the portion of the system that is actually regenerating and where the DC-side power is directed toward the busbar, avoiding the inclusion of non-regenerative periods.

[0058] The distribution of the regenerated energy follows clear priority rules: When the braking resistor is connected, the regenerative power at the corresponding moment is included in the braking energy; When the braking resistor is not connected and the regenerative device is in operation, the regenerative power at the corresponding moment is included in the regenerative energy; When the feedback device signal is missing, the energy not connected to the braking resistor is counted as feedback energy by default; When the braking resistor and the feedback device are both connected, the braking resistor takes priority, and the negative power on the line side is used as the upper limit of the feedback energy. The three allocation methods are mutually exclusive at the same time, ensuring that each portion of regenerative energy is allocated to only one destination. Braking energy and regenerative energy are accumulated separately and compared with the total regenerative energy. Any unattributed difference is marked as unknown energy.

[0059] In order to verify the consistency of the calibers of the DC side and the line side, the present invention introduces a cross-caliber consistency check. Under the regeneration mask constraint, the negative power sequence on the line side is integrated to obtain the negative energy during the regeneration period on the line side. Subsequently, the total energy determined by the DC side to be fed back to the power grid is compared with the negative energy on the line side, and a tolerance threshold is set to determine whether the two are within the consistency range. If there is inconsistency, a backtracking check is performed in sequence: whether the DC side power sign factor calibration is correct, whether the synchronization data sequence deviates, and whether the elevator operation state boundary needs to be refined. This verification mechanism balances the results under different physical calibers to ensure the robustness of destination discrimination.

[0060] After obtaining the total regenerative energy and its respective distributions, efficiency and ratio indicators are calculated. Regeneration efficiency is defined as the ratio of energy fed back to the grid to the total regenerative energy; braking ratio is defined as the ratio of energy dissipated by the braking resistor to the total regenerative energy; and unknown ratio quantifies the proportion of unclassified energy relative to the total regenerative energy. When the total regenerative energy is zero, the above ratios are treated as zero or undefined for safety reasons and are explicitly indicated in the report to prevent misinterpretation.

[0061] To maintain consistency with the segmented energy consumption caliber, this invention maps regenerative energy and its destination to state intervals for statistical analysis. Preferably, the regenerative operating state interval is decomposed specifically, and the energy fed back to the grid and the energy dissipated by the brake resistor within this interval are accumulated separately. If necessary, the same method can be applied to other state intervals. This one-to-one interval mapping allows the destination determination results to be compared and analyzed with the segmented energy consumption results under the same time semantics, maintaining a consistent technical caliber.

[0062] Furthermore, the duration, number of occurrences, and corresponding energy consumption of each state interval are statistically analyzed. The energy contribution of the increased diameter after stripping out the base power consumption is calculated, thereby determining the distribution of each state within the overall energy consumption structure. The energy consumption intensity per unit time of each state is also summarized, allowing for horizontal comparison of energy efficiency levels across different states.

[0063] In terms of regenerative energy, the total regenerative energy, feedback energy, braking energy and energy of unknown destination are summarized, and the corresponding proportional indicators are calculated. Through this statistical result, the distribution of regenerative energy during elevator operation can be clearly displayed, and the consistency between the DC side and the line side can be further checked.

[0064] On this basis, multiple regularized judgment criteria are set, such as: excessive standby energy consumption, abnormal door crane operation energy consumption or frequency, abnormal regenerative energy distribution during deceleration, excessive difference in regenerative energy between the DC and line sides, consistency check failure, unstable state boundaries, and missing or conflicting data. Any indicator that triggers any of these rules is marked as abnormal and graded according to different levels, such as prompt, warning, and severe, to form a systematic abnormality list.

[0065] Ultimately, the output of the method includes three types of content: first, a summary of energy consumption by state, clearly listing the duration, number of occurrences, energy consumption value, and proportion; second, a summary of the destination of regenerative energy, including energy breakdown by feed-in, braking dissipation, and unidentified destination; and third, an anomaly record list, detailing the anomaly category, trigger interval, and the corresponding relationship between indicator value and threshold, interconnected with previous steps for easy traceability. All results are accompanied by output parameter version numbers and threshold settings to ensure traceability for subsequent comparisons and audits.

