KR102114895B1 - Building automatic control system and method for predicting aging time of facilities in buildings based on energy efficiency of facilities in buildings - Google Patents

Abstract

The present invention relates to an automatic building control system for predicting a degradation time of facilities in a building based on energy efficiency of the facilities in the building, which generates and outputs a signal for controlling efficiently management, operation state information, and set operation conditions in accordance with operation of each facility installed in the building through operation and monitors the temperature, humidity, pressure, carbon monoxide concentration, power consumption, gas consumption, and the like inside and outside the building to predict the degradation time of the facility through a machine learning algorithm using data for a facility operation time and energy consumption based on the energy efficiency of the facilities, and a method thereof. According to the present invention, to an existing automatic building control system, a function to predict energy efficiency lowering and proper facility replacement time due to degradation facility is added through a separate facility efficiency management system (FEMS) to fuse functions of a facility management system (FMS) and a building efficiency management system (BEMS), and an Internet of things (IoT) wireless connection device integration module is installed to use both a wired connection device and an IoT wireless connection device, thereby solving limits of the existing automatic building control system.

Description

Building automatic control system and method for predicting aging time of facilities in buildings based on energy efficiency of facilities in buildings}

The present invention relates to an automatic building control system and method, and more specifically, a signal for generating a signal for controlling efficiency by operating the operation of each facility installed in a building and operating state information and a set operating condition by arithmetic processing. A building that can predict the facility aging time based on facility energy efficiency through machine learning algorithms by outputting and monitoring the temperature, humidity, pressure, carbon monoxide, power, gas, etc. in and outside the building through machine learning algorithms. It relates to a building automatic control system and method for predicting the aging timing of facilities in a building based on the energy efficiency of my facilities.

The building energy management system is a system that automatically controls energy use by monitoring sensors in real-time by connecting sensors connected to energy-using devices in a building through a communication network and analyzing collected information. The building energy management system manages energy use, including activities such as air conditioning, electrical lighting, cooking, use of various home appliances and machinery, communication and ventilation, and air conditioning.

On the other hand, as the use of the building is diversified, various energy consumption items are being created. Building energy management systems use additional energy, such as ambient temperature, temperature in each room or zone, and the amount of movement of people. Analyze and predict more accurate energy consumption using information. The building energy management system is generally composed of various sensors, servers, sensor-server communication networks, and control facilities. In the building energy management system, information such as sensors used for analysis are transmitted to a central server for analysis, and control facilities are used to control energy use.

However, the building energy management system targets a plurality of buildings, or when a management object increases due to a large building, a large amount of data is generated, and it is difficult to perform efficient and real-time high-speed analysis or control. In particular, the building energy management system is expected to become more prominent in the future as the use of large amounts of sensor data increases due to the development of the Internet of Things (IOT) technology. In particular, the building energy management system has a limitation with such a centralized analysis system when it is necessary to detect and respond to a failure or an abnormal situation.

The current building automatic control system consists of heating and cooling equipment, lighting equipment, power equipment, etc. These building automatic control systems generally operate and stop the equipment to be controlled and monitor environmental information.

Existing automatic building control systems cannot directly manage efficient operation management through energy analysis and matters related to energy efficiency reduction due to aging of the equipment to be monitored for control. For energy management, a separate building energy management system, BEMS (Building Energy) Management System) must be additionally installed, and a separate FMS (Facility Management System) must be additionally installed for facility management, but nevertheless, it is possible to predict the energy efficiency drop due to the aging of existing facilities and the appropriate time for facility replacement. There were no devices or systems and methods.

In addition, for energy management, more energy information and environmental information are needed than before. However, if only a wired connection device is used to obtain such information, there is a problem in that installation cost is high.

Therefore, in order to construct such a system, a separate system must be additionally installed in addition to the building automatic control system. In such a case, there is a problem in that the cost increases and the difficulty in deploying professional personnel greatly affects.

Prior Literature 1: Republic of Korea Patent Publication No. 10-2009-0066107 (published on June 23, 2009)-Building energy management system and control method thereof Prior Literature 2: Republic of Korea Patent Publication No. 10-2017-0143354 (released on December 29, 2017)-Building energy management system and method Prior Literature 3: Republic of Korea Patent Publication No. 10-2015-0043170 (published on April 22, 2015)-Energy management system and method Prior Literature 4: Republic of Korea Patent Registration No. 10-1659361 (announced on September 23, 2016)-IoT-based remote automatic control system using data correction

The object of the present invention is to solve the problems as described above, and generates a signal for controlling efficiency by operation of each facility installed in a building, operation status information, and a signal for controlling a set operation condition by arithmetic processing. Outputs, monitors temperature, humidity, pressure, carbon monoxide, power and gas in and out of the building, and can estimate the equipment aging time based on the facility energy efficiency through machine learning algorithms of equipment operation time and energy consumption data. It is to provide an automatic building control system and method for predicting the aging timing of facilities in a building based on energy efficiency of facilities in a building.

