KR101800310B1 - Cloud energy management system system and method for providing energy saving guide - Google Patents

Abstract

A method for providing a cloud EMS (Energy Management System) may include a step of generating the energy prediction model of a target building based on past energy data, a step of classifying the target building into at least one group of a plurality of predetermined groups, a step of monitoring the energy usage patterns of a plurality of buildings included in at least one group, a step of generating an energy saving guide for the target building based on the energy usage patterns of the plurality of buildings; and a step of providing the generated energy saving guide.

Description

[0001] CLOUD ENERGY MANAGEMENT SYSTEM AND METHOD FOR PROVIDING ENERGY SAVING GUIDE [0002]

The present invention relates to a cloud EMS (Energy Management System) system and method for providing an energy saving guide.

An energy management system (EMS) installs sensors on energy devices, sends sensed energy usage to the EMS server through the sensor, the EMS server determines the energy policy based on the collected energy usage information, It is a system that manages and controls energy usage of energy devices based on energy policy. The energy management system is divided into BEMS (Building EMS), HEMS (Home EMS), and FEMS (Factory EMS) according to the type of provision.

The conventional method of operating the building energy is a method in which the manager collects the operating state of the facilities (for example, the air conditioning system, the lighting facility, the disaster prevention facility, the security facility, etc.), the energy consumption amount, and the building environment data.

However, the manager was not an energy expert who could analyze the energy trends and various environmental factors in the building, and he was staying at the level of simple energy management. In addition, even if the equipment has the facility to reduce energy consumption in the building, it was impossible to operate the system to optimize its utilization and efficiency.

Korean Patent Laid-Open Publication No. 2014-0025050 discloses an energy saving system that monitors the energy usage of each of the energy usage apparatuses and saves energy based on the relationship information between at least two energy usage apparatuses of the plurality of energy usage apparatuses And the amount of energy savings that can be saved for each energy saving rule based on the monitored energy usage is calculated.

A plurality of buildings are grouped according to predetermined energy characteristics, energy saving patterns are compared between grouped buildings to generate energy saving guides, and a generated energy saving guide is provided to a plurality of buildings. It is to be understood, however, that the technical scope of the present invention is not limited to the above-described technical problems, and other technical problems may exist.

According to an aspect of the present invention, there is provided a method for providing a cloud EMS (Energy Management System) according to the first aspect of the present invention includes the steps of generating an energy prediction model of a target building based on past energy data, The method comprising the steps of: classifying a target building into at least one group of a plurality of predetermined groups; monitoring an energy use pattern of a plurality of buildings included in the at least one group; Generating an energy saving guide for the target building, and providing the generated energy saving guide.

 The cloud EMS system providing the energy saving guide according to the second aspect of the present invention includes an energy prediction model generation unit for generating an energy prediction model of a target building based on past energy data, A monitoring unit for monitoring an energy use pattern of a plurality of buildings included in the at least one group, a monitoring unit for monitoring an energy usage pattern of the plurality of buildings, An energy saving guide generating unit for generating a saving guide, and an energy saving guide providing unit for providing the generated energy saving guide.

A cloud EMS system providing an energy saving guide according to a third aspect of the present invention includes a monitoring unit for monitoring an energy usage pattern of a plurality of buildings, a monitoring unit for monitoring energy usage patterns of the plurality of buildings, An energy saving guide generating unit for generating an energy saving guide by comparing energy usage patterns between the grouped buildings, and an energy saving guide generating unit for generating the energy saving guide by using the plurality of And an energy saving guide providing unit provided to the building.

The above-described task solution is merely exemplary and should not be construed as limiting the present invention. In addition to the exemplary embodiments described above, there may be additional embodiments described in the drawings and the detailed description of the invention.

According to any one of the above-mentioned objects of the present invention, an energy saving guide is created by grouping a plurality of buildings according to predetermined energy characteristics, comparing energy usage patterns among grouped buildings, It can be provided to a plurality of buildings.

In addition, it is possible to provide optimum energy saving guide suitable for buildings by remotely integrating and processing the building energy management environment operated by individual buildings in a cloud operation manner.

1 is a configuration diagram of a cloud EMS (Energy Management System) providing system according to an embodiment of the present invention.
2 is a block diagram of an energy policy generator of the cloud EMS system shown in FIG. 1, according to an embodiment of the present invention.
3 is a block diagram of an energy policy generator of the cloud EMS system shown in FIG. 1, according to another embodiment of the present invention.
4A to 4D are views for explaining an energy saving guide according to an embodiment of the present invention.
FIG. 5 is a diagram illustrating a grouping of buildings according to the same characteristics, according to an embodiment of the present invention.
6 is a flow diagram illustrating a method for providing a cloud EMS, in accordance with an embodiment of the present invention.
7 is a block diagram of a first type of EMS platform, in accordance with an embodiment of the present invention.
8 is a block diagram of a second type of EMS platform, in accordance with an embodiment of the present invention.
9 is a view showing a conventional energy management system.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "electrically connected" with another part in between . Also, when an element is referred to as "comprising ", it means that it can include other elements as well, without departing from the other elements unless specifically stated otherwise.

