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CN-122022697-A - Energy consumption monitoring and optimizing system based on digital twin in intelligent storage

CN122022697ACN 122022697 ACN122022697 ACN 122022697ACN-122022697-A

Abstract

The invention provides an energy consumption monitoring optimization system based on digital twin in intelligent storage, which relates to the technical field of intelligent management and control and comprises an acquisition module, a construction module and a control module, wherein the acquisition module is used for acquiring multi-source high-frequency dynamic data in real time, carrying out real-time mapping and dynamic synchronization on a static three-dimensional visual model to obtain a dynamic digital twin body, and the construction module is used for constructing a dynamic parameterized space manifold according to a transient current harmonic acquisition point, a real-time path tracking and energy consumption mapping acquisition point and a temperature and humidity field dynamic response sensing acquisition point and respective data updating frequency, and mapping multi-source high-frequency dynamic data on discrete nodes of the space manifold according to a time stamp and space coordinates to obtain a synchronous running state flow. The invention reduces comprehensive energy consumption and improves the energy efficiency management and control refinement level.

Inventors

  • YANG ZHAOPENG
  • LIN WENZHOU

Assignees

  • 厦门唯创盈智能科技有限公司

Dates

Publication Date
20260512
Application Date
20260410

Claims (10)

  1. 1. Energy consumption monitoring optimizing system based on digital twin in intelligent storage, its characterized in that includes: The acquisition module is used for acquiring multi-source high-frequency dynamic data in real time, and carrying out real-time mapping and dynamic synchronization on the static three-dimensional visual model to obtain a dynamic digital twin body; The construction module is used for constructing a dynamic parameterized space manifold based on a dynamic digital twin body according to the distribution positions of transient current harmonic acquisition points, real-time path tracking and energy consumption mapping acquisition points and temperature and humidity field dynamic response sensing acquisition points in space and respective data updating frequencies, and mapping multi-source high-frequency dynamic data onto discrete nodes of the space manifold according to time stamps and space coordinates to obtain a synchronous running state stream; the computing module is used for executing constant parameter transformation on the dynamic parameterized space characterization object based on the synchronous running state flow to obtain a transformed projection domain, extracting boundary contours corresponding to all the acquisition points on the transformed projection domain, and sequentially biasing the boundary contours along the normal direction to obtain a plurality of layers of nested buffer boundaries; the processing module is used for executing dynamic self-adaptive regulation and control processing according to the previewing result and the pre-regulation parameter set to obtain equipment operation feedback data after the dynamic self-adaptive regulation and control processing; And the iteration module is used for executing closed-loop optimization iteration processing based on the equipment operation feedback data after the dynamic self-adaptive regulation and control processing to form continuous optimization of the working condition prediction and pre-control parameters.
  2. 2. The energy consumption monitoring and optimizing system based on digital twinning in intelligent warehouse of claim 1, wherein the system is characterized by acquiring multi-source high-frequency dynamic data in real time, mapping and dynamically synchronizing a static three-dimensional visual model in real time to obtain a dynamic digital twinning body, and capturing an original transaction data stream in real time, and comprises: A transient current harmonic wave acquisition point is deployed at a winding end of a driving motor of the high-speed stacker, a real-time path tracking and energy consumption mapping acquisition point is deployed at a navigation positioning position of unmanned carrying equipment, a temperature and humidity field dynamic response sensing acquisition point is deployed at a return air inlet side of an evaporator of a cold chain reservoir area, sampling frequency and a data reporting protocol of each acquisition point are configured, and a real-time data transmission link between the digital twin platform is established; Based on a real-time data transmission link, each acquisition point respectively captures a three-phase current time domain waveform of a stacker driving motor, extracts a harmonic distortion characteristic value, real-time position coordinates of unmanned carrying equipment, unit mileage energy consumption and temperature and humidity change rate of an air return port, and forms a multi-source high-frequency dynamic data stream; Adding a time stamp and a space coordinate label to the multi-source high-frequency dynamic data stream, and mapping the data stream with the aligned time stamp to a corresponding component node of the static three-dimensional visual model according to the space coordinate according to the preset anchor point position of each acquisition point in the static three-dimensional visual model so as to obtain a mapping result; Based on the mapping result, carrying out follow-up refreshing on the geometric structures, space pose states and operation attribute parameters of the stacker, the unmanned carrying equipment and the cold chain fan in the static three-dimensional visual model, so that the representation content of the static three-dimensional visual model is kept synchronous with the physical entity, and a dynamic digital twin body is formed.
