KR102634713B1 - Real-time control type mid/long-distance wired and wireless convergence energy management system - Google Patents

Abstract

The present invention relates to a real-time control type mid- to long-distance wired and wireless convergence energy management system. More specifically, the present invention relates to objects such as devices or facilities that use energy in buildings such as schools, gyms, offices, residential-commercial buildings, apartments, etc. Improves convenience of management by monitoring power usage by load usage in real time, storing the monitored information with a real-time timeline, analyzing the stored data, calculating the expected load power consumption of the object, and then automatically executing the calculation. It is about a real-time controllable mid- to long-distance wired and wireless convergence energy management system that enables energy management.

Description

Real-time control type mid/long-distance wired and wireless convergence energy management system}

The present invention relates to a real-time controllable mid- to long-distance wired and wireless convergence energy management system. More specifically, it is based on a multi-channel wireless convergence platform by applying wireless communication, convergence wired communication and mesh network technology to schools, gyms, In buildings such as offices, residential-commercial buildings, apartments, etc., we monitor in real time the power usage by load purpose consumed by objects such as devices or facilities that use energy, and store the monitored information along with a real-time timeline. This relates to a real-time control type mid- to long-distance wired and wireless convergence energy management system that improves convenience of management and enables energy management by analyzing and calculating the expected load power consumption of the object and then automatically executing it.

Recently, as building facilities have been modernized, automatic control systems that automatically control facilities such as power, lighting, air conditioning such as air conditioning and heating, and disaster prevention and crime prevention facilities installed within the building have spread. The development of a building management system that integrates and manages the building as a whole has been proposed.

The conventional building management system measures the amount of energy consumed, such as electricity, gas, temperature, flow, etc., used in each single building and provides each data to the manager. Separate data is provided for each energy used in the building. If there is no management, the integrated management of the building is difficult because the usage amount cannot be accurately known.

In addition, in the conventional building management system, sensors or devices installed to measure energy consumption are not installed to manage energy but to maintain each device or facility, so there is an error between actual consumption and measured consumption. Not only does it occur significantly, but because the measured data is not stored and volatile is used, there is no accumulated data or information even after the time used for measurement, making it difficult to predict or manage energy consumption in the future.

In terms of energy consumption in buildings, unnecessary energy consumption mainly occurs in heating, cooling, and lighting devices. For example, heating energy is consumed inside the building even though the outside temperature is sufficiently high, or the outside temperature is sufficiently high. There is a problem that cooling energy is consumed inside the building despite the low level, or lighting energy is consumed because the lighting installed inside the building is used even though the external illumination level is sufficiently bright.

It is difficult for conventional building management systems to reflect the energy consumption characteristics of the area in which the building is located, and expensive energy management systems are operated in specific buildings.

Republic of Korea Patent Publication No. 10-2022-0067379 (2022.05.24, published) Republic of Korea Patent No. 10-1068862 (registered on September 23, 2011)

The present invention was proposed to solve the above problems, and monitors in real time the power usage by load purpose used by devices and facilities (hereinafter abbreviated as 'objects') that consume energy in a building, and monitors the information. Convenience and efficiency of energy management in buildings by accumulating and storing information in a database along with a real-time timeline, analyzing the information stored in the database, and creating and executing a schedule that can supply the power usage consumed by the operation of the object under optimal conditions. The purpose is to provide a mid- to long-distance wired and wireless convergence energy management system with improved real-time control.

In addition, the present invention is a real-time controllable medium- and long-distance wired system that can reduce energy waste by reflecting environmental information such as weather, temperature, and illumination as correction values when creating a schedule to control the operation of an object and generating a corrected schedule. and the purpose of providing a wireless fusion energy management system.

In addition, the present invention is provided with a plurality of sensors that detect the motion of an object, determines whether or not there is an abnormality in the object by comparing the detection values detected by each sensor, and provides information about the object for which abnormal symptoms or occurrence of an abnormality has been detected. The purpose is to provide a real-time control-type mid- to long-distance wired and wireless convergence energy management system that can transmit to a pre-stored administrator terminal and take prompt follow-up action.