In this specification, the term " part " includes a unit realized by hardware, a unit realized by software, and a unit realized by using both. Further, one unit may be implemented using two or more hardware, or two or more units may be implemented by one hardware.

In this specification, some of the operations or functions described as being performed by the terminal or the device may be performed in the server connected to the terminal or the device instead. Similarly, some of the operations or functions described as being performed by the server may also be performed on a terminal or device connected to the server.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings.

FIG. 1A is a configuration diagram of a cloud EMS (Energy Management System) providing system according to an embodiment of the present invention.

Referring to FIG. 1A, a cloud EMS provisioning system may include a target building 100, a cloud EMS system 110, and a predetermined plurality of groups 120. Here, the target building 100 may be a new accommodating building of the cloud EMS providing system. However, since the cloud EMS providing system of FIG. 1 is only one embodiment of the present invention, the present invention is not limited to FIG. 1 and may be configured differently from FIG. 1 according to various embodiments of the present invention .

Generally, the components of the cloud EMS provisioning system of FIG. 1A are connected through a network (not shown). A network refers to a connection structure in which information can be exchanged between nodes such as terminals and servers. An example of such a network is Wi-Fi, Bluetooth, Internet, LAN Network, wireless LAN, WAN, PAN, 3G, 4G, 5G, LTE, and the like.

The target building 100 may transmit historical energy data of the energy devices built in the target building 100 to the cloud EMS system 110. [ Here, the energy device may include, for example, an air conditioner, a ventilator, an air conditioner, a heat pump, an on / humidity sensor, a lighting device, The past energy data may include, for example, operational status information of the energy device, energy metering information (power, gas, water, air volume, etc.), energy consumption and production volume.

The target building 100 may be a building in which a local EMS is built. For example, if a local EMS is installed in the target building 100, the local EMS of the target building 100 may receive the energy policy directly from the cloud EMS system 110 and, based on the energy policy, Can operate.

The target building 100 may be a building in which only the EMS gateway is built (FIG. 8). In addition, the target building 100 may be a building in which the local EMS is not built (Fig. 7). The target building 100 can be provided with energy policy and energy saving guide from the cloud EMS system 110 and can operate the energy device based on the energy policy and energy saving guide. Here, the energy policy may include, for example, an energy peak management policy, an energy saving consumption target policy, an energy facility operation control policy, and the like.

The cloud EMS system 110 generates an energy prediction model for each of a plurality of buildings based on past energy data collected from a plurality of buildings (not shown) for a predetermined period of time, A plurality of buildings having the same characteristics can be grouped according to energy production characteristics.

For example, the cloud EMS system 110 may generate an energy prediction model of the target building 100 based on historical energy data collected from the target building 100.

The cloud EMS system 110 may classify the target building 100 into at least one group 121 of a predetermined plurality of groups 120 by using the energy prediction model of the target building 100. [

For example, the cloud EMS system 110 can classify the target building 100 into the group 121 having the same characteristics as the target building 100, based on the energy usage pattern of the target building 100. [

The cloud EMS system 110 generates an energy saving guide for the target building 100 based on the energy usage pattern of the monitored plurality of buildings 122 and provides the generated energy saving guide to the target building 100 .

The predetermined plurality of groups 120 may be grouped according to predetermined energy consumption characteristics or energy production characteristics of a plurality of buildings based on energy usage patterns of a plurality of buildings. Here, the energy consumption characteristic may mean energy consumption according to, for example, cooling / heating index, day of the week, holiday information, resident information and working time information, and the energy production characteristic may be, for example, And can be a form of energy generation according to weather information such as solar radiation, solar radiation, and the like.

1B is a block diagram of a cloud EMS system 110 in accordance with one embodiment of the present invention.

Referring to FIG. 9, a conventional energy management system will be described. 13 is a view showing a conventional energy management system. Referring to FIG. 9, a conventional energy management system may include an EMS server 1300, a local EMS 1302, and a plurality of energy devices 1304.

Each energy device 1304 may include a sensor that senses energy usage, energy usage patterns, etc. of the energy device 1304 and sends sensed energy data to the EMS server 1300 via the EMS gateway 1308 ).

Local EMS 1302 may include policy manager 1308 and EMS gateway 1308. The energy management system must have an EMS gateway 1308 for communication of energy data between the plurality of energy devices 1304 and the EMS server 1300. [ EMS gateway 1308 may receive energy data from a plurality of energy devices 1304 and send it to EMS server 1300. In addition, the EMS gateway 1308 may receive policy information from the EMS server 1300.

