WO2018105784A1

WO2018105784A1 - Home energy management system using a plurality of sensors

Info

Publication number: WO2018105784A1
Application number: PCT/KR2016/014370
Authority: WO
Inventors: 진병진; 임근석; 나종현
Original assignee: (주)온테스트
Priority date: 2016-12-08
Filing date: 2016-12-08
Publication date: 2018-06-14

Abstract

The present invention relates to a home energy management system using a plurality of sensors, and, more specifically, is to provide a home energy management system using a plurality of sensors which can efficiently reduce energy considering various spaces or space environments inside a home, the wall body temperature of a building, and the like by receiving the wall body temperature of the inner wall of the building together with an adjustment data of a package air conditioner covering a plurality of indoor spaces and a sensing data with respect to the indoor spaces via a relay through a repeater, calculating a control command through a big data analysis and a machine learning analysis of the sensing data and the adjustment data comprising the wall body temperature by a machine learning engine, relaying the calculated control command through the repeater, and controlling the package air conditioner.

Description

Home Energy Management System Using Multiple Sensors

The present invention relates to a home energy management system using a plurality of sensors, and more particularly, using a plurality of sensors that can efficiently save energy in consideration of not only various spaces and space environments but also wall temperatures in the home. Home energy management system.

Recently, as the Smart Grid has attracted attention as part of the Green Energy business, the importance of the Home Energy Management System (HEMS) for the Smart Grid is increasing.

The home energy management system is a device for efficiently managing the energy consumption of home appliances using a smart grid, which includes general home appliances (refrigerators, washing machines, etc.), devices using renewable energy (solar, wind, etc.), and batteries. And various devices such as fuel cells.

Currently, most residential energy management systems are implemented in home-controlled home servers based on home network systems. Most energy consumption information is provided to users on a daily / weekly / monthly basis through IHD (In-Home Display). Based on this information, the government encourages voluntary energy savings through energy consumption awareness. Accordingly, the government is making policy efforts to disseminate green homes through various incentives and regulations to encourage energy saving and green energy use.

Recently, a home energy management system (HEMS) has been developed that includes energy consumption monitoring and analysis on existing home servers, and mainly supplies new apartments, and enables remote access through mobile technology. It provides control functions linked with network technology.

Such a home energy management system provides an energy consumption information to a user in a specific form, thereby inducing the user to voluntarily conserve energy by identifying the actual energy consumption in the home.

Meanwhile, in response to risks such as international and continuous increase in energy prices and environmental destruction, the introduction of various renewable energy such as solar, solar, geothermal and wind power is being actively considered. In particular, in the case of photovoltaic power generation, it is increasingly applied to buildings in the form of BIPV (Building Integrated Photovoltaic System).

However, these existing home energy management systems only provide simple energy consumption, and there is no information on patterns and devices that use energy consumption inefficiently, and voluntary energy saving causes difficulty in maintaining user participation. . In addition, for efficient BIPV control, it is optimized for active energy equipment such as optimal energy charge / discharge control and light collector control, common energy related facility control such as electric blinder, horizontal shade screen, etc. by considering energy consumption status information and weather information together. Central control is required.

On the other hand, the homes of the countries of the Middle East are usually in the form of detached houses of two or three stories, and operate a plurality of air conditioners.

In the Middle East buildings, a number of air conditioners are installed to efficiently operate the air conditioners. These air conditioners are controlled by zones, that is, by floors or sections, or by attaching temperature controllers to individual air conditioners. The operation of the air conditioner was controlled according to the temperature of the installed space.

However, this conventional method operates in accordance with the temperature regardless of whether there is a person or not, if there are several spaces (room 1, room 2, living room, etc.) in the building in a manner controlled by temperature. Therefore, there is a problem that the energy is wasted because the air conditioner is operated in a space without people.

In addition, since integrated control of many air conditioners that use a lot of energy in a building is difficult and difficult to monitor, it is urgently sought to reduce unnecessary energy waste.

Meanwhile, users in the Middle East do not change the air conditioner once it has been set. However, the user changes the temperature setting at seasonal or specific times. Looking at each season (seasonal), during February to October, the user sets a certain temperature and rarely performs temperature manipulation. During November through January, users do not use or minimally use packaged air conditioners (A / C).

Looking at breakfast, lunch and dinner on a daily basis, the user uses a fixed value and does not change it. However, the daily weather temperatures in the Middle East are quite large between morning, lunch and dinner.

However, countries in the Middle East are oil-mass-rich countries that have always had air conditioning turned into desert countries. In particular, Kuwait provides 95% of the electricity bill in the country, which causes a lot of waste by habitually operating air conditioners all year round.

Meanwhile, conventional simulation techniques for managing the energy of a building simulate and manage the energy of a building by using a heat-related factor collected from a sensor. Conventional simulation techniques mainly collect the room temperature, the outside temperature, the body temperature of the occupants in a heat-related factor and reflect them in the simulation. However, these conventional simulation techniques are impossible to accurately simulate the energy flow of the building, it is impossible to know how the temperature of the building changes.

Embodiments of the present invention receive the wall temperature of the inner wall of the building through a relay through the relay, along with the control data of the package air conditioner covering the plurality of indoor spaces and the sensing data for the indoor space, the sensing data including the wall temperature And control data through big data analysis and machine learning analysis by machine learning engine, and relay the calculated control command through repeater to control package air conditioner. It is to provide a home energy management system using a plurality of sensors that can efficiently save energy in consideration of the wall temperature of a building.

