Intelligent electromechanical installation energy-saving optimization system in construction stage

Abstract

The invention, which relates to the technical field of energy-saving optimization, discloses a construction-stage intelligent electromechanical installation energy-saving optimization system comprising a data statistics module, an equipment operation optimization module, an electric power resource configuration module and an interactive storage module. The data acquisition module is used for acquiring and counting data of a construction plan, construction equipment and a construction area transformer; the equipment operation optimization module comprises an equipment feature unit and an equipment scheduling unit, and is used for counting to obtain a single equipment time sequence feature set, predicting to obtain a single equipment operation probability sequence, calculating to obtain a construction equipment load prediction sequence and generating a peak shifting pause strategy; the power resource configuration module is used for predicting the overall load of a construction area to obtain a regional power prediction total load, and calculating according to the regional load safety capacity and a regional total load prediction sequence to obtain an optimal transformer commissioning and using plan table; and the interactive storage module is used for providing a visual interface for a user, storing all system data and generating an electromechanical installation energy-saving optimization log.

Description

Technical Field

[0001] The present invention relates to the technical field of energy conservation in construction, and in particular to an intelligent electromechanical installation energy conservation optimization system during the construction phase. Background Art

[0002] In recent years, the construction industry has entered a phase of transformation and upgrading, with a key focus on shifting from extensive, energy-intensive construction to energy-efficient, optimized construction. In large buildings, the installation of intelligent electromechanical systems (EMS), such as smart air conditioning and ventilation systems, networked elevator systems, power distribution management systems, and water supply and drainage systems, is becoming increasingly prevalent. However, due to cost constraints, detailed energy consumption monitoring was previously difficult to implement during construction. Thanks to the development of big data and Internet of Things technologies, leveraging the multi-sensor capabilities of intelligent EMS, the implementation of wireless sensor communication and energy monitoring technologies at construction sites has been significantly simplified, providing strong support for refined energy management. Energy savings are also gradually outweighing the costs. Therefore, combining new equipment and advanced processes to optimize energy consumption during the construction phase of intelligent EMS installation is a promising research direction.

[0003] Currently, a Chinese invention patent application with application number CN202210347790.5 discloses an energy-saving control system for the installation of electromechanical equipment. The application includes: a drive motor fixedly mounted on a fixed bracket, a center platform below the fixed bracket, and a lifting mechanism on the center platform; an anti-sway assembly, the anti-sway assembly being mounted on the center platform, and a connecting plate movably embedded in the bottom surface of the fixed bracket. The invention hoists the pipe to a certain height, then drives the movable rack to move, driving the rotating gears on both sides to rotate, thereby locking the pipe from both sides. As the center platform drives the pipe to rotate and adjust its direction, the pipe can be effectively locked in place, avoiding the problem of large-scale shaking during the adjustment process, thereby improving safety. At the same time, when the pipe is lowered into position, the floating rod is driven to closely contact the surface of the pipe, preventing the pipe from rotating and deviating again during the fall, thereby improving installation accuracy and work efficiency. However, this application is limited to high-energy-consuming construction equipment and ignores the huge energy loss caused by the unreasonable use of transformers in the construction area. Summary of the Invention

[0004] The technical problem addressed by this invention is that existing technologies for energy-saving optimization during the construction phase of intelligent electromechanical installations focus on individual equipment, lacking overall planning. These approaches are often limited to high-energy-consuming construction equipment such as cranes and conveyors, while ignoring the significant energy losses caused by inappropriate use of transformers in the construction area.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: An intelligent electromechanical installation energy-saving optimization system for the construction phase, comprising: Data statistics module, equipment operation optimization module, power resource configuration module and interactive storage module; The data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit, which are used to obtain statistics on construction plans, construction equipment and transformer data in the construction area; The equipment operation optimization module includes an equipment feature unit and an equipment scheduling unit, which are used to obtain a statistical set of time series features of a single device, predict the operation probability sequence of a single device, calculate the load forecast sequence of construction equipment, and generate a staggered suspension strategy. The power resource allocation module includes a regional power forecasting unit and a transformer dispatching unit, which are used to forecast the overall load of the construction area to obtain the regional power forecast total load, and calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence; The interactive storage module is used to provide a visual interface to users, store all system data and generate an electromechanical installation energy-saving optimization log.