The policy administration unit 1308 may store policy information received by the EMS gateway 1308 and may operate a plurality of energy devices 1304 based on the policy.

The EMS server 1300 may generate policies based on the energy data of the plurality of energy devices 1304.

According to such a conventional energy management system, a local EMS 1302 must be established for each site, which causes a problem of a large initial cost. In addition, the administrator of the site has to set a rule set of the energy device 1304 based on the policy information stored directly in the policy management unit 1308, and operate the policy according to the policy. Also, since the administrator is often a non-expert, it is difficult to operate the local EMS 1302.

The present invention can provide a cloud EMS system in which an EMS platform is built for each site to solve the problems of the conventional energy management system.

Referring to FIG. 1B, the cloud EMS system 110 may include an energy policy generating unit 130, a plurality of EMS platforms 140-1, 140-2, 140-3, and the like.

A plurality of EMS platforms 140-1, 140-2, 140-3, etc. are connected to each of the sites 150-1, 150-2, 150-3, etc. and the networks 160-1, 160-2, As shown in FIG. For example, the first EMS platform 140-1 is the EMS platform for the first site 150-1 and the second EMS platform 140-2 is the EMS platform for the second site 150-2. And the third EMS platform 140-3 may be the EMS platform for the third site 150-3. Although only three EMS platforms and three sites are shown in FIG. 1B, the number of EMS platforms and sites is not limited.

The EMS platforms 140-1, 140-2, 140-3, and the like receive energy data (energy use patterns) from the sites 150-1, 150-2, 150-3, To the energy policy generating unit 130.

The EMS platforms 140-1, 140-2, 140-3, and the like receive the energy policies received from the energy policy generation unit 130 and receive the energy policies from the sites 150-1, 150-2, 150 -3, etc.) energy devices.

Here, the types of the EMS platforms 140-1, 140-2, 140-3, etc. may include two types. This will be described later with reference to Figs. 7 and 8.

The energy policy generating unit 130 receives the energy data of each site 150-1, 150-2, 150-3, etc. from the EMS platform 140-1, 140-2, 140-3, To generate an energy policy for each site 150-1, 150-2, 150-3, and so on. Here, the energy policy may include ruleset setting information, demand forecast information, energy saving guide information, device management information, data processing information, monitoring information, and the like. The details of this will be described later with reference to FIG.

7 is a diagram illustrating a first type of EMS platform 140-1 of a plurality of EMS platforms 140-1, 140-2, 140-3, and so on. Referring to FIG. 7, a first type of EMS platform 140-1 may include a policy administration unit 1100, 1102 and an EMS gateway 1104. Here, the policy operating units 1100 and 1102 may include a first policy operating unit 1100 and a second policy operating unit 1102.

Since both the policy management units 1100 and 1102 and the EMS gateway 1104 are constructed in the first type of EMS platform 140-1, there is no need to construct a local EMS system including the EMS gateway in the corresponding site.

The energy device 1106 at the site may communicate directly with the first type of EMS platform 140-1 on a static IP basis. In this case, each energy device 1106 may transmit energy data to the EMS gateway 1104 and the EMS gateway 1104 may transmit the energy data to the energy policy generator 130. The EMS gateway 1104 may transmit the energy policy received from the energy policy generating unit 130 to each energy device 1106 of the corresponding site.

The first policy operating unit 1100 may store the first type of energy policy among the energy policies generated by the energy policy generating unit 130. [ The first type of energy policy may be an EMS system common policy. The EMS system common policy may include device management information, data processing information, monitoring information, and the like.

The first policy operating unit 1100 may operate each energy device 1106 based on a first type of energy policy.

The second policy operation unit 1102 may store a second type of energy policy among the energy policies generated by the energy policy generating unit 130. [ The first type of energy policy may be a specialized EMS policy. The specialized EMS policy may include ruleset configuration information, demand forecast information, energy saving guide information, and the like.

The second policy operation unit 1102 may operate each energy device 1106 based on the second kind of energy policy.

Alternatively, the energy device 1106 at the site may communicate directly with the first type of EMS platform 140-1 on a static IP basis, such as an embedded wireless communication modem such as LTE (Long Term Evolution) or 3G (3Generation) . In this case, the energy device 1106 may communicate directly with the energy policy generator 130 without passing through the EMS gateway 1104.

By constructing the first type of EMS platform 140-1, the site can build EMS at a low cost, and maintenance of the EMS system is not necessary.