In addition, another object of the present invention is energy efficiency due to facility aging through a separate FEMS (Facility Efficiency Managment System) capable of integrating FMS (Facility Managment System) and BEMS (Building Efficiency Managment System) functions into an existing building automatic control system. It adds the ability to predict the appropriate time for deterioration and equipment replacement, and installs the integrated module of the IOT wireless connection device that enables the use of wired connection devices as well as wireless connection devices for IOT, thereby solving the limitations of the existing building automatic control system. It is to provide a building automatic control system and method for predicting the aging timing of facilities in a building based on energy efficiency of facilities in a building.

In order to achieve the above object, the present invention comprises an input device, an output device, a computing device, and an uninterruptible power supply, and monitors environmental information and energy information in a building, and commands and statuses of control monitoring equipment , Central control unit (CCMS) for receiving the data of the abnormal alarm and displaying it through a monitor that is an output device; Environment information including temperature, humidity, and pressure, and energy including gas volume, temperature, humidity, and pressure of the control equipment in buildings including air conditioning circulation pump, water supply pump, cooling water pump, supply / exhaust fan, air conditioner, boiler, and freezer Monitors information, outputs a command to operate the control target equipment according to a predetermined set value, collects status information and an abnormality alarm through a wired connection method or a wireless communication method, transmits it to the central control device, and A remote control device that performs a command received from the central control device; A plurality of environmental information sensors for sensing environmental information in a building connected to the remote control device through a wired connection method, and a wired connection device which is a plurality of energy information measuring devices; And a plurality of environmental information sensors for sensing environmental information in a building communicating with the remote control device through a wireless communication method and a wireless communication method device that is a plurality of energy information measuring devices. It provides an automatic building control system for predicting the aging timing of facilities in a building based on efficiency.

Here, the remote control device includes a BAS control unit for automatic building control, and environmental information including temperature, humidity and pressure in the building collected from the BAS control unit, energy information including power amount and gas amount, and the state of the control target facility. Future operation of the facility based on the energy efficiency of the facility in the building that can manage information and abnormal alarms, and the energy efficiency of the energy management and control monitoring facilities in the building and facility management. Environmental information measuring device, energy information measuring device and control monitoring object connected by wireless communication method using any one of the facility energy efficiency management unit (FEMS) and Z-wave, ZigBee, and BLE to predict and manage equipment aging by predicting time Including the IOT wireless device integration module that collects environmental information and energy information through wireless communication with the IOT wireless sensor, IOT wireless input / output device, and IOT wireless measuring device through wireless communication. It is characterized by being configured.

In addition, the BAS control unit, the communication unit communicating with the BAS control unit and the central control unit (CCMS), and the information of the environmental information measuring device and control monitoring target equipment provided through the signal input / output unit and the input from the central control unit. A control operation unit that generates an output signal by comparing with a set value and receives the environmental information including the operation status of the sensor, instrument or facility, and an abnormality alarm value through the wired connection type device and the wireless communication type device, or the control operation part It is characterized in that it comprises a signal input / output that controls the facilities (facilities) in a building by directly sending (outputting) operation commands coming out.

In addition, the information of the environment information measuring device, energy information measuring device and control monitoring equipment connected by a wired connection type device or a wireless communication type device is received from the signal input / output unit, and inputted through the signal input / output unit from the control operation unit. Converts the processed information into data, compares it with the BAS control program, processes it, and outputs a preset command to the control monitoring equipment as a signal according to the processed data. It is stored in, it is characterized in that it is also transmitted to the central control device.

And the facility energy efficiency management unit (FEMS) reads the data stored in the data storage unit) through the consumption status analysis unit that analyzes the energy consumption status of the control target equipment through a predetermined consumption status algorithm and the efficiency analysis algorithm. The efficiency analysis unit analyzes the current operation efficiency of each equipment based on the operation information and energy consumption of the equipment to be monitored, and the consumption status analysis unit and the efficiency analysis unit are converted into DATA and stored in the data storage unit. A machine learning unit that predicts the future operational time of the control monitoring target facility using a machine learning algorithm using the operation time information of the control monitoring target facility and power consumption data per hour by using the machine learning algorithm, and the data storage unit that determines whether the control monitoring target facility operates or not. It is characterized in that it is provided by the operation pattern analysis unit 234 for the monitoring device of the central control device through the multi-graph, numerical value, history storage of the operation pattern of each control monitoring target equipment by time zone.