[0006] Preferably, the data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit; The construction equipment statistics unit is used to obtain equipment historical operation data, equipment basic data and construction plan data based on the BIM construction progress management system, and obtain real-time equipment status data based on the sensors configured on each construction equipment; The equipment historical operation data includes power data and operation status records of each construction equipment at each time within two weeks, and the operation status records are startup, shutdown and standby; The basic equipment data includes the rated power, priority level, startup warm-up time, maximum operating time and standby power consumption of each construction equipment, and the priority level includes high priority, medium priority and low priority; The construction plan data includes the task type code, the start time of each task, the end time of each task, the list of construction equipment used for each task and the parallel relationship between each task in the construction plan for the day; The real-time device status data includes startup status, shutdown status and real-time power.

[0007] Preferably, the power equipment statistical unit is used to obtain real-time regional total power, transformer environmental data, macro-operation data, historical total load curves, transformer performance parameters and transformer commissioning status; Collect real-time data from smart meters in the construction area to obtain the real-time total regional power. The real-time total regional power includes the real-time active power and reactive power of the entire construction area or power supply zone. The collection time window is 1 minute. The transformer environmental data is collected by the temperature and humidity sensors at the heat dissipation ports of the transformers, and the transformer environmental data includes the on-site temperature and on-site humidity of each transformer; Obtaining macro operation data according to the BIM construction progress management system, wherein the macro operation data includes the electromechanical installation construction stage and the electromechanical installation type; Based on the completed projects in the historical database, the total power load data for each electromechanical installation construction stage and electromechanical installation type is statistically obtained. The historical total load curve is generated based on the total power load data. The electromechanical installation construction stage includes the auxiliary material installation stage, the main body installation stage, and the acceptance stage. The transformer performance parameters include the rated capacity, no-load loss, load loss and impedance voltage percentage of each transformer supplying power to the construction area; The transformer commissioning status includes a grid-connected operation state, a non-grid-connected operation state and a load rate.

[0008] Preferably, the equipment operation optimization module includes an equipment feature unit and an equipment scheduling unit; The equipment feature unit is used to collect statistics on historical operation data, equipment basic data and construction plan data in the order of each construction equipment to obtain a single equipment time series feature set; The single device time series feature set includes time features, historical energy usage features, planned task features and device status features; The time characteristics include the current planned task time of using the single device and the time until the next task of using the single device; Historical energy usage characteristics include the average power of a single device over the past 5 minutes and 15 minutes, and the duration of the device's operating state; Planned task characteristics include whether there is a planned task requiring the device within the next 60 minutes, the task type code, and the estimated duration of the task; Device status characteristics include startup status, running time, shutdown status, and shutdown time.

[0009] Preferably, the equipment scheduling unit is used to predict and obtain a single equipment operation probability sequence, calculate and obtain a construction equipment load prediction sequence and generate a staggered suspension strategy. The processing logic includes: The pre-trained LSTM model is used to classify and predict the time series feature set of a single device to obtain a single device operation probability sequence. The single device operation probability sequence includes the probability of each construction device operating in the next 30 minutes. The next 30 minutes are divided into 6 time steps with an interval of 5 minutes. Based on the weighted summation of the single-device operation probability sequence and the rated power data in the equipment basic data, the probability of each construction equipment operating at each time step in the next 30 minutes is multiplied by the rated power to obtain the single-device predicted power set. Based on the sum of the data in the single-device predicted power set, the construction equipment load forecast sequence is obtained. A staggered pause strategy is generated based on the construction equipment load forecast sequence, real-time equipment status data, and priority data in the equipment basic data. The staggered pause strategy includes: when the construction equipment load forecast sequence is greater than or equal to a preset energy consumption power threshold, querying the real-time equipment status data and the equipment basic data to obtain the lowest priority start-up state construction equipment, and generating an equipment pause instruction for the lowest priority start-up state construction equipment; Iterate the calculation until the construction equipment load forecast sequence is less than the preset energy consumption power threshold.

