Method and system for realizing elevator energy feedback data communication

Abstract

The invention provides a method and system for achieving elevator energy feedback data communication. The method comprises the steps that multi-modal data are collected, and fault features are extracted, encrypted and packaged; and after decryption, phase deviation of elevator operation and power grid voltage is calculated by utilizing an algorithm, a current phase is synchronously fed back, and a feedback instruction is generated. Uploading the harmonic suppression parameter to an energy center, calculating a demand, generating a region-level feedback strategy, dynamically distributing a feedback power upper limit, synchronizing the harmonic suppression parameter, and obtaining region-level feedback data. And aggregating feedback data, and setting a global optimization target, including cost minimization, feedback maximization and carbon emission reduction. And calculating feedback energy and carbon integral according to a target adjustment algorithm, automatically settling to an operator account, and adjusting the target of the next period. Through an algorithm and an optimization mechanism, the problem of energy waste of a brake resistor in a traditional feedback technology is solved, the feedback efficiency is improved, and energy waste is reduced.

Description

Technical Field

[0001] The present invention relates to the field of data communication technology, and in particular to a method and system for realizing elevator energy feedback data communication. Background Art

[0002] In elevator systems, energy regeneration technology is a key component in improving energy efficiency and reducing operating costs. During braking or deceleration, traditional elevators typically use brake resistors to dissipate regenerative energy as heat, resulting in significant energy waste. With the advancement of power electronics technology, elevator energy regeneration devices have become a research hotspot. Their core goal is to feed regenerative electrical energy back to the grid, achieving energy recycling. However, due to the lack of dynamic phase matching and harmonic suppression technology, traditional elevators face difficulties in real-time synchronization of the feedback current phase with the grid voltage phase, resulting in limited regenerative power. To avoid current surges caused by phase deviation, systems typically adopt conservative regeneration strategies, or even rely entirely on brake resistors to dissipate energy. For example, in lightly loaded elevators or when the elevator frequently starts and stops, regenerative energy cannot be efficiently fed back to the grid, resulting in energy waste rates exceeding 30%.

[0003] Furthermore, existing energy regeneration devices generate significant harmonic currents when injecting current into the grid due to the nonlinear characteristics of their switching devices. These harmonic currents not only degrade grid power quality but can also cause voltage distortion, equipment overheating, and even malfunction of protective devices. For example, a non-optimized space vector pulse width modulation (SVPWM) strategy can result in total harmonic distortion (THD) exceeding 5%, far exceeding grid access standards. Summary of the Invention

[0004] The present invention aims to at least solve the technical problem of energy waste rate in the prior art, and particularly innovatively proposes a method and system for realizing elevator energy feedback data communication.

[0005] In order to achieve the above-mentioned object of the present invention, the present invention provides a method for realizing elevator energy feedback data communication, the method comprising: S1. Collect multimodal operation data, extract fault characteristic data from the multimodal operation data, package and encrypt the fault characteristic data, and obtain an encrypted characteristic data packet; S2. Decrypting the encrypted characteristic data packet to obtain the fault characteristic data, calculating the phase offset between the elevator operating phase and the grid voltage phase using a dynamic phase adjustment algorithm based on the current harmonic characteristics and vibration spectrum peaks in the fault characteristic data, adjusting the phase of the elevator energy feedback current to synchronize with the grid voltage phase according to the phase offset, and generating an energy feedback instruction for the elevator; S3. Uploading the harmonic suppression parameter to a regional energy management center, calculating the harmonic suppression requirement based on the phase offset, and obtaining the harmonic suppression parameter; S4. Receive the energy feedback instructions and harmonic suppression parameters of at least two elevators, generate a regional energy feedback strategy, dynamically allocate a feedback power upper limit for each elevator based on the regional energy feedback strategy, synchronize the harmonic suppression parameters of each elevator in the region, coordinate a space vector pulse width modulation strategy, and obtain regional energy feedback data. S5. Aggregate the regional energy feedback data to generate a global energy optimization goal, wherein the goal includes minimizing grid costs, maximizing regenerative energy feedback, and minimizing carbon emissions; based on the global energy optimization goal, dynamically adjust the phase adjustment step size and harmonic suppression threshold in the dynamic phase matching algorithm to generate a globally optimized phase offset and modulation ratio; and calculate the feedback energy by integration based on the optimized phase offset and modulation ratio; S6. Calculate carbon credits based on the feedback energy and carbon price, automatically settle the carbon credits to the elevator operator's account through a blockchain smart contract, and dynamically adjust the global energy optimization target for the next cycle.

[0006] As an optional embodiment of the present invention, optionally, in step S4, receiving the energy feedback instructions and harmonic suppression parameters of at least two elevators and generating a regional energy feedback strategy includes: S401, verifying the energy feedback instruction and harmonic suppression parameters; S402, using the collected real-time data of the regional power grid, normalizing the harmonic suppression parameters; S403, based on the energy feedback instruction and harmonic suppression parameters, a regional energy feedback optimization model is constructed, with minimization of power deviation, total harmonic distortion and switching loss as the objective function, and a model predictive control framework is adopted to optimize the energy feedback in each control cycle. Solving the regional energy feedback optimization model by internal rolling to obtain a solution result; S404: Generate the regional energy feedback strategy based on the solution result.