And in order to achieve the above object, the present invention comprises the steps of storing the collected information and the measured value (power amount) in the data storage unit when the control monitoring target facility in the building is started or stopped; The data stored in the data storage unit is analyzed through the efficiency analysis unit, the efficiency of energy consumption per hour during initial operation, the energy consumption per hour is selected during initial operation, and stored in the data storage unit; In the efficiency analysis unit, analyzing energy consumption efficiency per hour per operation date; As a result of comparing the current efficiency with the preset efficiency 1, if the analyzed current efficiency is less than or equal to the preset efficiency 1, the set efficiency 1 or less is displayed through the monitor, which is an output device of the central control device, and the analysis is performed. If the current efficiency is greater than or equal to the preset efficiency, a machine learning algorithm is applied through the machine learning unit to the data stored in the data storage unit until the previous day to predict the efficiency according to additional uptime in the future. Predicting a future expected date falling below the set efficiency 2, which is a relatively lower efficiency than the set efficiency 1; And displaying a predicted future date falling below the set efficiency of 2 on the monitor screen of the central control device; predicting the aging time of the facilities in the building based on the energy efficiency of the facilities in the building. For building automatic control method.

Here, when the primary management point is reached, it is characterized in that the information on the corresponding facility is transmitted through the smart phone or email of the central control device manager.

And the step of displaying the expected future date falling below the set efficiency of 2 on the monitor screen of the central control unit, the current efficiency, the set efficiency of the equipment for which the expected efficiency falls below the set efficiency of 2 on the monitor screen of the central control unit 1 It is characterized in that it further displays the expected date of falling below 2 and the set efficiency, energy consumption per initial hour, energy consumption per hour of the current day, and cumulative operating time up to the current day.

The present invention has the following effects.

First, through the automatic building control system for predicting the aging time of facilities in a building based on the energy efficiency of the facilities in the building, it is possible to perform integrated management and energy management of the facilities in the building with one system.

Second, a system using the automatic building control system for predicting the aging time of facilities in a building based on the energy efficiency of the facilities in the building. It is possible to predict when to replace equipment.

Third, it is possible to directly show the operation time, maintenance time forecast, replacement time forecast, and maintenance budget management information of the facilities in the building on a monitor screen of the facility manager.

Fourth, information such as the energy consumption per hour of the facilities in the building, the energy consumption per hour per cumulative operating time, the current hourly energy consumption ratio compared to the initial hourly energy consumption, and energy consumption analysis can be displayed on the monitor screen.

Fifth, energy efficiency, ie, the degree of aging, can be predicted for the facilities in the building as future operating time, so the budget for future building facility management can be prepared.

Sixth, it is a system of a building automatic control system for predicting the aging time of facilities in a building based on the energy efficiency of the facilities in the building, so the facility manager can easily obtain the above information, enabling effective operation of the facilities in the building. Therefore, it is possible to reduce the management cost for the facilities in the building.

Seventh, by installing the IOT wireless device integrated module, it is possible to collect energy information and environmental information in a wireless communication method, so installation is simpler and the installation cost can be reduced.

1 is a block diagram for explaining a building automatic control system for predicting aging time of facilities in a building based on energy efficiency of facilities in a building according to the present invention.
2 is a flow chart for explaining a building automatic control method for predicting the aging timing of facilities in a building based on energy efficiency of facilities in a building according to the present invention.
3 is a graph illustrating a cost function graph and a slope at an arbitrary W value in a building automatic control system for predicting aging time of facilities in a building based on energy efficiency of facilities in a building according to the present invention .

If described in detail by the accompanying drawings, preferred embodiments of the present invention.

In addition, the terms used in the present invention have been selected as general terms that are currently widely used as much as possible, but in certain cases, the terms are arbitrarily selected by the applicant, and in this case, the meaning is described in detail in the description of the applicable invention. It is intended to clarify that the present invention should be understood as a meaning of a term rather than a name of. In addition, in describing the embodiments, descriptions of technical contents well known in the technical field to which the present invention pertains and which are not directly related to the present invention will be omitted. This is to more clearly communicate the subject matter of the present invention by omitting unnecessary description.

Basically, in most buildings, when designing a building, the type of installation and installation location are determined according to the purpose of the building, and the location of the central control unit and the number of remote control panels are determined accordingly.

An intelligent building that introduces an automatic building control system is generally connected to a remote control panel using a dedicated communication network in order to control and monitor facilities and environmental information in the building from the central monitoring panel.

This automatic building control system monitors the building's temperature, humidity, pressure, etc. (hereinafter referred to as “environmental information”) and the amount of electricity and gas (hereinafter referred to as “energy information”), and sets the target equipment for control monitoring in advance. It outputs the command to drive by and also collects status information and abnormal alarms.