In addition, embodiments of the present invention receives the wall temperature of the inner wall of the building and the wall surface temperature of the other inner wall through the relay through the repeater together with the control data of the package air conditioner covering the plurality of indoor space and the sensing data for the indoor space. The control command is calculated through the big data analysis and the machine learning analysis of the sensing data and the adjustment data including the wall temperature and the wall surface temperature, and the calculated control command is relayed through the repeater to install the package air conditioner. By controlling, in consideration of various spaces or space environments in the home, as well as the wall temperature and the wall surface temperature of the building, it is possible to provide a home energy management system using a plurality of sensors that can efficiently save energy.

According to a first aspect of the present invention, an apparatus regulator for controlling a package air conditioner for cooling operation through a duct connected to each of a plurality of indoor space; A first repeater receiving adjustment data for adjusting the package air conditioner from the device controller and relaying the received adjustment data; An indoor sensor unit configured to sense indoor environments for the plurality of indoor spaces, respectively, and installed on an inner wall of the space to sense a wall temperature; A second repeater receiving sensing data and wall temperature data from the indoor sensor unit and relaying the received sensing data and wall temperature data; A home energy controller for collecting and processing wall temperature data, sensing data, and adjustment data relayed from the first and second repeaters; And receiving the wall temperature data, the sensing data, and the adjustment data from the home energy controller in a big data format to build a database, and converting the received wall temperature data, the sensing data, and the adjustment data based on the constructed database into a machine learning engine. A home energy management server for processing through big data analysis and machine learning analysis to calculate a control command, and transmitting the calculated control command to the home energy controller, wherein the home energy controller includes the calculated control command. It may be transmitted to the device controller via the first repeater, the device controller may be provided with a home energy management system for adjusting the package air conditioner according to the transmitted control command.

The home energy management system includes: a solar cell system providing power generated through a solar cell as an auxiliary power source to the package air conditioner; A power meter for measuring the amount of power consumed by the package air conditioner and the amount of power generated by the solar cell system; And a third repeater for relaying the amount of power consumption and generation power measured by the power meter to the home energy controller, wherein the home energy management server is configured to display the wall temperature data, the sensing data and the adjustment data, and the amount of power consumption and generation power. The control command may be processed by processing through big data analysis and machine learning analysis by the machine learning engine.

The home energy management system may include: an outdoor sensor unit configured to generate outdoor sensing data by sensing an outdoor environment of a home; And a fourth repeater for relaying the generated outdoor sensing data to the home energy controller, wherein the home energy management server includes the wall temperature data, the sensing data and the adjustment data, and the outdoor sensing data by a machine learning engine. Big data analysis and machine learning analysis can be used to generate control commands.

The home energy management system further includes at least one external home server connected to the home energy management server through an external network and providing a reference database for machine learning to the home energy management server. The management server processes wall temperature data, sensing data, and adjustment data through big data analysis and machine learning analysis by a machine learning engine based on the constructed database and a reference database provided from an external home server to calculate a control command. Can be.

The indoor sensor unit may include a wall temperature sensor installed at an inner wall of the space and configured to sense a wall temperature, and may include at least one sensor of a temperature sensor, a humidity sensor, a thermal sensor, an in-room sensor, and an infrared sensor.

The home energy management server may control a control command by reflecting an adjustment priority of at least one of the priorities of indoor spaces, the priorities of each room, the priorities of each room, and the limits of the indoor spaces in the big data analysis and machine learning analysis. Can be calculated.

The home energy management server calculates the time required for stopping and restarting the package air conditioner by reflecting a heat transmission rate set in advance according to the material and thickness of the inner wall of the space in the big data analysis and the machine learning analysis, and calculating the calculated time required. Can be included in control commands.

According to a second aspect of the present invention, a device regulator for controlling a package air conditioner for cooling operation through a duct connected to each of a plurality of indoor space; A first repeater receiving adjustment data for adjusting the package air conditioner from the device controller and relaying the received adjustment data; An indoor sensor unit configured to sense indoor environments for the plurality of indoor spaces, respectively, installed on an inner wall of the space to sense a first wall temperature, and a second wall temperature for the inner wall of the space and a different inner wall; A second repeater receiving sensing data and first and second wall temperature data from the indoor sensor unit, and relaying the received sensing data and wall temperature data; A home energy controller for collecting and processing first and second wall temperature data, sensing data, and regulating data relayed from the first and second repeaters; And receiving first and second wall temperature data, sensing data, and adjustment data from the home energy controller in a big data format to construct a database, and based on the constructed database, the received first and second wall temperature data. And a home energy management server configured to process the sensing data and the adjustment data through big data analysis and machine learning analysis by a machine learning engine, to calculate a control command, and to transmit the calculated control command to the home energy controller. The home energy controller may transmit the calculated control command to the device controller via the first repeater, and the device controller may be provided with a home energy management system for adjusting the package air conditioner according to the transmitted control command. .

The home energy management system includes: a solar cell system providing power generated through a solar cell as an auxiliary power source to the package air conditioner; A power meter for measuring the amount of power consumed by the package air conditioner and the amount of power generated by the solar cell system; And a third repeater for relaying the consumption and power generation power measured by the power meter to the home energy controller, wherein the home energy management server includes the first and second wall temperature data, sensing data and adjustment data, and The power consumption and power generation can be processed through big data analysis and machine learning analysis by the machine learning engine to generate control commands.