[0066] Through the above-mentioned indicator summarization and anomaly judgment links, the method of the present invention forms a complete closed loop in technical logic: it not only realizes the accurate decomposition of segmented energy consumption and the determination of the destination of regenerated energy, but also converts energy consumption characteristics into structured data and regularized labels through multi-dimensional statistics and anomaly recognition mechanisms.

[0067] Example 2: In an exemplary embodiment, an elevator energy consumption analysis system is also provided, including an acquisition module for acquiring elevator operation data, detecting anchor point events based on the elevator operation data, performing time alignment processing on the elevator operation data, and generating a synchronized data sequence with a unified time axis.

[0068] The segmentation module identifies the elevator operation status and marks the regeneration operation stage based on the synchronous data sequence, and outputs the time segment corresponding to each elevator operation status.

[0069] The calculation module integrates the active power of the line within the time segment, combines it with the standby power benchmark to achieve base consumption stripping, and outputs the segmented energy consumption through positive and negative power decomposition.

[0070] The output module calculates the feedback energy and braking energy according to the elevator operation data during the regeneration operation phase, calculates the feedback efficiency, and outputs the energy consumption analysis results.

[0071] If the above functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0072] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0073] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, and then editing, interpreting, or processing in another suitable manner as necessary, and then storing it in a computer memory.

[0074] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0075] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for analyzing elevator energy consumption, characterized in that: include: Acquire elevator operation data, detect anchor events based on the elevator operation data, perform time alignment on the elevator operation data, and generate a synchronized data sequence with a unified time axis; Based on the synchronous data sequence, identify the elevator operation status and mark the regeneration operation stage, and output the time segment corresponding to each elevator operation status; In each time segment, the active power of the line is integrated and calculated, and the base power is stripped off by combining it with the standby power benchmark. The segmented energy consumption is then output by decomposing the positive and negative power. During the regenerative operation phase, the feedback energy and braking energy are calculated based on the elevator operation data, and the feedback efficiency is calculated to output the energy consumption analysis results.

2. The elevator energy consumption analysis method according to claim 1, characterized in that: The elevator operation data includes line active power, DC bus voltage, DC bus current, traction motor angular velocity, motor electromagnetic torque, door machine operation status, brake resistor relay status, feedback device operation status, operation quadrant mark and time data; The anchor point event detection based on elevator operation data includes retrieving line active power, DC bus voltage and traction motor angular velocity from the elevator operation data, and setting power change threshold, bus voltage change threshold and angular acceleration threshold through on-site calibration; Detect anchor point events. When the line active power change amplitude exceeds the power change threshold, it is determined to be a power anchor point. When the DC bus voltage changes by a threshold value, it is determined to be the bus voltage anchor point; When the traction motor angular velocity change amplitude exceeds the speed change threshold, it is determined to be a speed anchor point.

3. The elevator energy consumption analysis method according to claim 2, characterized in that: The time alignment process includes taking the time data of the electric energy meter as the reference time, and the devices other than the electric energy meter as the non-reference devices, and establishing an affine mapping from the local time of the non-reference devices to the reference time; Will As a reference anchor sequence, the window length is determined according to the elevator operation data. ,exist Find the closest one on the axis ,when When creating a candidate pair , assign physical consistency confidence weight to each candidate pair and establish a candidate pair set, where, represents the reference anchor sequence; Indicates the timestamp of the mth power anchor point; Representation device The local timeline; Indicates non-reference device The first detected The timestamps of the anchor points, including the bus voltage anchor point and the speed anchor point; Indicates the window length; Based on the candidate pair set, the residual between the reference anchor point timestamp and the non-reference device anchor point timestamp is used as the regression target. According to the physical consistency confidence weight, the global correction parameter is calculated through weighted robust linear regression. Non-reference devices The original elevator operation data is mapped to the reference time through the global correction parameters to obtain the synchronized data sequence.

4. The elevator energy consumption analysis method according to claim 3, characterized in that: The identification of the elevator operation status includes six types: standby, door machine action, starting acceleration, uniform speed operation, regeneration operation, leveling alignment and door open hold. The time axis of the entire elevator operation cycle is divided into several time segments according to the synchronization data sequence, and each time segment corresponds to a unique elevator operation status.