FIG. 8 is a diagram illustrating a second type of EMS platform 140-2 among a plurality of EMS platforms 140-1, 140-2, 140-3, and so on. Referring to FIG. 8, the second type of EMS platform 140-2 may include a policy administration unit 1200, 1202. [ Here, the policy management units 1200 and 1202 may include a first policy management unit 1200 and a second policy management unit 1202.

Since only the policy management units 1200 and 1202 are installed in the second type of EMS platform 140-2, a local EMS gateway 1204 needs to be separately installed in the corresponding sites. For example, the local EMS gateway 1204 may be an industrial mini PC. The local EMS gateway 1204 may communicate with the energy device 1206 configured as a floating IP through an internal network.

The local EMS gateway 1204 may receive energy data in real time from each energy device 1206. [ The local EMS gateway 1204 may store the collected real-time energy data for disaster recovery (DR). The local EMS gateway 1204 may transmit the collected energy data to the energy policy generating unit 130. [

The local EMS gateway 1204 can receive the energy policy from the first policy operation unit 1200, the second policy operation unit 1202 and transmit it to each energy device 1206.

By configuring the second type of EMS platform 140-2, the site has the advantage that it can be used for disaster recovery by storing real-time energy data in the local EMS gateway 1204.

Hereinafter, the operation of each component of the energy policy generator of the cloud EMS provision system of FIGS. 1A and 1B will be described in more detail. FIG. 2 is a block diagram of the energy policy generator 130 shown in FIGS. 1A and 1B, according to an embodiment of the present invention.

2, the energy policy generating unit 130 includes an energy prediction model generating unit 210, a grouping unit 220, a monitoring unit 230, an updating unit 240, an energy saving guide generating unit 250, An energy saving guide providing unit 260 and a DB 270. The energy saving prediction model generating unit 210 includes an energy demand prediction model generating unit 211 and an energy production prediction model generating unit 212. The energy saving guide generating unit 260 includes a correction performing unit 261 . However, the energy policy generating unit 130 shown in FIG. 2 is only one embodiment of the present invention, and various modifications are possible based on the components shown in FIG.

The energy prediction model generation unit 210 can generate the energy prediction model of the target building 100 based on the past energy data. The energy forecasting model may include an energy demand forecasting model and an energy production forecasting model.

For example, the energy prediction model generation unit 210 may generate an energy prediction model of the target building 100 based on real-time information related to energy consumption and production status of energy-related facilities of the target building 100.

The energy demand forecast model generation unit 211 generates an energy demand forecast model for the target building 100 based on at least one of the cooling / heating index, the day of the week, the holiday information, the resident information, Energy demand forecasting model can be created.

For example, the parameters for generating the energy demand forecasting model may include air conditioning index, day of the week, holiday information, resident information, and working time information.

For example, the variables of the energy demand forecasting model are fixed energy, demand change by holiday, demand change by Monday, demand change by Friday, demand change by Saturday, demand change by Sunday, demand change by work time , Consumption before 1 hour, consumption before 2 hours, consumption before 24 hours, consumption time before a week, cooling index (CDD), and heating index (HDD).

The energy demand forecast model generation unit 211 can generate historical energy demand data corresponding to generation variables of the energy demand prediction model based on the past data received from the target building 100. [ Past energy demand data may include constants corresponding to each of the generated variables of the energy demand forecasting model.

The energy demand prediction model generation unit 211 can generate an energy demand prediction model of the target building 100 based on the energy demand prediction model and past energy demand data. For example, the energy demand forecast model (E) is shown in Equation (1).

[Equation 1]

Consumption (-2h) + a9 * consumption (-24h) E = a0 + a1 * holiday + a2 * Mon + a3 * fri + a4 * sat + a5 * sun + a6 * work_time + + a10 * consumption (-168h) + a11 * CDD + a12 * HDD

Here, a0 to a12 are the variables corresponding to the variables of the energy demand forecasting model, and are the variables of holiday, Mon, fri, sat, sun work_time, consumption (-1h), consumption (-2h) -168h), CDD and HDD can be constant values corresponding to each of the generated variables of the energy demand prediction model included in the past energy demand data.

For example, the energy demand forecast model generation unit 211 generates energy demand prediction model 211 from the target building 100 based on fixed energy, demand change according to holiday, demand change according to Monday, demand change according to Friday, demand change according to Saturday, The demand change amount according to the working time, the consumption amount of 1 hour before, the consumption amount of 2 hours before, the consumption amount of 24 hours before, the total consumption time of one week, the cooling index and the heating index, Can be used as a value.

The energy demand prediction model generation unit 211 can update the past energy demand data for the target building 100 based on the data received from the target building 100. [ For example, the energy demand prediction model generation unit 211 may update each constant corresponding to each of the generated variables of the energy demand prediction model included in the past energy demand data. This allows the energy prediction model of the target building 100 to be close to the energy room model.