The home energy management system may include: an outdoor sensor unit configured to generate outdoor sensing data by sensing an outdoor environment of a home; And a fourth repeater for relaying the generated outdoor sensing data to the home energy controller, wherein the home energy management server is configured to exchange the first and second wall temperature data, sensing data and adjustment data, and the outdoor sensing data. The control command may be processed by processing through big data analysis and machine learning analysis by the machine learning engine.

The home energy management system further includes at least one external home server connected to the home energy management server through an external network and providing a reference database for machine learning to the home energy management server. The management server processes the first and second wall temperature data, sensing data, and adjustment data through big data analysis and machine learning analysis by a machine learning engine based on the constructed database and a reference database provided from an external home server. The control command can be calculated.

The indoor sensor unit includes a wall temperature sensor installed on an inner wall of the space and senses a first wall temperature, and includes an infrared sensor that senses a second wall temperature of the inner wall of the space and another inner wall, and includes a temperature sensor and humidity. It may include at least one or more of the sensor, the thermal sensor and the occupant sensor.

Embodiments of the present invention receive the wall temperature of the inner wall of the building through a relay through the relay, along with the control data of the package air conditioner covering the plurality of indoor spaces and the sensing data for the indoor space, the sensing data including the wall temperature And control data through big data analysis and machine learning analysis by machine learning engine, and relay the calculated control command through repeater to control package air conditioner. Energy can be saved efficiently by considering the wall temperature of the building.

In addition, embodiments of the present invention receives the wall temperature of the inner wall of the building and the wall surface temperature of the other inner wall through the relay through the repeater together with the control data of the package air conditioner covering the plurality of indoor space and the sensing data for the indoor space. The control command is calculated through the big data analysis and the machine learning analysis of the sensing data and the adjustment data including the wall temperature and the wall surface temperature, and the calculated control command is relayed through the repeater to install the package air conditioner. By controlling, it is possible to efficiently save energy in consideration of the wall temperature and the wall surface temperature of the building, as well as various spaces and space environments in the home.

1 and 2 are views illustrating the operation of a package air conditioner installed in a groove applied to embodiments of the present invention.

3 is a block diagram of a home energy management system using a plurality of sensors according to embodiments of the present disclosure.

4 is a block diagram of a home energy management system using a plurality of sensors according to embodiments of the present disclosure.

5 is a detailed configuration diagram of an indoor sensor unit in a home energy management system using a plurality of sensors according to the first embodiment of the present invention.

6 is a detailed configuration diagram of an indoor sensor unit in a home energy management system using a plurality of sensors according to a second embodiment of the present invention.

FIG. 7 is a diagram illustrating an implementation example in which a home energy management system using a plurality of sensors according to a first embodiment of the present invention is installed in a plurality of indoor spaces.

FIG. 8 is a diagram illustrating an implementation example in which a home energy management system using a plurality of sensors according to a second embodiment of the present invention is installed in a plurality of indoor spaces.

[Description of the code]

100: home energy management system 101: package air conditioning

102: duct 110: appliance regulator

120: first repeater 300: indoor sensor unit

131: indoor sensor 140: second repeater

150: power meter 160: third repeater

170: solar cell system 180: outdoor sensor unit

190: fourth repeater 11: home energy controller

12: home energy management server 13: external home server

301: first wall 302: second wall

311: wall temperature sensor 312: infrared sensor

313: temperature / humidity sensor 314: occupant sensor

315: Additional sensor A 316: Additional sensor B

320: data collection unit

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It will be described in detail focusing on the parts necessary to understand the operation and action according to the present invention. In describing the embodiments of the present invention, descriptions of technical contents that are well known in the technical field to which the present invention belongs and are not directly related to the present invention will be omitted. This is to more clearly communicate without obscure the subject matter of the present invention by omitting unnecessary description.

In addition, in describing the components of the present invention, different reference numerals may be given to components having the same name according to the drawings, and the same reference numerals may be given to different drawings. However, even in such a case, it does not mean that the corresponding components have different functions according to embodiments, or does not mean that they have the same functions in different embodiments. Judgment should be made based on the description of each component in.

First, prior to the description of Figures 1 and 2, it will be described with respect to the building features of the Middle East, the package air conditioner is applied to the embodiments of the present invention.

In general, buildings in the Middle East are facing north. All of me is to the north of the window. The buildings in the Middle East are inhabited by multi-family homes. In general houses, multi-family families live together in two- or three-story buildings.

Packaged air conditioners are installed in these buildings to perform the cooling operation of the house. The package air conditioner may be installed as a rooftop package air conditioner. Looking at the rooftop package air conditioner, a duct-shaped air vent and a ventilation system are installed on the roof. Depending on the size, five to eight tuyeres may be installed.

One packaged air conditioner covers two or three or 2.5 spaces or rooms.

These packaged air conditioners are directly connected to the rooftop air conditioning system and thermostat. One thermostat is connected to each package air conditioner.

Looking at the general three-story building structure, the ground floor of the building includes a living room and a reception room. There is a living room and a room on the 1st floor. The 2nd Floor has a room and a laundry / housekeeper room. The rooftop has an air conditioning blower system and a power terminal box.