In addition, the present invention applies wireless communication (LoRa/Bluetooth) or convergence wired communication (DMX-512) and mesh network (MESH-Network) technology and controls the energy management of the object in real time based on a multi-channel wireless convergence platform, It provides a real-time control-type mid- to long-distance wired and wireless convergence energy management system that improves the accuracy and prediction accuracy of energy management of objects by learning accumulated information and creating a schedule for energy management of objects. There is a purpose.

In order to achieve the above object, the present invention includes a usage collection unit that receives in real time the power usage by load purpose of an object consuming energy and stores the received power usage by load use in a database along with a real-time timeline;

a usage calculation unit that analyzes the power usage for each load purpose stored in the database and calculates the amount of power consumed by the object;

An operation management unit that controls the operation of the object by applying the amount of power consumption calculated by the usage calculation unit to the object in real time,

The usage calculation unit,

A calculation module that classifies the power consumption by load purpose stored in the database by the stored timeline and divides it by season, date, or time to calculate the power consumption by load purpose of the object;

A schedule creation module that generates a control schedule to control the operation of the object through the calculated power usage for each load purpose of the object;

After receiving the control schedule created through the schedule creation module, environmental information such as real-time weather information, fine dust information, air information, sunrise time, sunset time, etc. is collected through the Internet connected through wired or wireless communication means. It is characterized by including a schedule correction module applied to the control schedule.

In addition, the schedule correction module generates a corrected correction schedule for operation control of the object by applying the environmental information to the control schedule received from the schedule creation module, and transmits the generated correction schedule to the calculation module to It is characterized by being applied as a correction value in the process of calculating power usage for each load purpose.

In addition, the usage collection unit remotely controls an electromagnetic contactor placed on the object, and calculates the current value measured by a current sensor that measures the current between the object and the electromagnetic contactor, and the voltage between the electromagnetic contactor and the power line. It further includes a status diagnosis unit that receives the voltage values measured from the measuring voltage sensor in real time and stores them in the database, and transmits the information to a pre-stored administrator terminal when an abnormal situation occurs in the process of receiving the current and voltage values. It is characterized by being

At this time, the status diagnosis unit checks whether there is an abnormality in the received voltage value and at the same time checks whether there is an abnormality in the received current value. When the voltage value is abnormal, it determines that a problem has occurred in power supply and sends this to the previously stored manager terminal. The information is transmitted to , and when the voltage value is normal and the current value is abnormal, the object is determined to be in trouble and the information is transmitted to a pre-stored manager terminal.

In addition, a communication module is further provided to transmit the operation status of the usage collection unit, the usage calculation unit, and the operation management unit to a pre-stored administrator terminal or a central control server in real time, and the communication module is Lora (Long Range) or Bluetooth. It is characterized by including a wireless communication unit consisting of one of Bluetooth and a wired communication unit consisting of serial communication including RS-485.

The present invention achieved as described above not only monitors in real time the power usage by load purpose used by objects placed in a building, but also accumulates and stores the monitored information, analyzes the accumulated and stored information, and then optimizes the operation of each object. There is an effect of improving the efficiency of building energy management by creating and executing the necessary schedule.

In addition, the present invention can reduce the waste of energy used by objects placed in a building, thereby reducing the cost consumed in energy use, and by providing the optimal operation required for the operation of each object, it does not cause inconvenience to the user. It has the effect of maximizing user convenience.

In addition, the present invention improves the convenience of management and supervision by detecting in real time the presence or absence of abnormalities in objects placed in a building and transmitting the detected information to a pre-stored manager terminal through wired or wireless communication means to enable prompt follow-up action. It has an effect.

In addition, the present invention has the effect of improving operation and prediction accuracy for energy management as usage time increases by learning accumulated data in creating a schedule for controlling energy management of an object.

Figure 1 is an exemplary diagram illustrating a real-time controllable medium- and long-distance wired and wireless convergence energy management system according to the present invention.
Figure 2 is a schematic diagram showing the structure of a real-time controllable medium- and long-distance wired and wireless convergence energy management system according to the present invention.
Figure 3 is an exemplary diagram showing a usage collection unit constituting the present invention.
Figure 4 is an exemplary diagram showing a monitoring screen of the usage collection unit constituting the present invention.
Figure 5 is an example diagram showing information stored in a database constituting the present invention.
Figure 6 is an exemplary diagram showing an embodiment of a condition diagnosis unit constituting the present invention.
Figure 7 is a schematic diagram showing the structure of a real-time controllable medium- and long-distance wired and wireless convergence energy management system according to the present invention.
Figure 8 is an exemplary diagram illustrating a real-time control type mid- to long-distance wired and wireless convergence energy management system according to another embodiment of the present invention.