  3. 3. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 2, wherein based on dynamic digital twinning, the dynamic parameterized spatial manifold is constructed according to the distribution position of transient current harmonic wave acquisition points, real-time path tracking and energy consumption mapping acquisition points and temperature-humidity field dynamic response sensing acquisition points in space and respective data updating frequency, comprising: Extracting space coordinate values of all the acquisition points from the dynamic digital twin body, and respectively associating a harmonic distortion rate characteristic value sequence, a position coordinate, a unit mileage energy consumption sequence and a temperature and humidity change rate sequence according to the data stream type corresponding to each acquisition point to form a space-time attribute vector of each acquisition point; the space coordinate value of each acquisition point is taken as a node position, the data updating frequency is taken as a time axis sampling interval, a discrete node set is established, a continuous attribute field covering the storage space is constructed based on the space-time attribute vector associated with each node, and an isoparametric curved surface of the continuous attribute field is defined as a base curved surface of a dynamic parameterized space manifold; On a substrate curved surface, according to the harmonic distortion gradient change direction of a transient current harmonic acquisition point, the motion track density degree of the real-time path tracking and energy consumption mapping acquisition point and the temperature-humidity field equipotential line distribution of a temperature-humidity field dynamic response sensing acquisition point, applying non-uniform scaling factors along three main directions of the substrate curved surface to obtain a dynamic parameterized space manifold; Discretizing the dynamic parameterized space manifold into a grid topological structure, and reserving corresponding space-time attribute vectors for each vertex to complete the construction of the dynamic parameterized space manifold.
  4. 4. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 3, wherein mapping the multi-source high-frequency dynamic data onto discrete nodes of a space manifold according to time stamps and space coordinates to obtain a synchronous running state stream comprises: three-dimensional space coordinates of each discrete node are extracted from a grid topological structure, space membership relations among nodes, transient current harmonic acquisition points, real-time path tracking, energy consumption mapping acquisition points and temperature and humidity field dynamic response sensing acquisition points are established according to space-time attribute vector types of each node, and the dominant acquisition point attribution of each discrete node in space is determined; Based on three paths of parallel multi-source high-frequency dynamic data streams, carrying out sliding window alignment processing on time axes on each path of data stream by taking the set data updating frequency of each acquisition point as a reference to obtain a synchronous data frame sequence with a unified time reference; Aiming at each synchronous data frame, distributing the harmonic distortion characteristic value, the position coordinate, the unit mileage energy consumption and the temperature and humidity change rate corresponding to each acquisition point to each discrete node in the belonging space area according to the determined space membership between the node and the acquisition point, so that each discrete node obtains a fusion attribute value matched with the space position; fusing the assigned discrete node fusion attribute values with the reserved space-time attribute vectors to obtain real-time state vectors of all the discrete nodes; and (3) carrying out time sequence arrangement on the real-time state vectors of all the discrete nodes according to the obtained synchronous data frame sequence, and packaging the synchronous data frame sequence into a synchronous running state stream capable of being updated iteratively.
  5. 5. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 4, wherein based on synchronous running state flow, performing iso-parametric transformation on dynamic parameterized space characterization object to obtain transformed projection domain, extracting boundary contour corresponding to each acquisition point on the transformed projection domain, and obtaining multi-layer nested buffer boundary by successive bias along normal direction, comprising: Extracting a grid topological structure of a dynamic parameterized space representation body and a real-time state vector on each discrete node from a synchronous running state stream, and constructing a mapping relation from a three-dimensional physical space to a three-dimensional attribute space by using coordinates of each node and the real-time state vector; Applying equal parameter transformation to the mapping relation, mapping the dynamic parameterized space characterization object to a parameterized projection domain in a three-dimensional attribute space, and forming one-to-one corresponding parameter coordinates between the space position and the attribute field quantity to complete parameterized dimension reduction expression; In a parameterized projection domain, taking parameter coordinates corresponding to all the acquisition points as a center, setting a threshold according to harmonic distortion characteristic values, unit mileage energy consumption peak values and temperature and humidity change rate extremum captured by all the acquisition points, and extracting an contour line as an initial boundary contour; Reversely mapping the initial boundary contour back to a three-dimensional physical space to obtain corresponding three-dimensional boundary contour lines, and discretizing each contour line to obtain a polygonal boundary formed by ordered point sequences; And calculating the normal direction of each side section aiming at each polygon boundary, sequentially obtaining an expansion boundary outwards along the normal direction with a preset offset step length, and numbering the original boundary and the expansion boundary according to the offset distance to obtain a multi-layer nested buffer boundary sequence.