On the other hand, looking at the general three-storey and basement building structure, the first basement of the building includes a living room, prayer room and room. The ground floor of the building contains a living room, a reception room and a room. There is a living room and a room on the 1st floor. The 2nd Floor has a living room, room and laundry / housekeeper room. The rooftop has an air conditioning blower system and a power terminal box.

Meanwhile, an air conditioner operation pattern in which a user of the Middle East operates a package air conditioner will be described.

For the basics, the user basically does not change the temperature once set. However, the user changes the temperature setting at seasonal or specific times.

Looking at each season (seasonal), during February to October, the user sets a certain temperature and rarely performs temperature manipulation. During November through January, users do not use or minimally use packaged air conditioners (A / C).

Seasonally, during the summer holidays, Christmas season, and Ramadan, families leave their homes and, if only housekeepers live, maintain the least energy use possible. The housekeeper (Housekeeper) resides on a separate floor.

Looking at breakfast, lunch and dinner on a daily basis, the user uses a fixed value and does not change it. Looking at the daily weather temperatures in the Middle East, the daily cross between breakfast, lunch and dinner is quite large.

Features of the package air conditioner applied to the home energy management system according to embodiments of the present invention and the cooling operation in the room layout will be described.

As shown in FIG. 1 and FIG. 2, the package air conditioner 101 may be installed as a rooftop packaged air conditioner. A duct-like tuyeres and a ventilation system are installed on the roof of the building where the package air conditioner 101 is installed. Five to eight tuyeres may be installed depending on the size.

One package air conditioner 101 may cover 2 to N or 2.5 spaces or rooms. It is not limited to the number of specific rooms.

For example, as shown in FIG. 1A, the package air conditioner 101 is cooled through a duct 102 connected to rooms 1 and 2, which are a plurality of indoor spaces, respectively.

As shown in FIG. 1B, the package air conditioner 101 is cooled through a duct 102 connected to a plurality of indoor spaces, a room 1 and a living room, respectively.

As shown in (a) of FIG. 2, the package air conditioner 101 is cooled through a duct 102 connected to each of a plurality of indoor spaces, room 1, room 2, and living room.

As shown in (b) of FIG. 2, the package air conditioner 101 is cooled through a duct 102 connected to each of a plurality of indoor spaces, a room 1, a kitchen, and a living room.

As shown in (a) of FIG. 2, the package air conditioner 101 is cooled through a duct 102 connected to a plurality of indoor spaces, that is, rooms 1, 2, 3, 4, and 4, respectively.

The device controller 110 controls the package air conditioners 101 respectively connected to the rooms or the living rooms, which are the plurality of indoor spaces.

The package air conditioner 101 is directly connected to the rooftop air conditioner blowing system and the device controller 110 in a 1: 1. One thermostat is connected to each package air conditioner. Here, the temperature control is a method of controlling with a temperature controller or a remote control.

One device controller 110 directly connected to the package air conditioner 101 is installed in any one space or room among a plurality of spaces covered by the package air conditioner 101. The device controller 110 may be in room 1 or in living room 1. Here, the room 2 is not installed. The appliance regulator 110 is also not present in room 3.

As shown in FIG. 3, the home energy management system 100 according to the embodiments of the present invention may include a device controller 110, a first repeater 120, an indoor sensor unit 300, a second repeater 140, A home energy controller 11 and a home energy management server 12.

Hereinafter, the specific configuration and operation of each component of the home energy management system 100 according to the embodiments of the present invention of FIG. 3 will be described.

The device controller 110 controls the package air conditioner 101 that is cooled by the duct 102 connected to the plurality of indoor spaces, respectively. The device controller 110 is a thermostat that controls the package air conditioner 101 and is connected 1: 1 with each package air conditioner. The device controller 110 may communicate with the first repeater 120 via wire or wirelessly. For example, the device controller 110 may communicate with the first repeater 120 based on power line communication (PLC).

The first repeater 120 receives adjustment data for adjusting the package air conditioner 101 from the device controller 110. The first repeater 120 relays the received adjustment data to the home energy controller 11. Here, the first repeater 120 may relay the adjustment data and the control command to the device controller 110 and the home energy controller 11 using PLC communication, respectively.

The indoor sensor unit 300 senses indoor environments for a plurality of indoor spaces, respectively, and is installed on an inner wall of the space to sense wall temperature. The indoor sensor unit 300 may communicate with the first repeater 120 through wire or wirelessly. For example, the indoor sensor unit 300 includes a Bluetooth / BLE-based temperature / humidity sensor and periodically measures and transmits temperature / humidity to the home energy controller 11 via the first repeater 120. have.

For example, the indoor sensor unit 300 may include a wall temperature sensor installed on an inner wall of the space and sense a wall temperature, and include at least one or more of a temperature sensor, a humidity sensor, a thermal sensor, an in-patient sensor, and an infrared sensor. Can be.

As another example, the indoor sensor unit 300 includes a wall temperature sensor installed on an inner wall of the space and senses a first wall temperature, and includes an infrared sensor sensing a second wall temperature of the inner wall of the space and another inner wall. It may include at least one sensor of the temperature sensor, humidity sensor, thermal sensor and occupant sensor.

The device controller 110 may communicate with the first repeater 120 based on power line communication (PLC).