The energy demand prediction model generation unit 211 can generate a plurality of energy demand prediction models for each building based on the variables of the energy demand prediction models of the plurality of buildings and the past energy demand data. In addition, the past energy demand data of a plurality of buildings can be updated.

The energy production prediction model generation unit 212 can generate an energy production prediction model based on the weather information. The weather information may include at least one of a temperature, a cloudiness, sunrise and sunset, and solar radiation.

For example, when the target building 100 is a building (e.g., a photovoltaic generator installed building, a solar power plant, or the like) that produces new and renewable energy, An energy production prediction model of the target building 100 can be generated based on the amount of solar radiation in the location.

The group classifying unit 220 may classify the target building 100 into at least one group 121 among a plurality of predetermined groups 120. [ Here, the predetermined plurality of groups 120 may be divided into buildings having the same characteristics based on energy consumption characteristics or energy production characteristics. For example, the predetermined plurality of groups 120 may include a group having high fixed energy, a group having sensitivity to heating index, a group having a high resident in the building, a group having high holiday energy consumption, and the like. A method of grouping into a plurality of groups 120 will be described later with reference to FIG.

The group classifying unit 220 can classify the target building 100 into any one of the predetermined plurality of groups 120 based on the energy usage pattern of the target building 100. [

For example, the group classifying unit 220 classifies the target building 100 into a plurality of predetermined buildings (not shown) based on at least one of the heating and cooling index, the day of the week information, the holiday information, And the group 121 may be classified into any one of the groups 120.

The grouping unit 220 may classify the target building 100 into any one of the predetermined plurality of groups 120 based on the local weather information in which the target building 100 is located.

The monitoring unit 230 may periodically monitor an energy usage pattern of a plurality of buildings 122 included in at least one group 121 in which the target building 100 is classified. For example, the monitoring unit 230 may monitor the amount of energy consumed by the target building 100 over time, the load information of equipment installed in the target building 100, and the peak value information.

The update unit 240 may periodically update the energy prediction models of each of the plurality of buildings 122 based on the energy usage patterns of the plurality of buildings 122 monitored.

The monitoring unit 230 may periodically monitor the energy usage pattern of the target building 100.

The update unit 240 may periodically update the energy prediction model of the target building 100 based on the energy usage pattern of the monitored target building 100. [ For example, the updating unit 240 can update the past energy demand data for the target building 100 based on the data received from the target building 100. [ For example, the update unit 240 may update each constant corresponding to each of the generated variables of the energy demand prediction model included in the past energy demand data. This allows the energy prediction model of the target building 100 to be close to the energy room model.

The energy saving guide generating unit 250 may generate an energy saving guide for the target building 100 based on the energy usage patterns of the plurality of buildings 122. [ The energy saving guide generating unit 250 may generate an energy saving guide for the target building 100 by comparing the energy usage patterns between the target building 100 belonging to the same group 121 and the plurality of buildings 122 .

The correction performing unit 251 compares the energy usage patterns between a plurality of buildings 122 in the same group 121 or a plurality of buildings in another group with the target building 100, Can be converted into a reference energy comparison index (area correction and local correction). Here, the correction performing unit 251 can analyze the energy use pattern of the target building 100 from the energy demand prediction model of the target building 100. [

The correction performing unit 251 may analyze an energy use pattern of a plurality of buildings from energy demand prediction models of each of a plurality of buildings, and then perform area correction and area correction on energy usage patterns of a plurality of buildings. The area correction means, for example, that the energy production and consumption of a building is converted to energy production and consumption or a reference energy unit based on the total area.

Local compensation can mean, for example, converting the energy production and consumption of a building into environmental conditions in a reference area.

The correction performing unit 251 may convert the energy usage amount of the target building 100 into the energy usage amount based on the total area based on the energy usage pattern of the target building 100. [

The correction performing unit 251 may convert the energy production amount of the target building 100 into the energy production amount with respect to the electricity generation capacity when the target building 100 is a building that produces new and renewable energy.

The correction performing unit 251 may convert a plurality of energy produced by the target building 100 and a plurality of energy consumed by the target building 100 into a Tone of Energy (TOE). For example, the correction performing unit 251 may convert the usage amount of electric energy and gas energy consumed in the target building 100 into the TOE.

The correction performing unit 251 can correct the energy usage amount of the target building 100 based on the energy usage pattern of the target building 100 and the weather information of the reference area. For example, when the reference area is charged, the correction performing unit 251 can lower the heating consumption amount of the building in the upper area by a predetermined value, and the cooling consumption amount can be increased by a predetermined value. Further, the heating consumption amount of the building in the lower area can be increased by a predetermined value, and the cooling consumption amount can be lowered by a predetermined value. Here, the predetermined value may be changed on the basis of the degree to which the area of the target building 100 and the reference area are separated from each other.