  6. 6. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 5, wherein the space characterization object is divided into a core disturbance area, a transition influence area and a peripheral stable area according to each layer buffer boundary, and numerical simulation of transient energy consumption surge trend is performed on each area respectively to obtain a pre-modeling result of an energy consumption surge abnormal working condition and a corresponding pre-control parameter set, and the system comprises: Extracting an innermost boundary from a multi-layer buffer boundary sequence to serve as a core disturbance boundary, and marking an area inside the boundary as a core disturbance area; extracting an intermediate layer boundary as a transition influence boundary, and marking a region between a core disturbance boundary and the transition influence boundary as a transition influence region; aiming at the core disturbance area, extracting real-time state vectors of discrete nodes in the area, and simulating instantaneous impact effects of stacker start-stop, equipment path intersection and fan load fluctuation on local energy consumption to obtain energy consumption surge peak value and duration previewing results; For the transition influence area, extracting state vectors of discrete nodes in the area, and simulating attenuation rules and delay response characteristics of energy consumption impact outwards transmitted along grid topology to obtain energy consumption sweep range and lag time previewing results; aiming at the peripheral stable region, extracting steady-state operation parameters of discrete nodes in the region, comparing a simulation result of a core disturbance region and a transition influence region with a base line, and identifying abnormal points exceeding a threshold value to obtain an abnormal overflow previewing result; and (3) combining the previewing results of all the areas, solving a stacker start-stop frequency optimization value, an unmanned carrying equipment path energy consumption weight adjustment value and a cold chain fan rotating speed pre-regulation value, and obtaining a pre-regulation parameter set.
  7. 7. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 6, wherein the executing the dynamic adaptive regulation and control processing according to the previewing result and the preset regulation and control parameter set to obtain the equipment operation feedback data after the dynamic adaptive regulation and control processing comprises: Analyzing a stacker start-stop frequency optimization value, an unmanned carrying equipment path energy consumption weight adjustment value and a cold chain fan rotating speed pre-regulation value from the pre-regulation parameter set, and respectively packaging the optimized value, the unmanned carrying equipment path energy consumption weight adjustment value and the cold chain fan rotating speed pre-regulation value into regulation instruction frames for a stacker driving controller, an unmanned carrying equipment navigation scheduler and a cold chain fan variable frequency driver; the stacker start-stop frequency optimization value is sent to a high-speed stacker driving controller, the stacker start-stop time sequence and an acceleration-deceleration curve are dynamically corrected, and harmonic current impact and mechanical energy consumption are reduced; transmitting the path energy consumption weight adjustment value of the unmanned carrying equipment to the unmanned carrying equipment navigation scheduler, re-planning the traveling path and the intersection traffic priority, avoiding the bundling congestion and the idle detour, and reducing the path energy consumption density; The method comprises the steps of sending a pre-regulation value of the rotation speed of the cold chain fan to a variable frequency drive of the cold chain fan, and regulating the rotation speed and the start-stop period of the evaporator fan by feedforward so as to avoid the triggering of full-load redundant operation of the refrigerating unit due to tiny temperature and humidity fluctuation; And acquiring an actual current harmonic sequence executed by a stacker driving controller, an actual unit mileage energy consumption sequence executed by an unmanned carrying equipment navigation scheduler and an actual temperature and humidity fluctuation sequence executed by a cold chain fan variable frequency driver, and performing deviation calculation on acquired data and corresponding original data streams to obtain equipment operation feedback data.
  8. 8. The energy consumption monitoring and optimizing system based on digital twinning in intelligent storage according to claim 7, wherein the performing closed-loop optimization iterative processing based on the equipment operation feedback data after the dynamic adaptive regulation and control processing to form continuous optimization of the working condition prediction and pre-control parameters comprises: Extracting a harmonic suppression deviation sequence between an actual current harmonic sequence and an original harmonic distortion rate of the stacker, a path energy consumption deviation sequence between the actual unit mileage energy consumption of the unmanned carrying equipment and the original unit mileage energy consumption, and a temperature control response deviation sequence between the actual temperature and humidity fluctuation of the cold chain fan and the original temperature and humidity change rate from equipment operation feedback data, aligning the three types of deviation sequences according to time stamps, and constructing a closed loop deviation vector set; Reversely mapping the closed loop deviation vector set into a grid topological structure of the dynamic parameterized space manifold, and correcting non-uniform scaling factors applied along three main directions of a substrate curved surface by taking the deviation vector amplitude as a weight coefficient to obtain an updated dynamic parameterized space manifold; According to the updated dynamic parameterized space manifold, recalculating a threshold value set value of an initial boundary contour, and adjusting an offset step length gradually offset along a normal direction by taking the statistical characteristic of a closed loop offset vector set as an offset; Substituting the corrected non-uniform scaling factor, the adjusted threshold value set value and the updated offset step length into working condition prediction and abnormal pre-modeling processing to enable the pre-modeling result and the pre-control parameter set of the next iteration to be adaptively calibrated based on actual regulation feedback.
  9. 9. A computing device, comprising: one or more processors; storage means for storing one or more programs that when executed by the one or more processors cause the one or more processors to perform the system of any of claims 1-8.
  10. 10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a program which, when executed by a processor, performs the system according to any of claims 1 to 8.