In the present invention, the collected state information and abnormal alarm information data are separately stored in a data storage unit, and a facility efficiency management system (FEMS) for managing facility efficiency is mounted on a master controller (remote control device) to build Building automatic control system that can manage the energy efficiency of facilities subject to energy management and control monitoring, and can predict facility operation aging by predicting future operating time for facilities based on facility energy efficiency in buildings that can manage facilities Implement

Here, efficiency is

Efficiency = (Energy consumption per hour at the time of initial operation / Energy consumption per hour at the present time) * 100%, efficiency at initial operation is expressed as 100%.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram for explaining a building automatic control system for predicting aging time of facilities in a building based on energy efficiency of facilities in a building according to the present invention.

Building automatic control system for predicting the aging timing of facilities in a building based on energy efficiency of facilities in a building according to the present invention, as shown in FIG. 1, Central Control and Monitoring System (CCMS) 100 , Remote control device 200, a plurality of wired connection-type devices 300 and a plurality of wireless communication-type devices 400.

Here, the central control device (CCMS) 100 is composed of an input device such as a computer or a server (keyboard, mouse, etc.), an output device (monitor, printer, etc.), a computing device (CPU, etc.), an uninterruptible power supply, and the like. The environment information (temperature, humidity, pressure, etc.) and energy information (power, gas, etc.) in the building are monitored through the control device 200. Through the remote control device 200, the operation command and status of the control monitoring target equipment, The data of the abnormality alarm is received and displayed through a monitor that is an output device. Here, the target equipment for control monitoring may be a cooling / heating circulation pump, a water supply pump, a cooling water pump, a supply / exhaust fan, an air conditioner, a boiler, a freezer, etc., and there is no need to specifically limit the equipment in the building.

The remote control device 200 collects the reception information of the environmental information measuring device and the control monitoring target equipment through a wired connection method or a wireless communication method, transmits it to the central control device 100, and receives commands received from the central control device 100. And transmits the collected various information to the central control device 100.

To this end, the remote control device 200 includes a BAS (Building Automation System) control unit 210, a data storage unit 220, a facility energy efficiency management unit 230, and an IOT wireless device integration module 240.

First, the BAS control unit 210 performs an overall function for automatic building control, and is composed of a communication unit 211, a control operation unit 212, and a signal input / output unit 213.

The communication unit 211 communicates with the BAS control unit 210 and the central control unit (CCMS) 100 to provide setting values pre-entered by an administrator (user) or environmental information by an administrator (user) request, and is not illustrated. Although not communicated with other remote control devices in a preset manner, it is possible to share environmental information between the remote control devices, a state value of a control monitoring target facility, or an abnormality alarm value.

The control operation unit 212 compares the information of the environmental information measuring device and the control target equipment provided through the signal input / output unit 213 with the set value input from the central control device 100 to generate an output signal. do. At this time, the program logic for the comparison operation is calculated by one or more elements such as a comparison statement, conditional statement, PI, PID, etc. according to the field conditions.

The signal input / output unit 213 receives environmental information such as an operation state of an sensor or a measuring instrument or facility, an abnormality alarm value, or directly transmits (outputs) an operation command issued through the control operation unit 212 to generate (in a building) Facilities).

At this time, the information of the environmental information measuring device, energy information measuring device and control monitoring equipment connected to the wired connection type device 300 is received from the signal input / output unit 213, and the signal input / output unit is controlled by the control operation unit 212. The information input through (213) is converted to data and compared with the BAS control program for processing. According to the processed data, a preset command is output as a signal to the control monitoring target facility, and each input and output information is stored (stored) in the DATA storage unit 220 through the communication unit 211. Also, the corresponding data is transmitted to the central control device 100.

The data storage unit 220 includes environmental information such as temperature, humidity and pressure in the building collected from the BAS control unit 210, energy information including power amount, gas amount, etc., and status information and abnormality alarms of control target equipment, wireless The environment information measuring device connected to the communication method device 400, energy information measuring device and control monitoring equipment are collected through wireless communication, and environmental information and energy information are collected in a wireless communication method and stored in the data storage unit 220.

The facility energy efficiency management unit (FEMS) 230 can manage the energy efficiency of the facilities subject to energy management and control monitoring in the building. Make predictions to predict when equipment will age.

To this end, the facility energy efficiency management unit (FEMS) 230 may include a consumption status analysis unit 231, an efficiency analysis unit 232, a machine learning unit 233, and an operation pattern analysis unit 234.

The consumption status analysis unit 231 reads the data stored in the DATA storage unit 220 and analyzes the energy consumption status of the control monitoring target equipment through a preset consumption status algorithm. The analyzed consumption status manages trend and history in the monitoring device.