[0007] As an optional embodiment of the present invention, optionally, aggregating the regional energy feedback data in step S5 to generate a global energy optimization target includes: S501, performing spatiotemporal alignment and quality verification on the regional energy feedback data uploaded by each regional energy management center; the regional energy feedback data includes energy feedback data, real-time grid status data, and carbon trading market prices; S502. Based on the subsequent regional energy feedback data, combined with the peak and valley characteristics of the power grid load, the carbon price fluctuation curve, and the pre-trained equipment health prediction model, dynamically assign priority weights to the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions; The priority weight expression for dynamically allocating the minimization of grid cost is: in, represents the target weight of the grid cost, represents the natural base, Indicates the grid load sensitivity, Indicates the peak-valley characteristic index of power grid load, represents the carbon price sensitivity, represents the carbon price fluctuation intensity index, Indicates the sensitivity of device health. Indicates the device health indicator; The priority weight expression for dynamically allocating the maximum regenerative energy feedback is: in, Indicates the target weight of regenerative energy feedback; The dynamic allocation of the priority weight expression for minimizing carbon emissions is: in, represents the carbon emission target weight; S503. Based on the priority weights, a global energy optimization objective function is generated through weighted fusion, the global energy optimization target is calculated through the global energy optimization objective function, and the global energy optimization target is decomposed into each regional energy management center according to the regional grid capacity, regional differences in carbon prices and equipment life distribution.

[0008] As an optional embodiment of the present invention, optionally, in step S5, based on the global energy optimization target, dynamically adjusting the phase adjustment step and the harmonic suppression threshold in the dynamic phase matching algorithm to generate a globally optimized phase offset and modulation ratio, and calculating the feedback energy by integration based on the optimized phase offset and modulation ratio includes: S504, dynamically adjusting the phase adjustment step size and harmonic suppression threshold of the dynamic phase matching algorithm based on the priority weight in the global energy optimization objective; S505: Calculate the globally optimized phase offset based on the adjusted phase adjustment step and harmonic suppression threshold, and generate a modulation ratio that matches the harmonic suppression requirement through a space vector pulse width modulation algorithm; S506 , based on the globally optimized phase offset and modulation ratio, combined with real-time data of grid voltage and elevator feedback current, calculate the feedback energy within a single control cycle through an integration algorithm.

[0009] In another aspect, the present invention further provides a system for realizing energy feedback data communication of an elevator, the system comprising the method for realizing energy feedback data communication of an elevator; The system also includes: a multimodal data acquisition and encryption module, a dynamic phase matching and energy feedback control module, a regional energy management module and a global energy optimization module; The multimodal data acquisition and encryption module is used to collect multimodal operation data of the elevator, extract fault feature data and encrypt it to generate an encrypted feature data packet; The dynamic phase matching and energy feedback control module is used to dynamically adjust the parameters in the phase matching algorithm based on the encrypted characteristic data packet and the regional energy feedback data uploaded by the regional energy management module; The regional energy management module is used to receive energy feedback instructions and harmonic suppression parameters from multiple elevators, generate a regional energy feedback strategy, and upload the regional energy feedback data to the global energy optimization module; The global energy optimization module is used to aggregate the regional energy feedback data uploaded by each regional energy management center, and dynamically allocate the priority weights of the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions in combination with the peak and valley characteristics of the grid load, the carbon price fluctuation curve, and the equipment health prediction model. Based on the priority weights, a global energy optimization target is generated, and the global energy optimization target is decomposed into each regional energy management center.

[0010] Beneficial effects of the present invention: The present invention fundamentally solves the problem of energy waste in braking resistors in traditional elevator energy feedback technology through a dynamic phase matching algorithm and a global energy optimization mechanism. Specifically, in step S2, the phase offset between the elevator feedback current and the grid voltage is calculated in real time by a dynamic phase adjustment algorithm using the current harmonic characteristics and the vibration spectrum peak, and the feedback current phase is adjusted synchronously, so that the regenerated energy can be efficiently fed back to the grid rather than dissipated through the braking resistor. Step S5 further dynamically adjusts the step size and harmonic suppression threshold of the phase matching algorithm based on the global energy optimization goal (such as maximizing regenerated energy feedback) to generate a globally optimized phase offset and modulation ratio. This process ensures the precise matching of the feedback power and the grid state through the controller, avoiding the problem of feedback power limitation caused by phase deviation in traditional solutions, improving the feedback efficiency of the elevator regenerated energy, and significantly reducing the dependence on the braking resistor, thereby greatly reducing energy waste.