The energy saving guide generation unit 250 compares the TOEs of the plurality of buildings 122 included in the group 121 in which the target building 100 is classified and compares the TOEs 122 of the plurality of buildings 122 Data and potential savings data.

The energy saving guide generating unit 250 can select a building (for example, a building having a high energy efficiency) to be benchmarked in the group 120. The energy saving guide generating unit 250 can calculate the potential savings data of a plurality of buildings by comparing the TOE between the benchmarking target building and the plurality of buildings. Potential savings data can include fixed parts, cooling parts, and heating parts.

The energy saving guide generation unit 250 can analyze the energy consumption factor of the target building 100 from the comparison data and the potential saving amount data of the plurality of buildings 122. [

For example, when the target building 100 is a building having a high energy consumption per unit area, the energy saving guide generating unit 250 generates energy saving guide 250 for energy equipment (e.g., communication equipment, power equipment, electric lamp / Energy consumption can be periodically compared and analyzed.

The energy saving guide providing unit 260 can provide the generated energy saving guide to the target building 100. [ Also, the energy saving guide providing unit 260 may transmit the generated energy saving guide to the EMS platforms 140-1, 140-2, and 140-3. 4A to 4D, the energy saving guide will be described.

4A to 4D are views for explaining an energy saving guide according to an embodiment of the present invention.

Referring to FIG. 4A, the energy saving guide includes an energy use comparison history 701 (including energy consumption and energy use fee information of the target building 100 and energy usage and energy use charge information of the target building 100) ) And energy savings record (703) from the previous month.

Referring to FIG. 4B, the energy saving guide includes an energy usage amount of the target building 100, an average energy usage amount of the group 121, and a group 121 of the group 121 in the group 121 to which the target building 100 belongs. The energy saving class information 707 of the target building 100 and the energy use analysis information 709. The graph 705 includes a graph 705 that compares the energy saving class information 701 and the benchmark target building 711 of the target building 100. [

Referring to FIG. 4C, the energy saving guide may include a graph showing energy usage trends of the target building 100 by monthly time period.

Referring to FIG. 4D, the energy saving guide includes energy usage ranking information (for example, a fixed energy usage ranking, a working energy usage ranking, an energy efficiency rating information) of the target building 100 in the group 121 to which the target building 100 belongs Etc.).

Referring again to FIG. 2, the energy saving guide providing unit 260 may provide the target building 100 with an energy saving guide including information on energy efficiency improvement measures suitable for the environmental conditions of the target building 100.

The energy saving guide providing unit 260 can provide the target building 100 with information for energy efficiency improvement such as monitoring and management of the energy efficiency failure of facilities installed in the target building 100.

The energy saving guide providing unit 260 may provide the transmission cycle and the transmission method of the energy saving guide differently based on the attribute data of the target building 100 (for example, building area, scale, building use, etc.).

For example, when the target building 100 is a temperature-sensitive building, the energy saving guide providing unit 260 can provide the target building 100 with an energy use increase rate of the target building 100 due to an increase in the external temperature have.

For example, the energy saving guide providing unit 260 can transmit an expected energy use increase report to the target building 100 on a specific day when the target building 100 has a high energy consumption on a specific day.

For example, the energy saving guide providing unit 260 may transmit an unused device power save notification message to the target building 100 on the day before the weekend when the target building 100 has a high energy consumption on the weekend. In another example, the energy saving guide providing unit 260 may propose replacement of the heating / heating equipment to the target building 100 when the target building 100 has a high value of the cooling / heating potential savings.

DB 270 stores data input and output between components of the cloud EMS system 110 and inputs and outputs data between components outside the cloud EMS system 110 and the cloud EMS system 110 And stores the data. One example of such a DB 270 includes a hard disk drive, a ROM (Read Only Memory), a RAM (Random Access Memory), a flash memory, a memory card, and the like existing in or outside the cloud EMS system 110.

The energy policy generating unit 130 may further include an energy policy determining unit 280 and an energy policy transmitting unit 290. The energy policy determination unit 280 may generate the energy policy of the target building 100 based on the energy prediction model of the target building 100. [ For example, the energy policy determination unit 280 can determine the energy policy based on the updated energy prediction model, that is, the real model.

The energy policy transmission unit 290 may transmit the energy policy of the generated target building 100 to the EMS platforms 140-1, 140-2, and 140-3.

Those skilled in the art will appreciate that the energy prediction model generating unit 210, the grouping unit 220, the monitoring unit 230, the updating unit 240, the energy saving guide generating unit 250, the energy saving guide providing unit 260, And the DB 270, the energy policy determination unit 280, and the energy policy transmission unit 290 may be separately implemented, or at least one of them may be integrated.