The efficiency analysis unit 232 analyzes the current operation efficiency of each equipment based on the operation information and energy consumption information of the control target equipment through an efficiency analysis algorithm. The analyzed operation efficiency information is displayed on the monitoring device of the central control device 100.

The machine learning unit 233 is machined by the consumption status analysis unit 231 and the efficiency analysis unit 232 to machine operation time information and power consumption data per hour of the control monitoring target equipment stored in the data storage unit 220 Using the running algorithm, predict the future operational time of the equipment to be controlled and monitored. And the predicted driving time is displayed on the monitoring device of the central control device (100). At this time, it is possible to predict from the time the system starts to operate, but the more data stored, the more accurate the predictable future operating time is.

The operation pattern analysis unit 234 receives information on whether a control monitoring target facility operates or not through the data storage unit 220, and stores the operation patterns of each control monitoring target facility through multi graphs, numerical values, and history storage by time. It is displayed on the monitoring device of the central control device 100.

The IOT wireless device integration module 240 uses the communication method of Z-wave, ZigBee, or BLE to display the information of the environmental information measuring device, energy information measuring device, and control monitoring equipment connected to the wireless communication device 400. Environmental information and energy information are collected in a wireless communication method through wireless communication with an IOT wireless sensor, an IOT wireless input / output device, and an IOT wireless instrument and stored in a data storage unit 220.

The plurality of wired connection-type devices 300 communicate in a wired manner with a plurality of environmental information sensors 1 to n, a plurality of energy information measuring instruments 1 to n, and a signal input / output unit 211 of the BAS control unit 210, In the plurality of wireless communication device 400, a plurality of environmental information sensors 1 to n and a plurality of energy information measuring devices 1 to n communicate with the IOT wireless device integration module 240 in a wireless manner.

According to this configuration, the building automatic control system of the present invention receives the operating state values of the control monitoring target equipment and environmental information inside and outside the building from the remote control device 200, and receives the information and operating conditions received through the communication unit 211. By comparison, the operation command value of the control monitoring target equipment is input, and the control value is transmitted from the central control device 100 through the signal input / output unit 213.

And the commands sent from the central control device 100 share each information through the communication unit 211 of the remote control device 200 of the BAS control unit 210, and by a logic algorithm already determined through the control operation unit 212. Execute the control command to the control monitoring target equipment wired to the signal input / output unit 213, or check the environmental information.

The information generated by the BAS control unit 210 is stored in the DATA storage unit 220, and the information required by the BAS control unit 210 is read (withdrawn) from the DATA storage unit 220 for use.

The Internet of Things (IOT) wireless device integration module 240 collects energy information and environmental information in a wireless communication method and stores it in a data storage unit 220.

And the facility energy efficiency management unit (FEMS) 230 loads the data stored in the data storage unit 220, analyzes the energy consumption status of the control monitoring target equipment, analyzes the current operation efficiency, predicts the future operating time, and predicts the operation pattern by time zone. The multi-graph, numerical value, and history are stored and the generated information is displayed on the monitoring device, which is an output device connected to the central control device 100.

Accordingly, the present invention can predict the energy efficiency reduction due to the aging of the facility and the appropriate time to replace the facility.

2 is a flow chart for explaining a building automatic control method for predicting the aging timing of facilities in a building based on energy efficiency of facilities in a building according to the present invention.

The building automatic control method for predicting the aging timing of facilities in a building based on the energy efficiency of facilities in a building according to the invention is as shown in FIG. , The measured value (power amount) is stored in the data storage unit 220 (S100).

The data stored in the data storage unit 220 is analyzed for efficiency of energy consumption per hour during initial operation through the efficiency analysis unit 232 (S110).

Accordingly, the energy consumption per hour is selected during the initial operation, and is stored in the data storage unit 220 (S120).

In addition, the efficiency analysis unit 232 analyzes the energy consumption efficiency per hour per operation date (S130).

As a result of the analysis, the current efficiency is compared with the preset efficiency 1 (S140).

Here, the setting efficiency 1 is the efficiency at which the energy efficiency is lowered and the manager has to reach the first management time point, for example, it can be set at an efficiency of 95%.

Of course, this can be set differently depending on the facilities in the building.

For the comparison, the consumption status analysis unit 231 described above uses data stored in the DATA storage unit 220 to analyze the energy consumption status of the control monitoring target equipment through a predetermined consumption status algorithm.

If the comparison result (S140) efficiency is less than or equal to the preset efficiency, the efficiency is expressed through a monitor, which is an output device of the central control device.

That is, when the primary management point is reached, information on the corresponding facility is made to be known by the manager, and at this time, the monitor can be transmitted through the manager's smartphone or email (S150).