[0011] The multi-level harmonic suppression strategy also effectively addresses the problem of harmonic interference with the power grid in traditional energy feedback technology. In step S3, the harmonic suppression requirement is calculated based on the phase offset, and the harmonic suppression parameters are generated and uploaded to the regional energy management center. In step S4, within the regional energy feedback strategy, the space vector pulse width modulation (SVPWM) strategy is coordinated through the model predictive control (MPC) framework to dynamically allocate the feedback power upper limit for each elevator and synchronize the harmonic suppression parameters to reduce harmonic generation at the source. In step S5, the global energy optimization objective is combined with the harmonic distortion rate weight coefficient to dynamically adjust the SVPWM modulation ratio to keep the harmonic content of the feedback current below the threshold, thereby reducing the total harmonic distortion (THD) and far below the grid access standard. At the same time, the blockchain carbon credit mechanism is used to incentivize low-carbon operation, achieving a dual improvement in economic benefits and grid quality.

[0012] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which: Figure 1 The present invention is a flow chart of a method for realizing elevator energy feedback data communication. DETAILED DESCRIPTION

[0014] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0015] Example 1 like Figure 1 As shown, a method for realizing elevator energy feedback data communication, the method comprising: S1. Collect multimodal operation data, extract fault characteristic data from the multimodal operation data, package and encrypt the fault characteristic data, and obtain an encrypted characteristic data packet; In this embodiment, multimodal operational data includes three-phase current values ​​and phase information collected by current sensors, the load weight in the elevator car collected by load sensors, the temperatures of key components such as the motor and brake collected by temperature sensors, and vibration signals (acceleration and frequency) collected by vibration sensors during elevator operation. During feature extraction, the three-phase current values ​​and phase information are processed using wavelet transform to extract current harmonic features, the load weight is processed using mean filtering to smooth random fluctuations, temperature data is identified by thresholding to identify abnormally high temperatures, and vibration signals are analyzed using spectrum analysis to determine vibration spectrum peaks. These feature data collectively reflect the elevator's operating status and potential failure modes. These extracted features are then encrypted using an encryption algorithm (AES or RSA) to ensure data security and privacy during transmission.

[0016] S2. Decrypting the encrypted characteristic data packet to obtain the fault characteristic data, calculating the phase offset between the elevator operating phase and the grid voltage phase using a dynamic phase adjustment algorithm based on the current harmonic characteristics and vibration spectrum peaks in the fault characteristic data, adjusting the phase of the elevator energy feedback current to synchronize with the grid voltage phase according to the phase offset, and generating an energy feedback instruction for the elevator; It should be noted in step S2 that the decryption process uses a corresponding decryption algorithm to ensure accurate data restoration. The fault characteristic data obtained after decryption, including current harmonic characteristics and vibration spectrum peaks, are key indicators for determining the elevator's operating status and energy feedback efficiency. Based on this characteristic data, a dynamic phase adjustment algorithm is used to calculate in real time the phase offset between the elevator's operating phase and the grid voltage phase. This algorithm automatically adjusts the phase of the feedback current based on the elevator's real-time operating status and grid voltage fluctuations, synchronizing it with the grid voltage phase to maximize feedback efficiency. Simultaneously, based on the calculated phase offset, an energy feedback command for the elevator is generated. This command is used to control the magnitude and phase of the elevator's feedback current to achieve efficient energy feedback.

[0017] S3. Uploading the harmonic suppression parameter to a regional energy management center, calculating the harmonic suppression requirement based on the phase offset, and obtaining the harmonic suppression parameter; It should be noted that the calculation of harmonic suppression parameters in step S3 is based on a precise assessment of the impact of phase offset on harmonic generation. Specifically, the phase offset can be used to predict the potential harmonic components and amplitudes of the elevator feedback current, thereby calculating the required harmonic suppression parameters. These parameters include but are not limited to filter design parameters and modulation strategy adjustment parameters, and are designed to effectively suppress the generation and propagation of harmonics and ensure that the feedback current quality meets grid requirements.

[0018] S4. Receive the energy feedback instructions and harmonic suppression parameters of at least two elevators, generate a regional energy feedback strategy, dynamically allocate a feedback power upper limit for each elevator based on the regional energy feedback strategy, synchronize the harmonic suppression parameters of each elevator in the region, coordinate a space vector pulse width modulation strategy, and obtain regional energy feedback data. S5. Aggregate the regional energy feedback data to generate a global energy optimization goal, wherein the goal includes minimizing grid costs, maximizing regenerative energy feedback, and minimizing carbon emissions; based on the global energy optimization goal, dynamically adjust the phase adjustment step size and harmonic suppression threshold in the dynamic phase matching algorithm to generate a globally optimized phase offset and modulation ratio; and calculate the feedback energy by integration based on the optimized phase offset and modulation ratio; S6. Calculate carbon credits based on the feedback energy and carbon price, automatically settle the carbon credits to the elevator operator's account through a blockchain smart contract, and dynamically adjust the global energy optimization target for the next cycle.