Hereinafter, other purposes and features of the present invention in addition to the above purposes will be clearly revealed through description of embodiments with reference to the accompanying drawings.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted in an ideal or excessively formal sense unless explicitly defined in the present application. No.

Hereinafter, a preferred embodiment of the real-time control type medium- and long-distance wired and wireless convergence energy management system according to the present invention will be described with reference to the attached drawings.

First, the real-time control-type mid- to long-distance wired and wireless convergence energy management system (1) according to the present invention receives the power usage for each load purpose of the object consuming energy in real time, and displays the received power usage for each load purpose in a real-time timeline. A usage collection unit 10 that stores the data together in a database, a usage calculation unit 20 that calculates the amount of power consumed by the object by analyzing the power usage for each load purpose stored in the database, and the power consumption calculated by the usage calculation unit 20. It includes an operation management unit 30 that controls the operation of the object by applying the amount of power consumption to the object in real time.

The usage collection unit 10 collects the power usage consumed by objects placed in a building. Looking at this in more detail, the usage collection unit 10 collects power usage by load purpose of objects consuming energy in real time. The power consumption for each load purpose is stored in the database 40 along with a real-time timeline.

This usage collection unit 10 remotely controls the electromagnetic contactor 11 placed on the object as shown in FIG. 3, and a current sensor 12 that measures the current between the object and the electromagnetic contactor 11. ) and the voltage value measured by the voltage sensor 13, which measures the voltage between the magnetic contactor 11 and the power line, are received in real time and stored in the database, and the current value and the voltage A status diagnosis unit 14 that transmits the relevant information to a previously stored administrator terminal when an abnormal situation occurs in the process of receiving the value is further included.

Here, the database 40 is a storage medium that is connected to the usage collection unit 10 and stores the transmitted information. Since the structure and operation of this database are known, a detailed description will be omitted.

The usage collection unit 10 stores the sensed values detected by the current sensor 12 and the voltage sensor 13 in a database along with a real-time timeline, and accumulates the power usage for each load purpose used by each object and converts it into data. The electromagnetic contactor 11 placed on each object is remotely controlled. More precisely, the operation of the electromagnetic contactor 11 connected to the usage collection unit 10 is controlled by the control schedule of the object generated by the operation management unit 30, which will be described later. is controlled by

The current sensor 12 is disposed between the object and the electromagnetic contactor to detect the current generated during the operation of the object, and the voltage sensor 13 is a power source that supplies power (energy) to the electromagnetic contactor and the object. It is placed between them and detects the voltage of electricity supplied to the electromagnetic contactor.

The current sensor 12 and the voltage sensor 13 arranged as above transmit the current and voltage values sensed by each to the status diagnosis unit 14, and the status diagnosis unit 14 transmits the received voltage value. Check for abnormalities, and at the same time check for abnormalities in the received current value. If the voltage value is abnormal, it is determined that a problem has occurred in power supply, and the information is transmitted to the pre-stored manager terminal, and the voltage value is checked. is normal, and when the current value is abnormal, the object is determined to be in trouble and the information is transmitted to the previously stored manager terminal.

The condition diagnosis unit 14 compares the detection values (current value, voltage value) transmitted from the current sensor 12 and the voltage sensor 13 to determine whether or not there is an abnormality in the object as well as the power consumed by the object for each load purpose. After detecting the usage in real time, it is transmitted to the usage calculation unit 20, which will be described later.

The usage calculation unit 20 calculates the amount of power consumed by the object by analyzing the power usage for each load purpose of the object stored in the database through the usage collection unit 10. This usage calculation unit 20 is stored in the database. It is desirable to analyze the stored information at regular intervals to calculate the amount of power consumed by the object. In this case, the constant cycle may change depending on the type and capacity of the object.