On the other hand, if the comparison result (S140) efficiency is greater than or equal to the preset efficiency, a machine learning algorithm is applied through the machine learning unit 233 to the data stored in the data storage unit 220 until the previous day to improve the efficiency according to additional uptime in the future. Prediction (S160).

Also, accordingly, the machine learning unit 233 predicts the expected future date when the expected efficiency falls below the preset efficiency 2 (S170). Here, the setting efficiency 2 is an efficiency in which the energy efficiency is significantly lowered and the manager needs to replace the equipment, for example, 85% or less. Of course, this setting efficiency 2 can also be set differently depending on the facilities in the building.

In addition, the predicted future date prediction information in which the expected efficiency in the machine learning unit 233 falls below the set efficiency of 2 is the current efficiency for the equipment whose expected efficiency falls below the set efficiency of 2 on the monitor screen of the central control device 100, It is displayed including the expected future date, the energy consumption per initial hour, the energy consumption per hour of the current day, and the cumulative operating time up to the current day (S180).

The automatic building control method for predicting the aging time of facilities in a building based on the energy efficiency of facilities in a building according to the present invention will be described as an example.

As described above, the equipment subject to control monitoring includes facilities such as air conditioning circulation pumps, water supply pumps, cooling water pumps, supply / exhaust fans, air conditioners, boilers, and refrigerators.

For any circulating pump 1, the information collected from the environmental information measuring device during the system operation time is converted into data by the consumption status analysis unit 231 and the efficiency analysis unit 232, and stored in the data storage unit 220 When the operation time / cumulative operation time / power consumption per hour of any circulating pump 1 was as shown in [Table 1], (S100)

Here, xi: the cumulative uptime of day i after operation (unit: h), and yi: the amount of power consumed per day (hour: i) after day of operation (unit: S110, S120, S130).

Meanwhile, a method of predicting the future operational time of the control monitoring target equipment in the machine learning unit 233 will be described (S140 to S180).

Arbitrary circulation pump 1 exhibits the characteristic that the power consumption per hour increases as the operating time increases.

y = Wx + b i.e.

The equation H (x) = Wx + b can be set to Hypothesis.

If the equation of H (x) = Wx + b is graphed, it can be expressed as a straight line, and the shape of the straight line appears differently depending on W and b, and finding a straight line that best represents the actual data is the machine to be used in the present invention. Linear regression algorithm during running.

Then, it is necessary to define how well a certain line represents the current data, and how well the current W, b value represents machine learning data by using the Cost function in linear regression during machine learning. To weigh.

The definition of the cost function in linear regression during machine learning is as follows.

Finding the W, b value of which the result of this function is the lowest is the core of the linear regression algorithm during machine learning. In general, the lowest value is searched using the gradient descent algorithm.

For convenience of description, if b value is fixed to 0 and Cost (W, 0) is drawn according to the change of W value, it has a slope shape in the Cost (W, 0) function graph shown in FIG. 3 and an arbitrary W value.

At this time, when there is an arbitrary W value, the slope of the point where the corresponding W value is located in the Cost function is determined, and it is determined whether to move while increasing W or decreasing while decreasing W.

Gradient Descent is a method of comparing errors in a graph by using the slope of the differential and moving in the smallest direction. It is represented by a graph for W, and if a derivative at any W point is obtained, the graph at that point You can see the slope of And, when the value of the cost (W) function is minimum, the slope is 0. Therefore, the machine learning unit needs to find the point where the derivative value is 0.

The algorithm of Gradient Descent is as shown in Equation 2.

① W: As the first W, it is the constant initialized first. It will be gradually updated to W which minimizes the cost (W) using the gradient descent method.

②α: Learning_rate, a constant that controls the learning rate.

: cost(W)를 W로 편미분한 값이다.③

: This is a partial derivative of cost (W) to W.

It can be seen from Equation 2 above that W is changed to update to the optimal W.

And if the above example data is machine-learned using the gradient descent algorithm, W and b values that minimize the cost (W) function can be found, and W = 0.0637 and b = 9,982.9, respectively.

Substituting the hypothesis equation set initially, H (x) = 0.0637 * x + 9982.9.

For example, if the facility manager wants to know the primary time when the circulation pump 1 reaches the time when the power consumption per hour increases by 10% or more (11000 Wh) compared to the initial hourly power consumption (10000 Wh).

It is predictable by substituting the above equation, and substituting as follows.

11000 = 0.0637xi + 9982.9

xi = (11000-9982.9) / 0.0637

   = 15967.03

Assuming day 368 is the current day,

15967 hours-1769 hours (cumulative operating time until Day 367) = 14,198 hours, which is expected to consume 11000 Wh after 14,198 hours based on the current day.