[0019] The principle of a method for implementing elevator energy feedback data communication in this embodiment is as follows: first, by collecting multimodal data of elevator operation and encrypting it, the security and privacy of the data are guaranteed. Subsequently, the decryption process ensures the accurate restoration of the data. Utilizing a dynamic phase adjustment algorithm, the phase offset is calculated and the phase of the feedback current is adjusted based on the real-time operating status of the elevator and the fluctuation of the grid voltage, achieving synchronization between the feedback current and the grid voltage, thereby improving the energy feedback efficiency. At the same time, the harmonic suppression requirement is calculated based on the phase offset and uploaded to the regional energy management center to provide data for the formulation of harmonic suppression strategies. Through the formulation and implementation of regional energy feedback strategies, the feedback power upper limit of each elevator is dynamically allocated, and the harmonic suppression parameters of each elevator in the region are synchronized, effectively coordinating the space vector pulse width modulation strategy and ensuring the quality of the feedback current. The generation and dynamic adjustment of global energy optimization targets further improves the overall efficiency of energy feedback, minimizing grid costs, maximizing regenerative energy feedback, and minimizing carbon emissions. Finally, carbon credits are calculated based on the feedback energy and carbon price, and automatically settled to the elevator operator's account through blockchain smart contracts. This not only encourages low-carbon operation, but also achieves a dual improvement in economic benefits and grid quality.

[0020] As an optional embodiment of the present invention, optionally, the expression of the dynamic phase adjustment algorithm in step S2 is: in, express The offset that needs to be adjusted for the phase of the elevator energy feedback current at all times, represents the proportional control coefficient; Indicates the current harmonic reference threshold, set by the IEC 61000-3-2 standard; express The effective value of the elevator current harmonics at the moment is obtained from the fault feature data extracted in step S1. represents the vibration suppression weight factor; Indicates the vibration safety threshold, which is set by the elevator manufacturer's design specifications; express The peak value of the elevator vibration spectrum at time t is obtained by the fault feature data extracted in step S1; represents the integral control coefficient, express Effective value of elevator current harmonics at all times.

[0021] As an optional embodiment of the present invention, optionally, the expression for calculating the harmonic suppression requirement in step S3 is: in, express The intensity of harmonic suppression requirements at all times, represents the proportional control coefficient; express The offset amount of the elevator energy feedback current phase that needs to be adjusted at this moment is output by the dynamic phase adjustment algorithm in step S2; represents the integral control coefficient, express The offset that needs to be adjusted for the elevator energy feedback current phase at all times.

[0022] As an optional embodiment of the present invention, optionally, in step S4, receiving the energy feedback instructions and harmonic suppression parameters of at least two elevators and generating a regional energy feedback strategy includes: S401, verifying the energy feedback instruction and harmonic suppression parameters; It should be noted that the verification process in step S401 includes checking the integrity, accuracy, and timeliness of the data to ensure the reliability of subsequent processing. If the data verification fails, an alarm is issued and relevant personnel are prompted to handle it; if the data verification passes, the process proceeds to the next step.

[0023] S402, using the collected real-time data of the regional power grid, normalizing the harmonic suppression parameters; It should be noted that normalization in step S402 converts the harmonic suppression parameters to the same magnitude range to facilitate subsequent analysis and processing. Specifically, based on real-time data from the regional power grid, such as voltage fluctuations and load variations, the harmonic suppression parameters are appropriately adjusted to more accurately reflect the impact of the elevator feedback current on the power grid.

[0024] S403, based on the energy feedback instruction and harmonic suppression parameters, a regional energy feedback optimization model is constructed, with minimization of power deviation, total harmonic distortion and switching loss as the objective function, using a model predictive control (MPC) framework, in each control cycle Solving the regional energy feedback optimization model by internal rolling to obtain a solution result; In step S403, it should be noted that the control cycle The length of is typically determined based on the grid's fluctuation frequency and the elevator's operating status, ensuring the optimization model can promptly respond to changes in the grid and elevators. The solution includes each elevator's upper limit for regenerative power during the current control cycle, the adjusted values ​​for harmonic suppression parameters, and the specific parameters of the space vector pulse width modulation strategy. These parameters guide the elevator's energy regeneration process, achieving efficient regional energy regeneration and optimizing grid quality. By continuously resolving the optimization model, the present invention dynamically adapts to changes in the grid and elevators, ensuring continuous optimization and maximizing the benefits of the energy regeneration process.

[0025] S404: Generate the regional energy feedback strategy based on the solution result.

[0026] It should be noted in step S404 that, in this embodiment, the regional energy regeneration strategy is generated by first rationally allocating the regeneration power to each elevator based on the current operating status of each elevator and the real-time conditions of the power grid. Specifically, the strategy prioritizes ensuring the stability and quality of the power grid, while maximizing the energy regeneration efficiency of the elevators. To achieve this goal, the strategy comprehensively considers factors such as the elevator's fault signature data, current harmonic characteristics, vibration spectrum peaks, and power grid voltage fluctuations and load variations. The optimal regeneration power allocation scheme is determined through calculation (specifically, a multi-objective optimization intelligent allocation algorithm. This algorithm first calculates the possible regeneration power range for each elevator based on the real-time needs of the power grid and the operating status of each elevator. Then, combining the elevator's fault signature data and harmonic suppression requirements, the regeneration power is intelligently allocated to ensure that the energy regeneration efficiency of the elevators is maximized and harmonic pollution is reduced while meeting the power grid's needs. Furthermore, the strategy dynamically adjusts the upper limit of each elevator's regeneration power based on the real-time needs of the power grid and the operating status of the elevators to ensure a smooth regeneration process. Furthermore, the strategy synchronizes the harmonic suppression parameters of each elevator in the area and coordinates the space vector pulse width modulation strategy to reduce harmonic interference from the feedback current on the power grid, further improving the quality of the power grid. In this way, the present invention not only achieves efficient energy feedback from elevators, but also ensures stable and safe operation of the power grid.