The second repeater 140 receives the sensing data and the wall temperature data from the indoor sensor unit 300 and relays it to the home energy controller 11. Here, the second relay 140 may collect a Bluetooth Beacon Scanner, a Universally Unique IDentifier (UUID), and signal strength information, and collect the collected information using a PLC communication home energy controller. 11 can be transmitted.

Thereafter, the home energy controller 11 collects and processes wall temperature data, sensing data, and adjustment data relayed from the first and

second repeaters

120 and 140. Here, the home energy controller 11 receives and processes sensing data (eg, temperature, humidity, occupant, occupant location information, etc.), wall temperature data, and adjustment data collected from two or more repeaters, and then includes a home energy management server ( 12), and transmits the set temperature or humidity information received from the home energy management server 12 to the device controller.

The home energy management server 12 receives wall temperature data, sensing data, and adjustment data from the home energy controller 11 in a big data format and builds it into a database. Thereafter, the home energy management server 12 analyzes the wall temperature data, the sensing data, and the adjustment data received from the home energy controller 11 through the big data analysis and the machine learning analysis by the machine learning engine based on the established database. Processing to yield a control command. The home energy management server 12 transmits the calculated control command to the home energy controller 11. As such, the home energy management server 12 is a server existing within the system. The home energy management server 12 receives data collected from the home energy controller 11, stores the data in a database, and performs big data analysis and machine learning analysis through a machine learning engine. It is possible to provide the home energy controller 11 with an optimum control command (eg, temperature set value, restart time after stopping the air conditioner, etc.).

Here, the home energy management server 12 reflects the adjustment priority that combines at least one of the priority of each indoor space, the priority of each hour, the priority of each room, and the limits of the indoor space to the big data analysis and machine learning analysis. Control command can be calculated.

In addition, the home energy management server 12 calculates the time required for stopping and restarting the package air conditioner 101 by reflecting the heat transmission rate set in advance according to the material and thickness of the inner wall of the space in the big data analysis and the machine learning analysis. The calculated time required can be included in the control command.

Thereafter, the home energy controller 11 transmits the control command calculated by the home energy management server 12 to the device controller 110 via the first repeater 120. Subsequently, the device controller 110 adjusts the package air conditioner 101 according to the control command transmitted from the first repeater 120.

Meanwhile, the home energy management system 100 according to the embodiments of the present invention may further include a solar cell system 170, a power meter 150, and a third repeater 160.

The solar cell system 170 provides power generated through the solar cell to the package air conditioner 101 as an auxiliary power source. Here, the solar cell system 170 is a solar based PV module (eg, including an inverter) and may provide power generation information to the power meter 150.

The power meter 150 measures the amount of power consumed by the package air conditioner 101 and the amount of generated power generated by the solar cell system 170. Here, the power meter 150 may be connected to the solar cell system 170 and the package air conditioner 101 to measure the amount of power consumed and transmitted to the third repeater 160 using RS485 communication.

The third repeater 160 relays the amount of power consumption and generation power measured by the power meter 150 to the home energy controller 11. The third repeater 160 may transmit power information and the power meter 150 connected to the package air conditioner 101 and the solar cell system 170 to the home energy controller 11 through PLC communication.

Thereafter, the home energy management server 12 receives wall temperature data, sensing data and regulation data, and power consumption and generation power from the home energy controller 11. The home energy management server 12 may calculate the control command by processing the wall temperature data, the sensing data and the regulation data, the consumption and the generated power amount through the big data analysis and the machine learning analysis by the machine learning engine.

Meanwhile, the home energy management system 100 according to the embodiments of the present invention may further include an outdoor sensor unit 180 and a fourth repeater 190.

The outdoor sensor unit 180 generates outdoor sensing data by sensing an outdoor environment of a home. Here, the outdoor sensor unit 180 may measure an external temperature / humidity through a weather station and transmit it to the fourth repeater 190.

The fourth repeater 190 relays the outdoor sensing data generated by the outdoor sensor unit 180 to the home energy controller 11. Here, the fourth repeater 190 may collect external temperature and humidity data of the outdoor environment and transmit the data to the home energy controller 11 through PLC communication.

Then, the home energy management server 12 receives wall temperature data, sensing data and adjustment data, and outdoor sensing data from the home energy controller 11. The home energy management server 12 may calculate the control command by processing the wall temperature data, the sensing data, the adjustment data, and the outdoor sensing data through big data analysis and machine learning analysis by the machine learning engine.

Meanwhile, the home energy management system 100 according to the embodiments of the present invention may further include at least one external home server 13.

The external home server 13 is connected to the home energy management server 12 through an external network and provides the home energy management server 12 with a reference database for machine learning. Here, the external home server 13 is an external server that can support a database so that the home energy management server 12 performing machine learning can provide more effective results by providing a database for reference for machine learning. have.

Thereafter, the home energy management server 12 analyzes the wall temperature data, the sensing data, and the regulation data by the machine learning engine and the big data analysis and the machine learning analysis based on the built database and the reference database provided from the external home server 13. Can be processed to produce a control command.

On the other hand, the home energy controller 11 may communicate with the user terminal to monitor or control the state inside the home using a user terminal (eg, a smartphone, a smart pad, etc.) held by an externally located user.

As shown in FIG. 4, the home energy management system 100 according to the second embodiment of the present invention is the same as the embodiments of the present invention shown in FIG. 3, the device regulator 110 and the first repeater 120. ), An indoor sensor unit 300, a second repeater 140, a home energy controller 11, and a home energy management server 12.