[0010] Preferably, the power resource configuration module includes a regional power forecasting unit and a transformer dispatching unit, which are used to forecast the overall load of the construction area to obtain the regional power forecast total load, and calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence to reduce power supply losses and ensure power supply reliability.

[0011] Preferably, the regional power forecasting unit is used to analyze the real-time regional total power, transformer environmental data, macro-operation data, historical total load curve and transformer performance parameters to obtain a power configuration feature set, and to predict the regional power forecast total load based on the power configuration feature set, and to obtain the trend and peak-valley values of the transformer power supply demand in the construction area. The processing logic includes: The power configuration feature set includes macro-operation feature coding, real-time regional load features, historical regional load features, and transformer environmental data; Obtaining a macro-operation feature code based on the macro-operation data, wherein the macro-operation feature code includes a corresponding code of the electromechanical installation construction stage and a corresponding code of the electromechanical installation type, which are generated in series; The real-time regional load characteristics are obtained based on the real-time regional total power statistics. The real-time load characteristics include the power load mean and power load variance within a 5-minute window step within 30 minutes. Based on the historical total load curve under the same macro-operation feature coding conditions, the historical regional load characteristics are obtained by statistics. The historical load statistical characteristics include the power load mean and power load variance of the 1-hour window step; The regional load characteristic matrix is generated based on the power configuration feature set and the construction equipment load forecast sequence.

[0012] Preferably, the regional load feature matrix is processed by a pre-trained XGBoost regression model to obtain the regional total active power and regional total reactive power for the next 2 hours with a step length of 15 minutes, and a regional total load forecast sequence is obtained; The apparent power peak value of each prediction time step is obtained by calculating the regional total load prediction sequence through the apparent power algorithm, and the regional load safety capacity is obtained by multiplying the apparent power peak value of each prediction time step by the preset safety margin coefficient.

[0013] Preferably, the transformer dispatching unit is used to calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence, and obtain the transformer commissioning operation mode with the lowest energy consumption; The power configuration planning model processes the regional load safety capacity, transformer commissioning status, and regional load safety capacity to obtain the optimal transformer commissioning schedule. The processing logic of the power configuration planning model is as follows: Count the transformers whose commissioning status is grid-connected operation, calculate the sum of no-load losses based on the transformer performance parameters corresponding to the transformers in the grid-connected operation state, and calculate the sum of load losses based on the regional total load forecast sequence; The sum of no-load losses and the sum of active load losses are added to obtain the total regional loss. The minimum regional total loss is taken as the objective function. A 0-1 integer programming model is established with the regional load safety capacity as the constraint condition. The optimal transformer commissioning schedule is calculated using an integer programming solver. The optimal transformer commissioning schedule includes the transformer numbers that are put into operation in the construction area at each time step in the next 2 hours with a step length of 15 minutes.

[0014] Preferably, the interactive storage module includes an interactive display unit and a data storage unit; The display interaction unit is used to provide a visual interface to the user and receive instructions from the user to adjust parameters of the data statistics module, equipment operation optimization module, and power resource configuration module; The data storage unit is used to receive and store all output data from the data statistics module, equipment operation optimization module, and power resource configuration module, and generate an electromechanical installation energy-saving optimization log. Beneficial effects of the present invention: This application conducts a fusion analysis from the two perspectives of equipment and regional power supply, calculates the regional transformer load based on the equipment's predicted load, reuses the multi-sensor data of the intelligent electromechanical installation, and combines the BIM construction planning system to coordinate regional power consumption and leave safety redundancy, thereby achieving scientific and high-precision energy-saving optimization and realizing green building construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of the basic flow of an intelligent electromechanical installation energy-saving optimization system for the construction phase is provided as an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0017] Reference Figure 1 , which is an embodiment of the present invention, provides an intelligent electromechanical installation energy-saving optimization system for the construction phase, comprising: Data statistics module, equipment operation optimization module, power resource configuration module and interactive storage module; The data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit, which are used to obtain statistics on construction plans, construction equipment and transformer data in the construction area; The equipment operation optimization module includes an equipment feature unit and an equipment scheduling unit, which are used to obtain a statistical set of time series features of a single device, predict the operation probability sequence of a single device, calculate the load forecast sequence of construction equipment, and generate a staggered suspension strategy. The power resource allocation module includes a regional power forecasting unit and a transformer dispatching unit, which are used to forecast the overall load of the construction area to obtain the regional power forecast total load, and calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence; The interactive storage module is used to provide a visual interface to users, store all system data and generate an electromechanical installation energy-saving optimization log.