[0027] As an optional embodiment of the present invention, optionally, the expression of the objective function in step S403 is: in, Indicates the The upper limit of the feedback power of an elevator, Indicates the first Elevator SVPWM modulation ratio, Indicates the first Elevator switching frequency; Indicates that the power deviation weight coefficient is dynamically adjusted by the global optimization objective of step S5; Indicates the number of elevators in the area, Indicates the The target feedback current amplitude of each elevator, Indicates the regional power grid voltage; represents the harmonic distortion weight coefficient, which is dynamically adjusted by the global optimization objective of step S5; Indicates the regional total harmonic distortion rate; represents the switching loss weight coefficient, which is dynamically adjusted by the global optimization objective of step S5; Indicates the The increase in switching loss of an elevator, Indicates the highest harmonic analysis order, Indicates the Elevator No. Subharmonic current effective value, Indicates the effective value of fundamental current.

[0028] As an optional embodiment of the present invention, optionally, aggregating the regional energy feedback data in step S5 to generate a global energy optimization target includes: S501, performing spatiotemporal alignment and quality verification on the regional energy feedback data uploaded by each regional energy management center; the regional energy feedback data includes energy feedback data, real-time grid status data, and carbon trading market prices; It should be noted in step S501 that spatiotemporal alignment ensures accurate correspondence between data from different regions and time points for subsequent analysis and optimization. Quality verification checks the integrity, accuracy, and consistency of the data to ensure its reliability. If the data verification fails, an alarm is issued and relevant personnel are prompted to address the issue. If the data verification passes, the process proceeds to the next step.

[0029] S502. Based on the subsequent regional energy feedback data, combined with the peak and valley characteristics of the power grid load, the carbon price fluctuation curve, and the pre-trained equipment health prediction model, dynamically assign priority weights to the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions; The priority weight expression for dynamically allocating the minimization of grid cost is: in, represents the target weight of the grid cost, Indicates the natural base; Indicates the sensitivity of the power grid load. The larger the value, the higher the load sensitivity during peak hours. The more significant the improvement; Indicates the peak-valley characteristic index of power grid load; Indicates carbon price sensitivity. The larger the value, the greater the impact of carbon price fluctuations. The stronger the impact; represents the carbon price fluctuation intensity index; Indicates the sensitivity of device health. The larger the value, the more sensitive the device aging is. The more obvious the inhibition; Indicates the device health indicator; The priority weight expression for dynamically allocating the maximum regenerative energy feedback is: in, Indicates the target weight of regenerative energy feedback; The dynamic allocation of the priority weight expression for minimizing carbon emissions is: in, represents the carbon emission target weight; S503. Based on the priority weights, a global energy optimization objective function is generated through weighted fusion, the global energy optimization target is calculated through the global energy optimization objective function, and the global energy optimization target is decomposed into each regional energy management center according to the regional grid capacity, regional differences in carbon prices and equipment life distribution.

[0030] It should be noted in step S503 that the weighted fusion process takes into account the actual operating status of the power grid, price fluctuations in the carbon trading market, and the health status of the equipment, ensuring the rationality and feasibility of the global energy optimization target. Specifically, the weighted fusion algorithm will perform weighted processing on each target according to the priority weight of each target, and then fuse the weighted target values ​​to obtain a comprehensive global energy optimization objective function. This function can fully reflect the requirements of multiple aspects such as the economy, environmental protection, and safety of the power grid. By calculating the global energy optimization target, this embodiment can obtain a quantitative indicator for evaluating the energy utilization efficiency and environmental protection performance of the current power grid. At the same time, the global energy optimization target is decomposed into each regional energy management center according to the regional power grid capacity, regional differences in carbon prices, and equipment life distribution, which can ensure that each region can formulate a practical energy management and optimization plan based on its own actual situation.

[0031] As an optional embodiment of the present invention, optionally, in step S5, based on the global energy optimization target, dynamically adjusting the phase adjustment step and the harmonic suppression threshold in the dynamic phase matching algorithm to generate a globally optimized phase offset and modulation ratio, and calculating the feedback energy by integration based on the optimized phase offset and modulation ratio includes: S504, dynamically adjusting the phase adjustment step size and harmonic suppression threshold of the dynamic phase matching algorithm based on the priority weight in the global energy optimization objective; It should be noted in step S504 that the adjustment of the phase adjustment step is mainly based on the peak and valley characteristics of the power grid load and the fluctuation of the carbon price. When the power grid is in the peak load period or the carbon price is high, in order to maximize the feedback of regenerative energy and reduce carbon emissions, the system will appropriately increase the phase adjustment step to speed up the energy feedback process and improve the feedback efficiency. On the contrary, during the low load period of the power grid or when the carbon price is low, the system will appropriately reduce the phase adjustment step to balance the stability of the power grid and the feedback efficiency. At the same time, the adjustment of the harmonic suppression threshold is mainly based on the harmonic pollution level of the power grid and the health status of the equipment. When the harmonic pollution of the power grid is heavy or the health status of the equipment is low, the system will increase the harmonic suppression threshold to reduce the harmonic interference of the feedback current on the power grid and protect the safe operation of the equipment. On the contrary, the harmonic suppression threshold will be appropriately lowered to improve the feedback efficiency.