3 is a block diagram of the energy policy generator 130 shown in FIG. 1 according to another embodiment of the present invention.

3, the energy policy generating unit 130 may include a monitoring unit 310, a grouping unit 320, an energy saving guide generating unit 330, and an energy saving guide providing unit 340. However, the cloud EMS system 110 shown in FIG. 3 is only one embodiment of the present invention, and various modifications are possible based on the components shown in FIG.

The monitoring unit 310 may monitor energy usage patterns of a plurality of buildings. For example, the monitoring unit 310 can receive energy consumption amount, peak information, facility operation state information, and the like from a plurality of buildings over time. For example, the monitoring unit 310 can monitor the energy production amount of a plurality of buildings by receiving weather information about an area where a plurality of buildings are located, from a weather server (not shown).

The grouping unit 320 can group a plurality of buildings according to predetermined energy consumption characteristics or energy production characteristics based on energy usage patterns of a plurality of buildings.

Referring to FIG. 5, the grouping unit 320 may group a plurality of buildings having the same energy demand characteristics based on at least one of the heating / cooling index, the day of the week, the holiday information, the resident information, have.

The grouping unit 320 may group a plurality of buildings having the same energy production characteristics based on weather information including at least one of temperature, electric current, sunrise and sunset, and solar radiation.

Referring again to FIG. 3, the energy saving guide generating unit 330 may generate an energy saving guide by comparing energy usage patterns among the grouped buildings.

The energy saving guide providing unit 340 can provide the generated energy saving guide to a plurality of buildings.

Those skilled in the art will recognize that the monitoring unit 310, the grouping unit 320, the energy saving guide generating unit 330, and the energy saving guide providing unit 340 may be separately implemented, or at least one of them may be integrated It will be appreciated.

The monitoring unit 310, the grouping unit 320, the energy saving guide generating unit 330, and the energy saving guide providing unit 340 shown in FIG. 3 correspond to the grouping unit 220, The monitoring unit 230, the updating unit 240, the energy saving guide generating unit 250, and the energy saving guide providing unit 260.

6 is a flow diagram illustrating a method for providing a cloud EMS, in accordance with an embodiment of the present invention.

The cloud EMS providing method according to the embodiment shown in FIG. 6 is a method for providing the cloud EMS in the target building 100, the cloud EMS system 110 and the predetermined plurality of groups 120 according to the embodiment shown in FIGS. Lt; / RTI > Therefore, the contents described with respect to the target building 100, the cloud EMS system 110, and the predetermined plurality of groups 120 of FIGS. 1 to 5, according to the embodiment shown in FIG. 6, It can also be applied to the cloud EMS provisioning method.

Referring to FIG. 6, in step S901, the cloud EMS system 120 may generate an energy prediction model of the target building 100 based on past energy data.

In step S903, the cloud EMS system 120 may classify the target building 100 into at least one group 121 among a plurality of predetermined groups 120.

In step S905, the cloud EMS system 120 may monitor an energy usage pattern of a plurality of buildings 122 included in at least one group 121. [

In step S907, the cloud EMS system 120 can generate an energy saving guide for the target building 100 based on the energy usage patterns of the plurality of buildings 122. [

In step S909, the cloud EMS system 120 can provide the generated energy saving guide to the target building 100. [

Although not shown in FIG. 6, in step S907, the cloud EMS system 120 may perform area correction and area correction on the energy usage pattern of the target building 100. FIG.

Although not shown in FIG. 6, in step S907, the cloud EMS system 120 converts the energy usage amount of the target building 100 into the energy consumption amount per unit area based on the energy usage pattern of the target building 100, 100) and a plurality of energy consumed in the target building (100) can be converted into the TOE.

Although not shown in FIG. 6, in step S907, the cloud EMS system 120 can correct the energy usage amount of the target building 100 based on the energy usage pattern of the target building 100 and the weather information of the reference area.

Although not shown in FIG. 6, in step S909, the cloud EMS system 120 compares the TOEs of the plurality of buildings 122 included in at least one group 121, and, based on the comparison result, ) And the potential savings data to the target building 100. [0035]

Although not shown in FIG. 6, in step S901, the cloud EMS system 120 calculates an energy demand prediction model based on at least one of the cooling / heating index, the day of week information, the holiday information, the resident information, And generate an energy production prediction model based on the weather information. Here, the weather information may include at least one of a temperature, a cloudiness, sunrise and sunset, and an amount of solar radiation.

Although not shown in FIG. 6, in step S903, the cloud EMS system 120 groups a plurality of buildings having the same characteristics based on at least one of the cooling / heating index, day of the week, holiday information, resident information, and working time information .