[0018] In this embodiment, the data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit; The construction equipment statistics unit is used to obtain equipment historical operation data, equipment basic data and construction plan data based on the BIM construction progress management system, and obtain real-time equipment status data based on the sensors configured on each construction equipment; The equipment historical operation data includes power data and operation status records of each construction equipment at each time within two weeks, and the operation status records are startup, shutdown and standby; The basic equipment data includes the rated power, priority level, startup warm-up time, maximum operating time and standby power consumption of each construction equipment, and the priority level includes high priority, medium priority and low priority; The construction plan data includes the task type code, the start time of each task, the end time of each task, the list of construction equipment used for each task and the parallel relationship between each task in the construction plan for the day; The real-time device status data includes startup status, shutdown status and real-time power.

[0019] In this embodiment, the power equipment statistics unit is used to obtain real-time regional total power, transformer environmental data, macro operation data, historical total load curve, transformer performance parameters and transformer commissioning status; Collect real-time data from smart meters in the construction area to obtain the real-time total regional power. The real-time total regional power includes the real-time active power and reactive power of the entire construction area or power supply zone. The collection time window is 1 minute. The transformer environmental data is collected by the temperature and humidity sensors at the heat dissipation ports of the transformers, and the transformer environmental data includes the on-site temperature and on-site humidity of each transformer; Obtaining macro operation data according to the BIM construction progress management system, wherein the macro operation data includes the electromechanical installation construction stage and the electromechanical installation type; Based on the completed projects in the historical database, the total power load data for each electromechanical installation construction stage and electromechanical installation type is statistically obtained. The historical total load curve is generated based on the total power load data. The electromechanical installation construction stage includes the auxiliary material installation stage, the main body installation stage, and the acceptance stage. The transformer performance parameters include the rated capacity, no-load loss, load loss and impedance voltage percentage of each transformer supplying power to the construction area; The transformer commissioning status includes a grid-connected operation state, a non-grid-connected operation state and a load rate.

[0020] In this embodiment, the equipment operation optimization module includes an equipment feature unit and an equipment scheduling unit; The equipment feature unit is used to collect statistics on historical operation data, equipment basic data and construction plan data in the order of each construction equipment to obtain a single equipment time series feature set; The single device time series feature set includes time features, historical energy usage features, planned task features and device status features; The time characteristics include the current planned task time of using the single device and the time until the next task of using the single device; Historical energy usage characteristics include the average power of a single device over the past 5 minutes and 15 minutes, and the duration of the device's operating state; Planned task characteristics include whether there is a planned task requiring the device within the next 60 minutes, the task type code, and the estimated duration of the task; Device status characteristics include startup status, running time, shutdown status, and shutdown time.

[0021] In this embodiment, the equipment scheduling unit is used to predict and obtain a single equipment operation probability sequence, calculate and obtain a construction equipment load prediction sequence, and generate a peak-shifting suspension strategy. The processing logic includes: The pre-trained LSTM model is used to classify and predict the time series feature set of a single device to obtain a single device operation probability sequence. The single device operation probability sequence includes the probability of each construction device operating in the next 30 minutes. The next 30 minutes are divided into 6 time steps with an interval of 5 minutes. Based on the weighted summation of the single-device operation probability sequence and the rated power data in the equipment basic data, the probability of each construction equipment operating at each time step in the next 30 minutes is multiplied by the rated power to obtain the single-device predicted power set. Based on the sum of the data in the single-device predicted power set, the construction equipment load forecast sequence is obtained. A staggered pause strategy is generated based on the construction equipment load forecast sequence, real-time equipment status data, and priority data in the equipment basic data. The staggered pause strategy includes: when the construction equipment load forecast sequence is greater than or equal to a preset energy consumption power threshold, querying the real-time equipment status data and the equipment basic data to obtain the lowest priority start-up state construction equipment, and generating an equipment pause instruction for the lowest priority start-up state construction equipment; Iterate the calculation until the construction equipment load forecast sequence is less than the preset energy consumption power threshold.