[0032] S505: Calculate the globally optimized phase offset based on the adjusted phase adjustment step and harmonic suppression threshold, and generate a modulation ratio that matches the harmonic suppression requirement through a space vector pulse width modulation algorithm; It should be noted in step S505 that the calculation of the globally optimized phase offset takes into account multiple factors, including the real-time state of the power grid, the operating characteristics of the elevator, and price fluctuations in the carbon trading market, ensuring the accuracy and rationality of the phase offset. The space vector pulse width modulation algorithm can generate a modulation ratio that matches the harmonic suppression requirements, thereby further reducing the harmonic interference of the feedback current on the power grid and improving feedback efficiency. Specifically, the algorithm accurately calculates the phase offset of each elevator based on the adjusted phase adjustment step size and harmonic suppression threshold. Using space vector pulse width modulation technology, the modulation ratio of each elevator is dynamically adjusted to ensure that the feedback current matches the harmonic suppression requirements of the power grid. In this way, not only can efficient elevator energy feedback be achieved, but the stable and safe operation of the power grid can also be ensured, while also reducing carbon emissions and improving energy efficiency.

[0033] S506 , based on the globally optimized phase offset and modulation ratio, combined with real-time data of grid voltage and elevator feedback current, calculate the feedback energy within a single control cycle through an integration algorithm.

[0034] It should be noted in step S506 that the integration algorithm should be selected to accurately reflect the energy exchange between the feedback current and the grid voltage, thereby obtaining a precise feedback energy value. By continuously calculating and accumulating the feedback energy within a single control cycle, the total feedback energy during the entire elevator operation can be obtained. Furthermore, by continuously monitoring and adjusting the feedback energy calculation process, the present invention can achieve real-time control and optimization of the elevator energy feedback process, ensuring the efficiency, stability, and reliability of the feedback process.

[0035] As an optional embodiment of the present invention, optionally, the expression for calculating the globally optimized phase offset in step S505 is: in, express Phase offset after global optimization at the moment; Indicates the proportional coefficient of the PID controller (needs to be adjusted according to the grid impedance characteristics); express The difference between the grid voltage phase and the elevator feedback current phase at that moment; Indicates the integral coefficient of the PID controller; Indicates at time The difference between the grid voltage phase and the elevator feedback current phase; represents the differential coefficient of the PID controller, express The grid voltage phase at time express The elevator feedback current phase at each moment, Indicates the phase difference ratio.

[0036] As an optional embodiment of the present invention, optionally, in step S506, the expression for calculating the feedback energy within a single control cycle by the integration algorithm is: in, Indicates the accumulated feedback energy within a single control cycle, Indicates the end time of the control cycle, Indicates the start time of the control cycle, express The instantaneous value of the grid voltage at time , express The instantaneous value of the elevator feedback current at the moment; Indicates the power factor and quantifies the effect of phase shift on the feedback power; express The global optimized phase offset at time , Represents the SVPWM modulation ratio after global optimization.

[0037] Example 2 A system for realizing energy feedback data communication of an elevator, the system comprising the method for realizing energy feedback data communication of an elevator; The system also includes: a multimodal data acquisition and encryption module, a dynamic phase matching and energy feedback control module, a regional energy management module and a global energy optimization module; The multimodal data acquisition and encryption module is used to collect multimodal operation data of the elevator, extract fault feature data and encrypt it to generate an encrypted feature data packet; The dynamic phase matching and energy feedback control module is used to dynamically adjust the parameters in the phase matching algorithm based on the encrypted characteristic data packet and the regional energy feedback data uploaded by the regional energy management module; The regional energy management module is used to receive energy feedback instructions and harmonic suppression parameters from multiple elevators, generate a regional energy feedback strategy, and upload the regional energy feedback data to the global energy optimization module; The global energy optimization module is used to aggregate the regional energy feedback data uploaded by each regional energy management center, and dynamically allocate the priority weights of the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions in combination with the peak and valley characteristics of the grid load, the carbon price fluctuation curve, and the equipment health prediction model. Based on the priority weights, a global energy optimization target is generated, and the global energy optimization target is decomposed into each regional energy management center.

[0038] The system for realizing elevator energy feedback data communication in this embodiment is used to execute the method for realizing elevator energy feedback data communication in embodiment 1; The principle behind the elevator energy regeneration data communication system is that elevators generate a large amount of regenerative energy during operation. If this energy is not utilized, it not only wastes energy but also potentially impacts the power grid. This system utilizes a multimodal data acquisition and encryption module to collect real-time multimodal data on elevator operation, including key parameters such as incremental switching loss, the RMS values ​​of various harmonic currents, and the RMS value of the fundamental current. This data is encrypted and transmitted to the dynamic phase matching and energy regeneration control module.