The usage calculation unit 20 includes a calculation module 21 that classifies the power usage by load purpose stored in the database by the stored timeline and divides it by season, date, or time to calculate the power usage by load usage of the object; A schedule creation module 22 that generates a control schedule for controlling the operation of the object through the calculated power consumption for each load purpose of the object, receives the control schedule generated through the schedule generation module 22, and receives the control schedule through a wired or wireless It includes a schedule correction module 23 that collects environmental information such as real-time weather information, fine dust information, air information, sunrise time, sunset time, etc. through the Internet connected through a communication means and then applies it to the control schedule.

The calculation module 21 analyzes the information stored in the database and calculates the power consumption by load purpose used by the object by timeline. The power consumption by load purpose calculated by the calculation module 21 is calculated by the load purpose actually used by the object. Sort power usage by season, date, and time.

This calculation module 21 analyzes information stored in the database while repeatedly operating at a constant cycle. Here, the constant cycle may be one of 3 days, 7 days, or 14 days, and this cycle depends on the type of object and the capacity of the object. It can be changed accordingly, and in addition, the cycle can be shortened when environmental conditions such as external temperature and external illumination change rapidly in a short period of time, and the cycle can be changed to lengthen during periods when the change in environmental conditions is small.

The schedule creation module 22 generates a control schedule to control the operation of the object after receiving the power usage for each load purpose of the object calculated in the calculation module 21. The schedule generation module 22 generates a control schedule. In addition to turning the object's operation on/off, the schedule also includes a schedule that controls the operation speed and intensity of the operation depending on the type of object.

Meanwhile, the control schedule generated in the schedule creation module 22 is generated by analyzing only the power consumption by load purpose of the object calculated in the calculation module 21, that is, the power consumption by load purpose used by the object in real time, so external weather, Since temperature, illuminance, etc. are not taken into consideration, problems of wasting energy may occur when controlling an object using the generated control schedule.

Therefore, in the present invention, the control schedule generated through the schedule creation module 22 is transmitted to the schedule correction module 23, and then environmental information is added to create a correction schedule to be actually used.

The schedule correction module 23 applies environmental information such as weather information, fine dust information, air information, sunrise time, sunset time, etc. collected through the Internet connected through wired or wireless communication means to the control schedule to actually control the object. Create a correction schedule to control.

This schedule correction module 23 applies the environmental information to the control schedule received from the schedule generation module 22 to generate a corrected correction schedule for the operation control of the object, and sends the generated correction schedule to the calculation module. It is transmitted to (21) and applied as a correction value in the process of calculating the power usage for each load purpose of the object.

In other words, the schedule correction module 23 applies the environmental information collected through the Internet to the control schedule received from the schedule generation module 22 to generate a correction schedule to be actually applied to the object, thereby adjusting the energy consumption during the operation of the object. It reduces waste and does not cause user inconvenience.

For example, if the time to control lighting at a specific location in the building in the control schedule is low when the expected value of external illumination is low among the environmental information collected by the schedule correction module 23, the operating time of the lighting is extended to avoid causing user inconvenience. It may not be possible.

As another example, the control schedule created in the schedule creation module 22 applies the external temperature and illuminance confirmed in the schedule correction module 23 to the operating time and set temperature of the air conditioning device to be operated on the same day to determine the air conditioning device. Correct the operating time and set temperature.

The environmental information collected by the schedule correction module 23 may further include wind direction and speed in addition to the weather information, fine dust information, air information, sunrise time, and sunset time, and the air information is air pollution information, These include ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide contained in the atmosphere.

Meanwhile, the correction schedule generated in the schedule correction module 23 is transmitted to the calculation module 21 and applied as a correction value in the process of calculating the power usage for each load purpose of the object. The calculation module 21 is a schedule correction module. By using the correction schedule delivered in (23) to include environmental information along with a real-time timeline in the process of calculating the power usage by load use of the object, more accurate and detailed power usage by load use can be calculated.

In other words, the calculation module 21 applies the environmental information collected in real time along with the information stored in the database as a correction value to calculate the power consumption for each load purpose used by each object, thereby calculating the power consumption for each load purpose that changes depending on the environment. The more the control schedule and correction schedule are accumulated, the more accurate the power usage can be calculated for each load purpose of the object.