Description

Energy consumption monitoring and optimizing system based on digital twin in intelligent storage Technical Field The invention relates to the technical field of intelligent management and control, in particular to an energy consumption monitoring and optimizing system based on digital twinning in intelligent storage. Background Along with the upgrading of intelligent storage to automation, intellectualization and large scale, the energy consumption duty ratio of core equipment such as a stacker, unmanned carrying equipment and a cold chain refrigerating system is improved year by year, and energy consumption management and control become the key for reducing storage operation cost and realizing green low-carbon operation, and most intelligent storage currently adopts a traditional energy consumption monitoring mode. For example, a large-scale cold chain intelligent warehouse is characterized in that a single type of energy consumption acquisition measuring point is deployed at a stacker driving motor and a cold chain evaporator fan, and energy consumption monitoring is realized by regularly acquiring current and temperature and humidity data, but the technical defects are that in actual operation of the warehouse, the energy consumption of unit mileage is greatly increased due to transient current harmonic impact generated by frequent start and stop of the stacker and the congestion of an unmanned carrying equipment path, and a traditional monitoring system acquires discrete single-point data, so that a warehouse universe energy consumption time-consuming and air-consuming correlation mode is difficult to construct, the energy consumption is serious, the management and control precision is low, and the operation requirements of intelligent warehouse refinement and energy conservation are difficult to meet. Disclosure of Invention The invention provides an energy consumption monitoring and optimizing system based on digital twinning in intelligent storage, which reduces comprehensive energy consumption and improves energy efficiency management and control refinement level. In order to solve the technical problems, the technical scheme of the invention is as follows: in a first aspect, a digital twinning-based energy consumption monitoring optimization system in smart warehousing includes: The acquisition module is used for acquiring multi-source high-frequency dynamic data in real time, and carrying out real-time mapping and dynamic synchronization on the static three-dimensional visual model to obtain a dynamic digital twin body; The construction module is used for constructing a dynamic parameterized space manifold based on a dynamic digital twin body according to the distribution positions of transient current harmonic acquisition points, real-time path tracking and energy consumption mapping acquisition points and temperature and humidity field dynamic response sensing acquisition points in space and respective data updating frequencies, and mapping multi-source high-frequency dynamic data onto discrete nodes of the space manifold according to time stamps and space coordinates to obtain a synchronous running state stream; the computing module is used for executing constant parameter transformation on the dynamic parameterized space characterization object based on the synchronous running state flow to obtain a transformed projection domain, extracting boundary contours corresponding to all the acquisition points on the transformed projection domain, and sequentially biasing the boundary contours along the normal direction to obtain a plurality of layers of nested buffer boundaries; the processing module is used for executing dynamic self-adaptive regulation and control processing according to the previewing result and the pre-regulation parameter set to obtain equipment operation feedback data after the dynamic self-adaptive regulation and control processing; And the iteration module is used for executing closed-loop optimization iteration processing based on the equipment operation feedback data after the dynamic self-adaptive regulation and control processing to form continuous optimization of the working condition prediction and pre-control parameters. Further, the method for obtaining the multi-source high-frequency dynamic data in real time, mapping and dynamically synchronizing the static three-dimensional visual model in real time to obtain a dynamic digital twin body, and capturing the original transaction data stream in real time comprises the following steps: A transient current harmonic wave acquisition point is deployed at a winding end of a driving motor of the high-speed stacker, a real-time path tracking and energy consumption mapping acquisition point is deployed at a navigation positioning position of unmanned carrying equipment, a temperature and humidity field dynamic response sensing acquisition point is deployed at a return air inlet side of an evaporator of a cold chain reservoir ar