[0039] The dynamic phase matching and energy feedback control module is the core of this system. It dynamically adjusts the phase adjustment step size and harmonic suppression threshold in the phase matching algorithm based on the encrypted signature data packets it receives and the regional energy feedback data uploaded by the regional energy management module. By accurately calculating the globally optimized phase offset and combining it with the space vector pulse width modulation algorithm to generate a modulation ratio that matches the harmonic suppression requirements, efficient elevator energy feedback is achieved.

[0040] The regional energy management module is responsible for receiving energy feedback instructions and harmonic suppression parameters from multiple elevators, generating regional energy feedback strategies based on these parameters, and uploading relevant data to the global energy optimization module. The global energy optimization module further aggregates data from each region and, combining the real-time status of the power grid, price fluctuations in the carbon trading market, and the health of the equipment, dynamically assigns priority weights to the three goals of minimizing grid costs, maximizing regenerative energy feedback, and minimizing carbon emissions. Through weighted fusion, a global energy optimization objective function is generated and global energy optimization goals are calculated. Ultimately, these goals are decomposed into each regional energy management center to guide energy management and optimization work in each region.

[0041] In summary, this system achieves efficient elevator energy feedback and stable power grid operation through precise data acquisition, encrypted transmission, dynamic phase matching and energy feedback control, and global energy optimization, while reducing carbon emissions and improving energy utilization efficiency.

[0042] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. A method for realizing elevator energy feedback data communication, characterized in that: The method comprises: S1. Collect multimodal operation data, extract fault characteristic data from the multimodal operation data, package and encrypt the fault characteristic data, and obtain an encrypted characteristic data packet; S2. Decrypting the encrypted characteristic data packet to obtain the fault characteristic data, calculating the phase offset between the elevator operating phase and the grid voltage phase using a dynamic phase adjustment algorithm based on the current harmonic characteristics and vibration spectrum peaks in the fault characteristic data, adjusting the phase of the elevator energy feedback current to synchronize with the grid voltage phase according to the phase offset, and generating an energy feedback instruction for the elevator; S3. Uploading the harmonic suppression parameter to a regional energy management center, calculating the harmonic suppression requirement based on the phase offset, and obtaining the harmonic suppression parameter; S4. Receive the energy feedback instructions and harmonic suppression parameters of at least two elevators, generate a regional energy feedback strategy, dynamically allocate a feedback power upper limit for each elevator based on the regional energy feedback strategy, synchronize the harmonic suppression parameters of each elevator in the region, coordinate a space vector pulse width modulation strategy, and obtain regional energy feedback data. S5. Aggregate the regional energy feedback data to generate a global energy optimization goal, wherein the goal includes minimizing grid costs, maximizing regenerative energy feedback, and minimizing carbon emissions; based on the global energy optimization goal, dynamically adjust the phase adjustment step size and harmonic suppression threshold in the dynamic phase matching algorithm to generate a globally optimized phase offset and modulation ratio; and calculate the feedback energy by integration based on the optimized phase offset and modulation ratio; S6. Calculate carbon credits based on the feedback energy and carbon price, automatically settle the carbon credits to the elevator operator's account through a blockchain smart contract, and dynamically adjust the global energy optimization target for the next cycle.

2. A method for realizing elevator energy feedback data communication according to claim 1, characterized in that: The expression of the dynamic phase adjustment algorithm in step S2 is: in, express The offset that needs to be adjusted for the elevator energy feedback current phase at all times, represents the proportional control coefficient, Indicates the current harmonic reference threshold, express The effective value of the elevator current harmonics at this moment, represents the vibration suppression weight factor, represents the vibration safety threshold, express The peak value of the elevator vibration spectrum at time represents the integral control coefficient, express Effective value of elevator current harmonics at all times.

3. A method for realizing elevator energy feedback data communication according to claim 1, characterized in that: The expression for calculating the harmonic suppression requirement in step S3 is: in, express The intensity of harmonic suppression requirements at all times, represents the proportional control coefficient, express The offset that needs to be adjusted for the elevator energy feedback current phase at all times, represents the integral control coefficient, express The offset that needs to be adjusted for the elevator energy feedback current phase at all times.

4. A method for realizing elevator energy feedback data communication according to claim 1, characterized in that: In step S4, the energy feedback instructions and harmonic suppression parameters of at least two elevators are received, and the regional energy feedback strategy is generated, including: S401, verifying the energy feedback instruction and harmonic suppression parameters; S402, using the collected real-time data of the regional power grid, normalizing the harmonic suppression parameters; S403, based on the energy feedback instruction and harmonic suppression parameters, a regional energy feedback optimization model is constructed, with minimization of power deviation, total harmonic distortion and switching loss as the objective function, using a model predictive control (MPC) framework, in each control cycle Solving the regional energy feedback optimization model by internal rolling to obtain a solution result; S404: Generate the regional energy feedback strategy based on the solution result.