Therefore, as information accumulates in the database and as the number of control schedules and correction schedules generated while the schedule creation module 22 and schedule correction module 23 operate increases, more accurate power consumption can be calculated for each load purpose of the object. , Through this, the accuracy of the correction schedule that controls the object can be improved.

The operation management unit 30 controls the operation of the object by applying the power consumption strategy calculated by the usage calculation unit 20 to the object in real time. More precisely, the correction generated by the schedule correction module 23 The schedule is applied to the relevant object.

This operation management unit 30 controls the operation of the object by controlling the operation of the electromagnetic contactor 11 connected through the usage collection unit 10, and the control command is generated in the schedule correction module 23. It is determined by the established correction schedule.

Meanwhile, in the present invention, the operating status of the usage collection unit 10, the usage calculation unit 20, and the operation management unit 30 and the information of the status diagnosis unit 14 are transmitted to a pre-stored administrator terminal or central control server. A communication module 50 for transmission is further provided. The communication module 50 includes a wireless communication unit 51 consisting of either LoRa (Long Range) or Bluetooth, and serial communication including RS-485. It includes a wired communication unit 52 consisting of (Serial Communication).

Here, the pre-stored manager terminal may be a portable terminal or smartphone of the manager who manages and supervises the energy management system according to the present invention, or may be a dedicated application installed on the portable terminal or smartphone.

Figure 8 is an exemplary diagram illustrating a real-time control type mid- to long-distance wired and wireless convergence energy management system according to another embodiment of the present invention.

Referring to the drawing, in the real-time control type medium- and long-distance wired and wireless convergence energy management system 1 according to this embodiment, the schedule correction module 23 of the usage calculation unit 20 includes a machine learning module 23a. This machine learning module 23a classifies the power usage by load purpose stored in the database 40 by the stored timeline, divides it by season, date, or time to calculate the power usage by load purpose of the object. It is equipped to analyze and learn/predict related data using deep learning techniques.

Power load-related data for learning of the machine learning module 23a includes load energy-related information of an object that consumes energy. Among this load energy-related information, hardware information includes the type, capacity, and performance of each load device of the object. , price, production year, etc. may be included, and the software information that controls it may include related information such as detailed information, update version, and date.

In addition, power load-related data may include environmental information. As described above, such environmental information may further include monthly average solar radiation, maximum solar radiation, etc. in addition to weather information, fine dust information, air information, sunrise time, and sunset time.

Accordingly, through the power load-related data stored in the database 40, the machine learning module 23a generates power usage prediction and load pattern data for each load purpose of the object through a machine learning model. This load pattern data refers to the corresponding load pattern data. The power load of an object by season, year, month, day of the week, and time period can be expressed in the form of values that appear along a timeline.

In addition, the machine learning model of the machine learning module 23a generates correction data by comparing power load prediction data and actual data for each load purpose during learning, and changes the parameters and structure in the machine learning model so that the correction value in the correction data becomes smaller. You can.

The machine learning model can predict the average value of the power usage of the object according to the power load data at a specific point in time, but more accurately, if more information about the temperature value and rate of change of temperature before a certain point is added, the predicted power usage value will be more accurate. This can be calculated.

If it is difficult to derive accurate formulas for numerous variables, the machine learning module 23a can calculate the predicted power usage value through a method based on numerical analysis. Neural Network Algorithm and Support Vector are examples of such numerical analysis methods.

Accordingly, the machine learning module 23a uses the power load-related data of the database 40 as input data through a machine learning model to generate power usage prediction and load pattern data for each load purpose for energy management of a specific object, The schedule correction module 23 can be applied to the control schedule based on this.

Meanwhile, the machine learning module 23a according to the present embodiment may be configured to calculate the degree of connection for each load of the object through the power usage data for each load of the object, and the degree of connection for each load is such that the degree of connection for each load is high. Energy savings can be achieved by grouping loads together and creating a control schedule so that when the main load is turned off, the sub-loads are also turned off.

This linkage by load can be calculated through a correlation technique using the machine learning model of the machine learning module 23a using power usage data by load use collected in the form of data in the database 40 over a certain period of time.