[0022] Among them, the equipment operation optimization module accurately predicts the usage requirements of a single device or a group of devices and adjusts their operating parameters in real time, thereby minimizing the equipment's no-load and standby energy consumption, improving the efficiency of single-machine operation, and providing planned load change information for Module 2.

[0023] In this embodiment, the power resource configuration module includes a regional power forecasting unit and a transformer scheduling unit, which are used to predict the overall load of the construction area to obtain the regional power forecast total load, and calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence to reduce power supply losses and ensure power supply reliability.

[0024] In this embodiment, the regional power forecasting unit is used to analyze the real-time regional total power, transformer environmental data, macro-operation data, historical total load curves, and transformer performance parameters to obtain a power configuration feature set. Based on the power configuration feature set, the unit makes a prediction to obtain the regional predicted total power load and obtain the trend and peak-valley values of the transformer power supply demand in the construction area. The processing logic includes: The power configuration feature set includes macro-operation feature coding, real-time regional load features, historical regional load features, and transformer environmental data; Obtaining a macro-operation feature code based on the macro-operation data, wherein the macro-operation feature code includes a corresponding code of the electromechanical installation construction stage and a corresponding code of the electromechanical installation type, which are generated in series; The real-time regional load characteristics are obtained based on the real-time regional total power statistics. The real-time load characteristics include the power load mean and power load variance within a 5-minute window step within 30 minutes. Based on the historical total load curve under the same macro-operation feature coding conditions, the historical regional load characteristics are obtained by statistics. The historical load statistical characteristics include the power load mean and power load variance of the 1-hour window step; The regional load characteristic matrix is generated based on the power configuration feature set and the construction equipment load forecast sequence.

[0025] In this embodiment, the regional load feature matrix is processed by the pre-trained XGBoost regression model to obtain the regional total active power and regional total reactive power for the next 2 hours with a step size of 15 minutes, and the regional total load forecast sequence is obtained; The apparent power peak value of each prediction time step is obtained by calculating the regional total load prediction sequence through the apparent power algorithm, and the regional load safety capacity is obtained by multiplying the apparent power peak value of each prediction time step by the preset safety margin coefficient.

[0026] In this embodiment, the transformer dispatching unit is used to calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence, and obtain the transformer commissioning operation mode with the lowest energy consumption; The power configuration planning model processes the regional load safety capacity, transformer commissioning status, and regional load safety capacity to obtain the optimal transformer commissioning schedule. The processing logic of the power configuration planning model is as follows: Count the transformers whose commissioning status is grid-connected operation, calculate the sum of no-load losses based on the transformer performance parameters corresponding to the transformers in the grid-connected operation state, and calculate the sum of load losses based on the regional total load forecast sequence; The sum of no-load losses and the sum of active load losses are added to obtain the total regional loss. The minimum regional total loss is taken as the objective function. A 0-1 integer programming model is established with the regional load safety capacity as the constraint condition. The optimal transformer commissioning schedule is calculated using an integer programming solver. The optimal transformer commissioning schedule includes the transformer numbers that are put into operation in the construction area at each time step in the next 2 hours with a step length of 15 minutes.

[0027] In this embodiment, the interactive storage module includes an interactive display unit and a data storage unit; The display interaction unit is used to provide a visual interface to the user and receive instructions from the user to adjust parameters of the data statistics module, equipment operation optimization module, and power resource configuration module; The data storage unit is used to receive and store all output data from the data statistics module, equipment operation optimization module, and power resource configuration module, and generate an electromechanical installation energy-saving optimization log.

[0028] Among them, this application conducts a fusion analysis from the two perspectives of equipment and regional power supply, calculates the regional transformer load based on the equipment's predicted load, reuses the multi-sensor data of the intelligent electromechanical installation, and combines the BIM construction planning system to coordinate regional power consumption and leave safety redundancy to achieve scientific and high-precision energy-saving optimization and realize green building construction.