5. A method for realizing elevator energy feedback data communication according to claim 4, characterized in that: In step S403, the objective function is expressed as: in, Indicates the The upper limit of the feedback power of an elevator, Indicates the first Elevator SVPWM modulation ratio, Indicates the first Elevator switching frequency, represents the power deviation weight coefficient, Indicates the number of elevators in the area, Indicates the The target feedback current amplitude of each elevator, Indicates the regional grid voltage, represents the harmonic distortion weight coefficient, represents the regional total harmonic distortion rate, represents the switching loss weight coefficient, Indicates the The increase in switching loss of an elevator, Indicates the highest harmonic analysis order, Indicates the Elevator No. Subharmonic current effective value, Indicates the effective value of fundamental current.

6. A method for realizing elevator energy feedback data communication according to claim 1, characterized in that: Aggregating the regional energy feedback data in step S5 to generate a global energy optimization target includes: S501, performing spatiotemporal alignment and quality verification on the regional energy feedback data uploaded by each regional energy management center; the regional energy feedback data includes energy feedback data, real-time grid status data, and carbon trading market prices; S502. Based on the subsequent regional energy feedback data, combined with the peak and valley characteristics of the power grid load, the carbon price fluctuation curve, and the pre-trained equipment health prediction model, dynamically assign priority weights to the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions; The priority weight expression for dynamically allocating the minimization of grid cost is: in, represents the target weight of the grid cost, represents the natural base, Indicates the grid load sensitivity, Indicates the peak-valley characteristic index of power grid load, represents the carbon price sensitivity, represents the carbon price fluctuation intensity index, Indicates the sensitivity of device health. Indicates the device health indicator; The priority weight expression for dynamically allocating the maximum regenerative energy feedback is: in, Indicates the target weight of regenerative energy feedback; The dynamic allocation of the priority weight expression for minimizing carbon emissions is: in, represents the carbon emission target weight; S503. Based on the priority weights, a global energy optimization objective function is generated through weighted fusion, the global energy optimization target is calculated through the global energy optimization objective function, and the global energy optimization target is decomposed into each regional energy management center according to the regional grid capacity, regional differences in carbon prices and equipment life distribution.

7. A method for realizing elevator energy feedback data communication according to claim 1 or 6, characterized in that: In step S5, based on the global energy optimization target, the phase adjustment step size and harmonic suppression threshold in the dynamic phase matching algorithm are dynamically adjusted to generate a globally optimized phase offset and modulation ratio. The feedback energy is calculated by integration based on the optimized phase offset and modulation ratio, including: S504, dynamically adjusting the phase adjustment step size and harmonic suppression threshold of the dynamic phase matching algorithm based on the priority weight in the global energy optimization objective; S505: Calculate the globally optimized phase offset based on the adjusted phase adjustment step and harmonic suppression threshold, and generate a modulation ratio that matches the harmonic suppression requirement through a space vector pulse width modulation algorithm; S506 , based on the globally optimized phase offset and modulation ratio, combined with real-time data of grid voltage and elevator feedback current, calculate the feedback energy within a single control cycle through an integration algorithm.

8. A method for realizing elevator energy feedback data communication according to claim 7, characterized in that: The expression for calculating the phase offset after global optimization in step S505 is: in, express The phase offset after global optimization at the moment, represents the controller proportional coefficient, express The difference between the grid voltage phase and the elevator feedback current phase at that moment, represents the controller integral coefficient, Indicates at time The difference between the grid voltage phase and the elevator feedback current phase, represents the controller differential coefficient, express The grid voltage phase at time express The elevator feedback current phase at each moment, Indicates the phase difference ratio.

9. A method for realizing elevator energy feedback data communication according to claim 7, characterized in that: In step S506, the expression for calculating the feedback energy in a single control cycle by the integration algorithm is: in, Indicates the accumulated feedback energy within a single control cycle, Indicates the end time of the control cycle, Indicates the start time of the control cycle, express The instantaneous value of the grid voltage at time , express The instantaneous value of the elevator feedback current at the moment, Indicates the power factor, express The global optimized phase offset at time , Represents the SVPWM modulation ratio after global optimization.

10. A data communication system for realizing energy feedback of an elevator, characterized in that: The system includes a method for realizing elevator energy feedback data communication according to any one of claims 1 to 9; The system also includes: a multimodal data acquisition and encryption module, a dynamic phase matching and energy feedback control module, a regional energy management module and a global energy optimization module; The multimodal data acquisition and encryption module is used to collect multimodal operation data of the elevator, extract fault feature data and encrypt it to generate an encrypted feature data packet; The dynamic phase matching and energy feedback control module is used to dynamically adjust the parameters in the phase matching algorithm based on the encrypted characteristic data packet and the regional energy feedback data uploaded by the regional energy management module; The regional energy management module is used to receive energy feedback instructions and harmonic suppression parameters from multiple elevators, generate a regional energy feedback strategy, and upload the regional energy feedback data to the global energy optimization module; The global energy optimization module is used to aggregate the regional energy feedback data uploaded by each regional energy management center, and dynamically allocate the priority weights of the three goals of minimizing grid costs, maximizing renewable energy feedback, and minimizing carbon emissions in combination with the peak and valley characteristics of the grid load, the carbon price fluctuation curve, and the equipment health prediction model. Based on the priority weights, a global energy optimization target is generated, and the global energy optimization target is decomposed into each regional energy management center.

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