For example, highly connected loads may include lighting and computers, computers and printers, and TVs and set-top boxes.

This linkage by load can be calculated after the machine learning module 23a checks whether simultaneous use is performed by timeline from the power usage data by load stored in the database 40 for a preset period, and more preferably by season. , by day of the week, by day, etc., it is possible to check simultaneous use and calculate it in the form of an index.

Accordingly, the calculated connection diagram for each load is additionally used as power load-related data, and the machine learning module 23a generates power usage prediction and load pattern data, and the schedule correction module 23 creates a control schedule based on this. Can be applied to.

Meanwhile, according to an example of the present invention, a plurality of photographing devices may be installed in the object, and the schedule correction module 23 may be configured to correct the control schedule based on photographing information generated from the photographing devices.

Of course, when creating a machine learning model of the machine learning module 23a, the shooting information is used as learning data to learn the machine learning model, and the shooting information is used as input data through the generated machine learning model to output the machine learning model. The schedule correction module 23 can be configured to correct the control schedule by referring to the data.

Such shooting information analyzes the state of the object in the object by the schedule correction module 23 and corrects the control schedule according to the object state. This object state analysis extracts behavioral feature points of the object in the shooting information, The sensory information experienced by the object is estimated according to the learned machine learning model.

Here, the perceived information may include, for example, the brightness of the lighting or the temperature of the air conditioner, and the behavioral feature points of the object for estimating such perceived information include, for example, when estimating the temperature of the air conditioner, the sweat estimated on the object's face area. This can be a behavior pattern such as fanning oneself with an object such as a fruit or a fan, or a behavior pattern such as curling up and shaking one's legs because one is cold.

Accordingly, the schedule correction module 23 can correct the control schedule based on the estimated sensory information, and outputs it through a machine learning model based on the case where the object in the object is below the set standard or when a specific behavior pattern is detected. The control schedule is corrected based on the control schedule results.

More specifically, the machine learning module 23a can be used to learn a machine learning model by further subdividing specific criteria for various items constituting perceived information. For example, learning a control schedule for the temperature of an air conditioner or heater. To this end, the machine learning model can be configured to further segment object classes and assign weight labels as well as result labels to enable more accurate object detection.

In other words, when the machine learning model performs machine learning based on the clothing worn by the object, it defines the object classes as thick long clothes, thin long clothes, medium clothes, and short clothes, and simply calculates the perceived temperature of the object. By setting a control schedule for heating and cooling temperatures uniformly without consideration, it is possible to resolve the inconvenience of the temperature environment felt by the object.

In addition, it can be trained by assigning weights to each object class. For example, thick long clothes can be set to 1, thin long clothes can be set to 0.7, medium clothes can be set to 0.4, and short clothes can be set to 0.

Here, in the case of the middle clothes, the ratio included in the shooting information can be calculated and the weight can be set differently by comparing the ratio with a preset ratio (for example, 80% of long clothes).

In addition, in addition to performing machine learning based on clothing, machine learning can be performed based on behavior as the object class. It is defined as the act of blowing on one's hand or fanning one's face.

When performing machine learning based on such behavior, it is possible to learn by assigning weights to each object class. For example, the behavior of shaking the whole body is 0.5, the behavior of rubbing hands or blowing on hands is 0.5, and the behavior of shaking the whole body is 0.5, and the behavior of shaking the whole body is 0.5. You can set shaking behavior to 0.3, body cowering behavior to 0.3, and fanning your face to 0.

In addition, the machine learning model can perform machine learning based on whether liquid presumed to be sweat is detected on the face or outside of the body in addition to behavior.

In addition, the machine learning model according to an example of the present invention can assign different weights to each object class according to the criteria for performing machine learning, which includes the result value judged based on clothing, the result value judged based on behavior, and sweat. The temperature environment felt by the object is estimated by varying the weight of the result values determined by the presence or absence of each in calculating the final result value.

Accordingly, it may be possible to perform more accurate machine learning for each object class.

In this way, the machine learning module 23a of the schedule correction module 23 estimates sensory information through analysis of shooting information, and corrects the control schedule through the estimated sensory information to create a schedule necessary for optimal operation of the object. and implementation, which leads to improving the efficiency of building energy management.