An embodiment of the present invention illustrated in FIG. 4 will be described based on differences from FIG. 3.

First, the package air conditioner 101 applied to the embodiment of the present invention includes a plurality of package air conditioners 101. Correspondingly, the device controller 110 also has a plurality of device controllers 110 connected to the plurality of package air conditioners 101, respectively, and controls the connected package air conditioners 101, respectively.

For example, package air conditioner # 1, package air conditioner # 2,... , Package air conditioner #X is installed in the home. Correspondingly, device controller # 1, device controller # 2,... , Appliance conditioner #X, package air conditioner # 1, package air conditioner # 2,… It is connected to package air conditioner #X respectively.

The first repeater 120 receives a plurality of adjustment data for adjusting the plurality of package air conditioners 101 from the plurality of device controllers. The first repeater 120 relays the received plurality of adjustment data to the home energy controller 11.

Thereafter, the home energy controller 11 collects and processes a plurality of adjustment data, wall temperature data, and sensing data relayed from the first and

second repeaters

120 and 140.

The home energy management server 12 receives a plurality of control data, wall temperature data, and sensing data from the home energy controller 11 in a big data format and builds it into a database. Thereafter, the home energy management server 12 analyzes the big data analysis and the machine learning analysis by the machine learning engine on the plurality of adjustment data, wall temperature data, and sensing data received from the home energy controller 11 based on the established database. Processing through to calculate a plurality of control commands for each package air conditioner. The home energy management server 12 transmits the calculated plurality of control commands to the home energy controller 11.

Thereafter, the home energy controller 11 individually transmits a plurality of control commands calculated by the home energy management server 12 to each device controller 110 via the first repeater 120. Subsequently, the plurality of device controllers 110 respectively adjust the package air conditioners 101 according to control commands respectively transmitted from the first repeater 120.

As shown in FIG. 5, the indoor sensor unit 300 of the home energy management system 100 according to the first embodiment of the present invention includes a wall temperature sensor 311, an infrared sensor 312, and a temperature / humidity sensor. 313 and the occupant sensor 314 and the data collection unit 320. Here, the indoor sensor unit 300 may further include an additional sensor A 315 and an additional sensor B 316 capable of sensing additional information of the indoor environment.

Hereinafter, specific configurations and operations of components of the indoor sensor unit 300 according to the first embodiment of the present invention of FIG. 5 will be described.

First, the wall temperature sensor 311 is provided on the first wall 301 which is an inner wall of the space. The wall temperature sensor 311 generates wall temperature data by sensing a wall temperature of the inner wall.

In addition, the plurality of indoor sensors, the infrared sensor 312, the temperature / humidity sensor 313, and the in-room sensor 314, sense the indoor environment for the indoor space divided by the first wall 301.

The data collector 320 is connected to the wall temperature sensor 311, the infrared sensor 312, the temperature / humidity sensor 313, and the occupant sensor 314. The data collector 320 may be wall temperature data of the first wall 301 sensed by the wall temperature sensor 311, and an infrared sensor 312, a temperature / humidity sensor 313, and an in-room sensor 314, respectively. Collect sensed sensing data. Subsequently, the data collector 320 transmits the collected wall temperature data and the sensing data to the second repeater 140.

As shown in FIG. 6, the indoor sensor unit 300 of the home energy management system 100 according to the second embodiment of the present invention includes a wall temperature sensor 311, an infrared sensor 312, and a temperature / humidity sensor. 313 and the occupant sensor 314 and the data collection unit 320. Here, the indoor sensor unit 300 may further include an additional sensor A 315 and an additional sensor B 316 capable of sensing additional information of the indoor environment.

Hereinafter, specific configurations and operations of components of the indoor sensor unit 300 according to the second embodiment of the present disclosure of FIG. 6 will be described.

First, the wall temperature sensor 311 is provided on the first wall 301 which is an inner wall of the space. The wall temperature sensor 311 generates first wall temperature data by sensing the wall temperature of the inner wall.

The infrared sensor 312 is installed at a position facing the second wall 302 which is an inner wall different from the inner wall of the space. The infrared sensor 312 generates second wall temperature data by sensing the second wall temperature of the second wall 302 using infrared light. At this time, the second wall temperature is not the inner wall temperature of the second wall 302 but the surface temperature of the second wall 302.

The plurality of indoor sensors, the temperature / humidity sensor 313 and the occupant sensor 314, sense an indoor environment for an indoor space divided into a first wall 301 and a second wall 302, respectively.

The data collector 320 is connected to the wall temperature sensor 311, the infrared sensor 312, the temperature / humidity sensor 313, and the occupant sensor 314. The data collector 320 includes first wall temperature data of the first wall 301 sensed by the wall temperature sensor 311 and a second wall of the second wall 302 sensed by the infrared sensor 312. The sensing data collected by the temperature data, the temperature / humidity sensor 313, and the occupant sensor 314 are collected. Subsequently, the data collector 320 transmits the collected first and second wall temperature data and the sensing data to the second repeater 140.