[0029] Those skilled in the art will appreciate that embodiments of the present invention may provide methods, systems, or computer program products. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0030] 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. An intelligent electromechanical installation energy-saving optimization system for the construction phase, characterized in that: include: Data statistics module, equipment operation optimization module, power resource configuration module and interactive storage module; The data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit, which are used to obtain statistics on construction plans, construction equipment and transformer data in the construction area; The equipment operation optimization module includes an equipment feature unit and an equipment scheduling unit, which are used to obtain a statistical set of time series features of a single device, predict the operation probability sequence of a single device, calculate the load forecast sequence of construction equipment, and generate a staggered suspension strategy. The power resource allocation module includes a regional power forecasting unit and a transformer dispatching unit, which are used to forecast the overall load of the construction area to obtain the regional power forecast total load, and calculate the optimal transformer commissioning schedule based on the regional load safety capacity and the regional total load forecast sequence; The interactive storage module is used to provide a visual interface to users, store all system data and generate an electromechanical installation energy-saving optimization log.

2. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 1, characterized in that: The data acquisition module includes a construction equipment statistics unit and a power equipment statistics unit; The construction equipment statistics unit is used to obtain equipment historical operation data, equipment basic data and construction plan data based on the BIM construction progress management system, and obtain real-time equipment status data based on the sensors configured on each construction equipment; The equipment historical operation data includes power data and operation status records of each construction equipment at each time within two weeks, and the operation status records are startup, shutdown and standby; The basic equipment data includes the rated power, priority level, startup warm-up time, maximum operating time and standby power consumption of each construction equipment, and the priority level includes high priority, medium priority and low priority; The construction plan data includes the task type code, the start time of each task, the end time of each task, the list of construction equipment used for each task and the parallel relationship between each task in the construction plan for the day; The real-time device status data includes startup status, shutdown status and real-time power.

3. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 2, characterized in that: The power equipment statistics unit is used to obtain real-time regional total power, transformer environmental data, macro-operation data, historical total load curves, transformer performance parameters and transformer commissioning status; Collect real-time data from smart meters in the construction area to obtain the real-time total regional power. The real-time total regional power includes the real-time active power and reactive power of the entire construction area or power supply zone. The collection time window is 1 minute. The transformer environmental data is collected by the temperature and humidity sensors at the heat dissipation ports of the transformers, and the transformer environmental data includes the on-site temperature and on-site humidity of each transformer; Obtaining macro operation data according to the BIM construction progress management system, wherein the macro operation data includes the electromechanical installation construction stage and the electromechanical installation type; Based on the completed projects in the historical database, the total power load data for each electromechanical installation construction stage and electromechanical installation type is statistically obtained. The historical total load curve is generated based on the total power load data. The electromechanical installation construction stage includes the auxiliary material installation stage, the main body installation stage, and the acceptance stage. The transformer performance parameters include the rated capacity, no-load loss, load loss and impedance voltage percentage of each transformer supplying power to the construction area; The transformer commissioning status includes a grid-connected operation state, a non-grid-connected operation state and a load rate.

4. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 1, characterized in that: The equipment operation optimization module includes the equipment feature unit and the equipment scheduling unit; The equipment feature unit is used to collect statistics on historical operation data, equipment basic data and construction plan data in the order of each construction equipment to obtain a single equipment time series feature set; The single device time series feature set includes time features, historical energy usage features, planned task features and device status features; The time characteristics include the current planned task time of using the single device and the time until the next task of using the single device; Historical energy usage characteristics include the average power of a single device over the past 5 minutes and 15 minutes, and the duration of the device's operating state; Planned task characteristics include whether there is a planned task requiring the device within the next 60 minutes, the task type code, and the estimated duration of the task; Device status characteristics include startup status, running time, shutdown status, and shutdown time.

5. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 4, characterized in that: The equipment scheduling unit is used to predict and obtain the probability sequence of single equipment operation, calculate the load forecast sequence of construction equipment, and generate a staggered suspension strategy. The processing logic includes: The pre-trained LSTM model is used to classify and predict the time series feature set of a single device to obtain a single device operation probability sequence. The single device operation probability sequence includes the probability of each construction device operating in the next 30 minutes. The next 30 minutes are divided into 6 time steps with an interval of 5 minutes. Based on the weighted summation of the single-device operation probability sequence and the rated power data in the equipment basic data, the probability of each construction equipment operating at each time step in the next 30 minutes is multiplied by the rated power to obtain the single-device predicted power set. Based on the sum of the data in the single-device predicted power set, the construction equipment load forecast sequence is obtained. A staggered pause strategy is generated based on the construction equipment load forecast sequence, real-time equipment status data, and priority data in the equipment basic data. The staggered pause strategy includes: when the construction equipment load forecast sequence is greater than or equal to a preset energy consumption power threshold, querying the real-time equipment status data and the equipment basic data to obtain the lowest priority start-up state construction equipment, and generating an equipment pause instruction for the lowest priority start-up state construction equipment; Iterate the calculation until the construction equipment load forecast sequence is less than the preset energy consumption power threshold.

6. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 1, characterized in that: The power resource allocation module includes a regional power forecasting unit and a transformer dispatching unit, which are used to forecast the overall load of the construction area to obtain the regional power forecast total load. The optimal transformer commissioning schedule is calculated based on the regional load safety capacity and the regional total load forecast sequence to reduce power supply losses and ensure power supply reliability.

7. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 6, characterized in that: The regional power forecasting unit is used to analyze the real-time regional total power, transformer environmental data, macro-operation data, historical total load curves, and transformer performance parameters to obtain a power configuration feature set. Based on the power configuration feature set, it predicts the regional total power load and obtains the trend and peak-valley values of the construction area's transformer power supply demand. The processing logic includes: The power configuration feature set includes macro-operation feature coding, real-time regional load features, historical regional load features, and transformer environmental data; Obtaining a macro-operation feature code based on the macro-operation data, wherein the macro-operation feature code includes a corresponding code of the electromechanical installation construction stage and a corresponding code of the electromechanical installation type, which are generated in series; The real-time regional load characteristics are obtained based on the real-time regional total power statistics. The real-time load characteristics include the power load mean and power load variance within a 5-minute window step within 30 minutes. Based on the historical total load curve under the same macro-operation feature coding conditions, the historical regional load characteristics are obtained by statistics. The historical load statistical characteristics include the power load mean and power load variance of the 1-hour window step; The regional load characteristic matrix is generated based on the power configuration feature set and the construction equipment load forecast sequence.

8. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 7, characterized in that: The regional load feature matrix is processed by the pre-trained XGBoost regression model to obtain the regional total active power and regional total reactive power for the next 2 hours with a step length of 15 minutes, and the regional total load forecast sequence is obtained; The apparent power peak value of each prediction time step is obtained by calculating the regional total load prediction sequence through the apparent power algorithm, and the regional load safety capacity is obtained by multiplying the apparent power peak value of each prediction time step by the preset safety margin coefficient.

9. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 8, characterized in that: The transformer dispatching unit is used to calculate the optimal transformer commissioning schedule based on the regional load safety capacity and regional total load forecast sequence, and obtain the transformer commissioning operation mode with the lowest energy consumption; The power configuration planning model processes the regional load safety capacity, transformer commissioning status, and regional load safety capacity to obtain the optimal transformer commissioning schedule. The processing logic of the power configuration planning model is as follows: Count the transformers whose commissioning status is grid-connected operation, calculate the sum of no-load losses based on the transformer performance parameters corresponding to the transformers in the grid-connected operation state, and calculate the sum of load losses based on the regional total load forecast sequence; The sum of no-load losses and the sum of active load losses are added to obtain the total regional loss. The minimum regional total loss is taken as the objective function. A 0-1 integer programming model is established with the regional load safety capacity as the constraint condition. The optimal transformer commissioning schedule is calculated using an integer programming solver. The optimal transformer commissioning schedule includes the transformer numbers that are put into operation in the construction area at each time step in the next 2 hours with a step length of 15 minutes.

10. The intelligent electromechanical installation energy-saving optimization system for the construction phase according to claim 1, characterized in that: The interactive storage module includes an interactive display unit and a data storage unit; The display interaction unit is used to provide a visual interface to the user and receive instructions from the user to adjust parameters of the data statistics module, equipment operation optimization module, and power resource configuration module; The data storage unit is used to receive and store all output data from the data statistics module, equipment operation optimization module, and power resource configuration module, and generate an electromechanical installation energy-saving optimization log.

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