As described above, the present invention has been described with specific details such as specific components and limited embodiments and drawings, but this is only provided to facilitate a more general understanding of the present invention, and the present invention is not limited to the above embodiments. , those skilled in the art can make various modifications and variations from this description.

Therefore, the spirit of the present invention should not be limited to the described embodiments, and the scope of the patent claims described later as well as all things that are equivalent or equivalent to the scope of this patent claim shall fall within the scope of the spirit of the present invention. .

1: Real-time controlled mid- to long-distance wired and wireless convergence energy management system
10: Usage collection unit
11: electromagnetic contactor 12: current sensor
13: voltage sensor 14: status diagnosis unit
20: usage calculation unit
21: Calculation module 22: Schedule creation module
23: Schedule correction module 23a: Machine learning module
30: Operation management unit
40: database
50: Communication module
51: wireless communication department 52: wired communication department

Claims (5)

A usage collection unit 10 that receives in real time the power usage by load purpose of the energy-consuming object and stores the received power usage by load use in a database along with a real-time timeline;
a usage calculation unit 20 that analyzes the power usage for each load purpose stored in the database and calculates the amount of power consumed by the object;
An operation management unit 30 that controls the operation of the object by applying the power consumption calculated by the usage calculation unit 20 to the object in real time,
The usage calculation unit 20,
A calculation module 21 that classifies the power consumption by load purpose stored in the database by the stored timeline and divides it by season, date, or time to calculate the power consumption by load purpose of the object;
A schedule creation module 22 that generates a control schedule for controlling the operation of the object through the calculated power consumption for each load purpose of the object;
Receives the control schedule created through the schedule creation module 22, and collects environmental information such as real-time weather information, fine dust information, air information, sunrise time, sunset time, etc. through the Internet connected through wired or wireless communication means. After that, it includes a schedule correction module (23) applied to the control schedule,
The schedule correction module 23,
Applying the environmental information to the control schedule received from the schedule creation module 22 to generate a corrected correction schedule for operation control of the object,
The generated correction schedule is transmitted to the calculation module 21 and applied as a correction value in the process of calculating power usage for each load purpose of the object,
A plurality of photographing devices are installed in the object, and the schedule correction module 23 is configured to correct the control schedule based on the photographing information generated from the photographing devices,
The shooting information analyzes the state of the object in the object by the schedule correction module 23 and corrects the control schedule according to the object state. The object state analysis extracts the behavioral feature points of the object in the shooting information and uses learned machine learning. Estimating the sensory information experienced by the object according to the model,
Real-time controlled mid- to long-distance wired and wireless convergence energy management system.
delete According to paragraph 1,
The usage collection unit 10,
Remotely controlling the electromagnetic contactor (11) placed on the object,
The current value measured by the current sensor 12, which measures the current between the object and the electromagnetic contactor 11,
The voltage values measured by the voltage sensor 13, which measures the voltage between the magnetic contactor 11 and the power line, are received in real time and stored in a database,
In the process of receiving the current value and the voltage value, a status diagnosis unit 14 is further included for transmitting the corresponding information to a pre-stored manager terminal when an abnormal situation occurs,
Real-time controlled mid- to long-distance wired and wireless convergence energy management system.
According to paragraph 3,
The condition diagnosis unit 14,
Check whether there is an abnormality in the received voltage value, and at the same time check whether there is an abnormality in the received current value.
When the voltage value is abnormal, it is determined that a power supply problem has occurred and the corresponding information is transmitted to the previously stored manager terminal,
When the voltage value is normal and the current value is abnormal, the object is determined to be malfunctioning and the information is transmitted to a previously stored manager terminal.
Real-time controlled mid- to long-distance wired and wireless convergence energy management system.
According to claim 1 or 3,
A communication module 50 is further provided to transmit the operating status of the usage collection unit 10, the usage calculation unit 20, and the operation management unit 30 to a pre-stored administrator terminal or central control server in real time,
The communication module 50 is,
A wireless communication unit 51 consisting of either LoRa (Long Range) or Bluetooth, and
Including a wired communication unit 52 consisting of serial communication including RS-485,
Real-time controlled mid- to long-distance wired and wireless convergence energy management system.

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