As described above, the home energy management system 100 according to the first and second embodiments of the present invention is a method of directly or indirectly measuring the wall temperature of a building and by measuring the wall temperatures of two sides, respectively. The package air conditioner 101 can be controlled more accurately than the simulation technique. Here, in the case of the temperature of the wall (building), the ascending and descending speed proceeds very slowly compared to the room temperature or body temperature. Therefore, when the user wants to stop the package air conditioner 101 at the time of going out or for a certain time, the home energy management system 100 does not operate the package air conditioner 101 and uses the heat permeation rate to maintain a time required to maintain a certain temperature It can be predicted. Through this, the home energy management system 100 may reduce the operating time of the package air conditioner 101 as much as possible to save energy.

By measuring the wall temperature or the wall temperature of the inner wall of the building and the wall surface temperature of the other walls, it is possible to calculate the time required to restart the air conditioner by stopping the air conditioner according to the degree of heat transmission rate. Here, it is assumed that the thermal permeability is determined to some extent or the thermal permeability is known based on the material and thickness of the inner wall determined basically. The home energy management system 100 adds a factor of the wall surface temperature or heat permeability as well as the wall temperature to the heat related sensing data. The home energy management system 100 may control the package air conditioner 101 by calculating an effective duration through machine learning so that the home energy management system 100 may effectively use energy saving based on the plurality of sensing data. That is, in the first and second embodiments of the present invention, as an important main factor to reliably make a decision on the operation of the package air conditioner 101 and the temperature of the energy saving through such machine learning, In addition to the temperature, wall surface temperature or heat permeability may be further added.

The home energy management system 100 according to the first and second embodiments of the present invention cares to allow the occupant to feel similar to the usual when the air conditioner does not operate or operates at the minimum energy use (temperature) during the required time. Energy can be saved effectively.

As shown in FIG. 7, the home energy management system 100 according to the first embodiment of the present invention may include a first repeater 120, an indoor sensor unit 300, and a second repeater 120 connected to the device controller 110. 140, home energy controller 11, and home energy management server 12. In addition, the home energy management system 100 according to the first embodiment of the present invention may further include a solar cell system 170 and a power meter 150.

First, the first repeater 120 is installed in an indoor space in which the device controller 110 is installed. The first repeater 120 receives adjustment data for adjusting the package air conditioner 101 from the device controller 110.

The second repeater 140 is installed in a plurality of different spaces in which the first repeater 120 is not installed. The second repeater 140 receives sensing data and wall temperature data from the indoor sensor unit 300 installed in a plurality of different spaces and relays the sensing data and the wall temperature data to the home energy controller 11.

The indoor sensor unit 300 may include a wall temperature sensor installed on an inner wall of the space and sense a wall temperature, and may include at least one or more of a temperature sensor, a humidity sensor, a thermal sensor, an in-room sensor, and an infrared sensor.

In addition, the indoor sensor unit 300 may further include an illumination sensor for sensing the lighting of the indoor space, an entrance sensor for sensing the person entering and leaving the indoor space.

As shown in FIG. 8, the home energy management system 100 according to the first embodiment of the present invention may include a first repeater 120, an indoor sensor unit 300, and a second repeater 120 connected to the device controller 110. 140, home energy controller 11, and home energy management server 12.

The indoor sensor unit 300 includes a wall temperature sensor 311 installed on an inner wall of the space and senses a wall temperature, and includes an infrared sensor 312 that senses a second wall temperature for the inner wall of the space and another inner wall. do. In addition, the indoor sensor unit 300 may further include a temperature / humidity sensor 313 and an occupant sensor 314. In addition, the indoor sensor unit 300 may further include an illumination sensor for sensing the lighting of the indoor space, an entrance sensor for sensing the person entering and leaving the indoor space.

Here, the wall temperature sensor 311 is installed on the first wall 301 which is the inner wall of the space and senses the wall temperature of the inner wall to generate the first wall temperature data.

In addition, the infrared sensor 312 is installed at a position facing the second wall 302 which is an inner wall different from the inner wall of the space, and senses the second wall temperature of the second wall 302 by using infrared rays to sense the second wall. Generate temperature data. Here, the infrared sensor 312 may generate the second wall temperature data by sensing the second wall temperature using the thermal image. At this time, the second wall temperature is not the inner wall temperature of the second wall 302 but the surface temperature of the second wall 302.

The embodiments described above are just one example, and various modifications and changes may be made by those skilled in the art without departing from the essential characteristics of the present invention. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical idea of the present invention but to describe the present invention, and the scope of the technical idea of the present invention is not limited by these embodiments. The protection scope of the present invention should be interpreted by the following claims, and all technical ideas within the equivalent scope should be interpreted as being included in the scope of the present invention.

Claims

A device controller for controlling a package air conditioner that is cooled through a duct connected to a plurality of indoor spaces;

A first repeater receiving adjustment data for adjusting the package air conditioner from the device controller and relaying the received adjustment data;

An indoor sensor unit configured to sense indoor environments for the plurality of indoor spaces, respectively, and installed on an inner wall of the space to sense a wall temperature;

A second repeater receiving sensing data and wall temperature data from the indoor sensor unit and relaying the received sensing data and wall temperature data;

A home energy controller for collecting and processing wall temperature data, sensing data, and adjustment data relayed from the first and second repeaters; And

Receive wall temperature data, sensing data, and adjustment data from the home energy controller in a big data format and construct a database, and store the received wall temperature data, sensing data, and regulation data in a machine learning engine based on the constructed database. A home energy management server for processing through big data analysis and machine learning analysis to calculate a control command and transmitting the calculated control command to the home energy controller;

The home energy controller transmits the calculated control command to the device controller via the first repeater, and the device controller controls the package air conditioner according to the transmitted control command.
The method of claim 1,

A solar cell system providing electric power generated through a solar cell as an auxiliary power source to the package air conditioner;

A power meter for measuring the amount of power consumed by the package air conditioner and the amount of power generated by the solar cell system; And

And a third repeater which relays the amount of consumed power and generated power measured by the power meter to the home energy controller.