If the circulation pump 1 continues to operate after Day 368 with the operation method up to Day 367, it is possible to predict how many days after 14,198 hours will be machine-learned by accumulating uptime data by day until Day 367.

Table 2 shows the operation time / cumulative operation time of each circulation pump 1

xi: it is the first day of operation after operation,

yi: The cumulative uptime of day i after operation (unit: h).

Here, the optional circulation pump 1 exhibits an increase in operating time due to an increase in operating primary,

y = Wx + b i.e.

The equation H (x) = Wx + b can be set to Hypothesis.

By machine learning the above data using the gradient descent algorithm, W and b values that minimize the cost (W) function can be found.

W = 4.8160 and b = -0.7, respectively.

Substituting the hypothesis equation that we set earlier,

H (x) = 4.816 * x-0.7.

To predict the number of days that 15967 hours will occur, substituting them into the above equation is as follows.

15967 = 4.816 * xi-0.7

xi = (15967 + 0.7) / 4.816

   = 3315.6

 To find out how many days from the current date on day 3315.6:

 Day 3315.6-Day 367 = Day 2,948.6. If converted based on 1 year, 365 days, 1 month and 30 days, it can be represented after 8 years 28.6 days.

 As can be seen from the example of the circulating pump 1 above, the longer the operating time is, the more data stored can be machine-learned, so the more accurate prediction value can be found (i.e., the target time (replacement time, If there is not much time left for repairs, etc., the collected data is more than the remaining period, so you can find a more accurate forecasting point.)

The machine-learning algorithm of the present invention includes not only a change in the efficiency of the circulation pump (change in power consumption per hour according to the accumulated operating time (aging)), but also a building such as a water supply pump, a cooling water pump, a supply / exhaust fan, an air conditioner, a boiler, and a freezer. The advantage of providing useful information such as energy efficiency, equipment replacement time, and budget management for facility managers to manage equipment by predicting changes in the efficiency of mechanical facilities (change in energy consumption per hour according to cumulative operating time (aging)) have.

Although the present invention has been described as an example as described above, the present invention is not necessarily limited to these examples, and may be variously modified without departing from the technical spirit of the present invention. Therefore, the examples disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these examples. The scope of protection of the present invention should be interpreted by the following claims, and all technical spirits within the equivalent range should be interpreted as being included in the scope of the present invention.

100: Central control unit (CCMS) 200: Remote control unit
210: BAS control unit 211: Communication unit
212: control operation unit 213: signal input / output unit
220: DATA storage unit 230: Facility energy efficiency management unit
231: consumption status analysis unit 232: efficiency analysis unit
233: machine learning unit 234: operation pattern analysis unit
240: IOT wireless device integration module
300: wired connection type device 400: wireless communication type device

Claims (8)