5. The elevator energy consumption analysis method according to claim 4, characterized in that: The method of outputting segmented energy consumption by decomposing positive and negative power includes taking the median of the line active power in a fixed time window for the synchronous data sequence of the time segment corresponding to the standby operation state and removing 10% of abnormalities at both ends to obtain the base consumption power. The full time series power is corrected by the base consumption power to obtain an incremental power sequence stripped of the base consumption, which is expressed as: ； in, represents the incremental power; Indicates taking the maximum value; Indicates the line active power; Indicates base power consumption; Energy integration is performed for each operating state, and the original energy without stripping the base consumption and the incremental energy after stripping the base consumption are calculated respectively, and the total base consumption energy is calculated; Decompose the line active power into positive power and negative power and integrate them separately to obtain positive energy and negative energy; Using two sets of calibers with segmented sum consistency and hierarchical caliber consistency and bipolar closure to form a triangulation check, it can self-prove consistency without relying on external measurement devices and automatically locate the source of the problem; Make a micro-displacement perturbation on each state boundary, recalculate the original energy and incremental energy respectively, and calculate the sensitivity index to measure the sensitivity of the segmented result to the boundary perturbation, which is expressed as: ； in, The boundary sensitivity index of the elevator operation state s; represents the positive energy after disturbance; represents incremental energy; represents the negative energy after disturbance; represents a small constant that prevents division by zero; Represents the amplitude of boundary micro-displacement disturbance.

6. The elevator energy consumption analysis method according to claim 5, characterized in that: Calculating the regenerative energy and braking energy based on the elevator operation data includes calculating the instantaneous power on the DC side using the DC bus voltage and current, determining the positive and negative directions of the instantaneous power through self-calibration of a sign factor, selecting a sign factor that maximizes the correlation between the DC side power and the line side negative power during the regenerative operation phase, and obtaining a DC side power sequence with consistent directions; During the regeneration operation phase, the non-negative part of the DC side power sequence is integrated over time to obtain the total regenerative energy value; At each sampling moment of the synchronous data sequence, the brake resistor status and feedback device status are obtained based on the elevator operation data, and the energy destination is determined according to the priority rules: When the braking resistor is connected, the regenerative power at the corresponding moment is included in the braking energy; When the braking resistor is not connected and the regenerative device is in operation, the regenerative power at the corresponding moment is included in the regenerative energy; When the feedback device signal is missing, the energy not connected to the braking resistor is counted as feedback energy by default; When the braking resistor and the feedback device are both connected, the braking resistor takes priority, and the negative power on the line side is used as the upper limit of the feedback energy. The braking energy and regenerative energy are accumulated separately and compared with the total regenerative energy. If there is an unattributable difference, it is marked as unknown energy.

7. The elevator energy consumption analysis method according to claim 6, characterized in that: The output energy consumption analysis results include statistics on the duration, number of occurrences, segmented energy values ​​and their proportions of each operating state, and calculation of the energy consumption intensity per unit time for horizontal comparison; Summarize the energy consumption analysis results, output the total energy consumption of the original energy and incremental energy respectively, and compare them; The total value and destination of regenerative energy are counted, including feedback energy, braking energy, and energy with unknown destination, and the proportion of the three energy components is calculated. The regenerated energy is mapped to the state interval, so that the energy consumption results of each operation stage and the regeneration destination results are output together to form a complete energy consumption analysis summary result.

8. An elevator energy consumption analysis system, applied to an elevator energy consumption analysis method according to any one of claims 1 to 7, characterized in that: include, The acquisition module acquires elevator operation data, detects anchor events based on the elevator operation data, performs time alignment on the elevator operation data, and generates a synchronized data sequence with a unified time axis; The segmentation module identifies the elevator operation state and marks the regeneration operation phase based on the synchronous data sequence, and outputs the time segment corresponding to each elevator operation state; The calculation module integrates the active power of the line within the time segment, combines it with the standby power benchmark to achieve base consumption separation, and outputs the segmented energy consumption through positive and negative power decomposition; The output module calculates the feedback energy and braking energy according to the elevator operation data during the regeneration operation phase, calculates the feedback efficiency, and outputs the energy consumption analysis results.

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