The home energy management server is configured to process the wall temperature data, sensing data and control data and the power consumption and power generation through big data analysis and machine learning analysis by a machine learning engine to calculate a control command.
The method of claim 1,

An outdoor sensor unit configured to sense an outdoor environment of a home to generate outdoor sensing data; And

And a fourth repeater for relaying the generated outdoor sensing data to the home energy controller.

The home energy management server processes the wall temperature data, the sensing data and the adjustment data, and the outdoor sensing data through big data analysis and machine learning analysis by a machine learning engine to calculate a control command.
The method of claim 1,

At least one external home server connected to the home energy management server through an external network and providing the home energy management server with a reference database for machine learning;

The home energy management server processes wall temperature data, sensing data, and adjustment data through big data analysis and machine learning analysis by a machine learning engine based on the constructed database and a reference database provided from an external home server. Home energy management system.
The method of claim 1,

The indoor sensor unit,

And a wall temperature sensor installed on an inner wall of the space and sensing a wall temperature, the home energy management system including at least one of a temperature sensor, a humidity sensor, a thermal sensor, an in-patient sensor, and an infrared sensor.
The method of claim 1,

The home energy management server,

A home energy management system that calculates control commands by reflecting control priorities in combination with at least one of the priority of each room, priority of each room, priority of each room, and limit of each room in the big data analysis and machine learning analysis. .
The method of claim 1,

The home energy management server,

Home energy that calculates the time required to stop and restart the package air conditioner by reflecting the heat transfer rate set in advance according to the material and thickness of the inner wall of the space in big data analysis and machine learning analysis, and include the calculated time in the control command. Management system.
A device controller for controlling a package air conditioner that is cooled through a duct connected to a plurality of indoor spaces;

A first repeater receiving adjustment data for adjusting the package air conditioner from the device controller and relaying the received adjustment data;

An indoor sensor unit configured to sense indoor environments for the plurality of indoor spaces, respectively, installed on an inner wall of the space to sense a first wall temperature, and a second wall temperature for the inner wall of the space and a different inner wall;

A second repeater receiving sensing data and first and second wall temperature data from the indoor sensor unit, and relaying the received sensing data and wall temperature data;

A home energy controller for collecting and processing first and second wall temperature data, sensing data, and regulating data relayed from the first and second repeaters; And

Receiving first and second wall temperature data, sensing data, and adjustment data from the home energy controller in a big data format to construct a database, and based on the constructed database, the received first and second wall temperature data; A home energy management server which processes the sensing data and the adjustment data through big data analysis and machine learning analysis by a machine learning engine to calculate a control command, and transmits the calculated control command to the home energy controller,

The home energy controller transmits the calculated control command to the device controller via the first repeater, and the device controller controls the package air conditioner according to the transmitted control command.
The method of claim 8,

A solar cell system providing electric power generated through a solar cell as an auxiliary power source to the package air conditioner;

A power meter for measuring the amount of power consumed by the package air conditioner and the amount of power generated by the solar cell system; And

And a third repeater which relays the amount of consumed power and generated power measured by the power meter to the home energy controller.

The home energy management server processes the first and second wall temperature data, sensing data and control data, and the consumption and power generation amount through big data analysis and machine learning analysis by a machine learning engine to calculate a control command. Energy management system.
The method of claim 8,

An outdoor sensor unit configured to sense an outdoor environment of a home to generate outdoor sensing data; And

And a fourth repeater for relaying the generated outdoor sensing data to the home energy controller.

The home energy management server processes the first and second wall temperature data, sensing data and control data, and the outdoor sensing data through big data analysis and machine learning analysis by a machine learning engine to calculate a control command. Management system.
The method of claim 8,

At least one external home server connected to the home energy management server through an external network and providing the home energy management server with a reference database for machine learning;

The home energy management server performs big data analysis and machine learning analysis by a machine learning engine on the first and second wall temperature data, sensing data, and adjustment data based on the constructed database and a reference database provided from an external home server. A home energy management system that processes through to produce control commands.
The method of claim 8,

The indoor sensor unit,

A wall temperature sensor installed on an inner wall of the space and sensing a first wall temperature, and including an infrared sensor sensing a second wall temperature for the inner wall of the space and another inner wall, the temperature sensor, the humidity sensor, the thermal sensor; Home energy management system comprising at least one of the occupant sensors.
The method of claim 8,

The home energy management server,

A home energy management system that calculates control commands by reflecting control priorities in combination with at least one of the priority of each room, priority of each room, priority of each room, and limit of each room in the big data analysis and machine learning analysis. .
The method of claim 8,

The home energy management server,

Home energy that calculates the time required to stop and restart the package air conditioner by reflecting the heat transfer rate set in advance according to the material and thickness of the inner wall of the space in big data analysis and machine learning analysis, and include the calculated time in the control command. Management system.