It consists of an input device, an output device, a calculation device, and an uninterruptible power supply. It monitors environmental information and energy information in a building, and receives and outputs the data of the operation command, status, and abnormality alarms of the control target equipment under control. A central control device (CCMS) 100 displayed through a monitor that is a device;
Environment information including temperature, humidity, and pressure, and energy including gas volume, temperature, humidity, and pressure of the control equipment in buildings including air conditioning circulation pump, water supply pump, cooling water pump, supply / exhaust fan, air conditioner, boiler, and freezer Monitors information, outputs a command to operate the control target equipment according to a preset set value, collects status information and an abnormality alarm by wired connection method or wireless communication method, and transmits it to the central control device 100 And, the remote control device 200 for performing a command received from the central control device 100;
A plurality of environmental information sensors for sensing environmental information in a building connected to the remote control device 200 through a wired connection method, and a wired connection device 300 which is a plurality of energy information measuring devices; And
It comprises a plurality of environmental information sensor for sensing the environmental information in the building that communicates with the remote control device 200 in a wireless communication method, and a wireless communication method device 400 which is a plurality of energy information measuring devices.
The remote control device 200,
BAS control unit 210 for automatic building control,
A data storage unit 220 that stores environmental information including temperature, humidity, and pressure in the building collected from the BAS control unit 210, energy information including the amount of electricity and gas, and status information and abnormality alarms of the control target equipment. Wow,
The facility energy efficiency management department that can manage the energy efficiency of the facilities for the energy management and control monitoring in the building and predict the future operating time for the facilities based on the facility energy efficiency in the building that can manage the facilities. (FEMS) 230 and
IOT wireless sensor, IOT wireless input / output device for information of environmental information measuring device, energy information measuring device and control monitoring equipment connected to wireless communication device 400 using one of Z-wave, ZigBee, BLE , It comprises an IOT wireless device integration module 240 that collects environmental information and energy information through wireless communication with an IOT wireless instrument and stores it in the DATA storage unit 220,
The facility energy efficiency management unit (FEMS) 230,
A consumption status analysis unit 231 that reads the data stored in the DATA storage unit 220 and analyzes the energy consumption status of the control target equipment through a predetermined consumption status algorithm;
The efficiency analysis unit 232 analyzes the current operation efficiency of each equipment based on the operation information and energy consumption information of the control monitoring target equipment through an efficiency analysis algorithm,
The consumption status analysis unit 231 and the efficiency analysis unit 232 are converted into DATA and stored in the DATA storage unit 220, the operating time information and the power consumption per hour DATA of the control monitoring equipment are utilized by using a machine learning algorithm. Machine learning unit (233) for predicting the future operating time of the control target equipment and
Monitoring device of the central control device (100) through multi-graph, numerical, and historical storage of the operation pattern of each control-monitoring device for each time zone by receiving the presence or absence of operation of the control-monitoring device from the data storage unit (220) Building automatic control system for predicting the aging time of equipment in a building based on the energy efficiency of the equipment in the building, characterized in that it comprises a driving pattern analysis unit 234.
delete The method according to claim 1,
The BAS control unit 210,
A communication unit 211 communicating with the BAS control unit 210 and the central control unit (CCMS) 100;
A control operation unit 212 that generates an output signal by comparing and calculating the information of the environmental information measuring device and the control target equipment provided through the signal input / output unit 213 with the set value input from the central control device 100 And
Through the wired connection-type device 300 and the wireless communication-type device 400, environmental information including the operation state of the sensor, instrument, or facility, and an abnormality alarm value is received or an operation command issued through the control operation unit 212 is received. Predicting the aging timing of facilities in a building based on the energy efficiency of the facilities in the building, characterized in that it comprises a signal input / output unit 213 that directly controls the facilities (facilities) in the building by sending (output) it directly. For building automatic control system.
The method according to claim 3,
The information of the environmental information measuring device, energy information measuring device and control monitoring target equipment connected to the wired connection device 300 or the wireless communication device 400 is input from the signal input / output unit 213, and the control operation unit In (212), the information inputted through the signal input / output unit 213 is converted into data, compared with a BAS control program, processed, and outputs a preset command to a control monitoring target device as a signal according to the processed data. , Each input and output information is stored in the DATA storage unit 220 through the communication unit 211, and is also transmitted to the central control device 100. Building automatic control system to predict the aging time of my equipment.
delete Storing the collected information and measurement values (power consumption) in the data storage unit 220 when the control monitoring target facility in the building is started or stopped (S100);
The data stored in the data storage unit 220 is analyzed for efficiency of energy consumption per hour during initial operation through the efficiency analysis unit 232 (S110), and energy consumption per hour during initial operation is selected, and the data storage unit 220 Stored in step (S120);
The efficiency analysis unit 232 analyzes the energy consumption efficiency per hour per operation date (S130);
As a result of comparing the current efficiency with the preset efficiency 1 (S140), if the analyzed current efficiency is less than or equal to the preset efficiency 1, the efficiency is less than 1 through the monitor, which is the output device of the central control device 100. (S150), and when the analyzed current efficiency is greater than or equal to the preset efficiency, a machine learning algorithm is applied through the machine learning unit 233 to the data stored in the data storage unit 220 until the previous day. Estimating the efficiency according to the additional uptime in the future (S160), predicting the expected future date when the predicted efficiency falls below the set efficiency 2, which is a relatively lower efficiency than the set efficiency 1 (S170); And
In the building efficiency based on the energy efficiency of the facility in the building characterized in that it comprises a; (S180) for displaying the expected future date falling below the set efficiency 2 on the monitor screen of the central control device 100; Automatic building control method for predicting the aging time of a person.
The method according to claim 6,
If the analyzed current efficiency is less than or equal to the preset setting efficiency, the step of displaying the setting efficiency 1 or less through the monitor that is the output device of the central control device 100 (S150), the administrator can know information about the corresponding facility. Automatic building control method for predicting the aging time of equipment in a building based on the energy efficiency of the equipment in the building, characterized in that it is transmitted through the smart phone or email of the central control device manager.
The method according to claim 6,
In the step (S180) of displaying the expected future date falling below the set efficiency of 2 on the monitor screen of the central control apparatus 100,
The current efficiency of the equipment whose expected efficiency falls below the set efficiency of 2 or less on the monitor screen of the central control device 100, the expected future date when the set efficiency falls below the set efficiency of 1 and the set efficiency of 2, energy consumption per initial hour, energy per hour of the current day Automatic building control method for predicting aging time of facilities in buildings based on energy efficiency of facilities in buildings characterized by being displayed by including consumption and cumulative operation time up to the current day.

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