Although not shown in FIG. 6, after step S909, the cloud EMS system 120 may periodically update the energy prediction model of the target building 100 based on the energy usage patterns of the plurality of buildings 122 monitored.

In the above description, steps S901 to S909 may be further divided into further steps or combined in fewer steps, according to an embodiment of the present invention. Also, some of the steps may be omitted as necessary, and the order between the steps may be changed.

One embodiment of the present invention may also be embodied in the form of a recording medium including instructions executable by a computer, such as program modules, being executed by a computer. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes any information delivery media, including computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

It is intended that the present invention covers the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents. .

100: Target building
110: Cloud EMS system
120: a plurality of predetermined groups

Claims (22)

A method for providing a cloud EMS (Energy Management System)
Generating an energy prediction model of the target building based on past energy data;
Classifying the target buildings into at least one group among a plurality of predetermined groups;
Monitoring energy usage patterns of a plurality of buildings included in the at least one group;
Generating an energy saving guide for the target building based on energy usage patterns of the plurality of buildings; And
Providing the generated energy saving guide to the target building
, ≪ / RTI &
Wherein the plurality of groups are grouped into a plurality of buildings having the same characteristics based on energy consumption characteristics or energy production characteristics,
The step of classifying the target buildings into at least one of a plurality of preset groups
And classifying the target building into at least one group having the same energy consumption characteristic or the same energy production characteristic as the target building among the plurality of groups using the energy prediction model of the target building.
The method according to claim 1,
The step of generating the energy saving guide for the target building
Performing area correction and area correction on the energy usage pattern of the target building
Lt; RTI ID = 0.0 > EMS. ≪ / RTI >
3. The method of claim 2,
The step of performing the area correction and the area correction includes
Converting the energy usage amount of the target building into the energy usage amount based on the floor area based on the energy usage pattern of the target building; And
Converting a plurality of energy produced by the target building and a plurality of energy consumed by the target building into a Tone of Energy (TOE).
The method of claim 3,
The step of performing the area correction and the area correction includes
A step of correcting the energy usage amount of the target building based on the energy usage pattern of the target building and the weather information of the reference area
The method further comprising:
5. The method of claim 4,
The step of providing the generated energy saving guide
Comparing the TOEs of the plurality of buildings included in the at least one group;
Providing comparison data and potential savings data of the plurality of buildings to the target building based on the comparison result
Gt; EMS, < / RTI >
The method according to claim 1,
Wherein the energy prediction model comprises an energy demand prediction model and an energy production prediction model.
6. The method of claim 5,
The step of generating the energy prediction model
Generating an energy demand prediction model based on at least one of the cooling / heating index, the day of the week information, the holiday information, the resident number information, and the working time information of the target building; And
A step of generating an energy production prediction model based on weather information
Lt; / RTI >
Wherein the weather information includes at least one of a temperature, a cloudiness, a sunrise and a sunset, and a solar radiation amount.
The method according to claim 1,
The step of classifying the target buildings into at least one of a plurality of preset groups
And grouping a plurality of buildings having the same characteristics based on at least one of the heating / cooling index, the day of the week information, the holiday information, the resident person information, and the working time information.
The method according to claim 1,
Periodically updating the energy prediction model of the target building based on the energy usage pattern of the monitored plurality of buildings
The method further comprising:
In a cloud EMS (Energy Management System) system providing an energy saving guide,
An energy prediction model generation unit for generating an energy prediction model of the target building based on past energy data;
A group classifying unit for classifying the target buildings into at least one group among a plurality of predetermined groups;
A monitoring unit monitoring energy usage patterns of a plurality of buildings included in the at least one group;
An energy saving guide generating unit for generating an energy saving guide for the target building based on an energy usage pattern of the plurality of buildings; And
An energy saving guide providing unit for providing the generated energy saving guide to the target building,
, ≪ / RTI &
Wherein the plurality of groups are grouped into a plurality of buildings having the same characteristics based on energy consumption characteristics or energy production characteristics,
Wherein the group classifying unit classifies the target building into at least one group having the same energy consumption characteristic or the same energy production characteristic among the plurality of groups using the energy prediction model of the target building.
11. The method of claim 10,
The energy saving guide generating unit
And a correction performing unit for performing an area correction and an area correction on an energy usage pattern of the target building.
12. The method of claim 11,
The correction performing unit
Converting the energy usage amount of the target building into the energy usage amount based on the total floor area based on the energy usage pattern of the target building,
Wherein a plurality of energy produced in the target building and a plurality of energy consumed in the target building are converted into a TOE (Tone of Energy).
13. The method of claim 12,
The correction performing unit
Wherein the energy usage of the target building is corrected based on the energy usage pattern of the target building and the weather information of the reference area.
13. The method of claim 12,
The energy saving guide generating unit
Comparing the TOEs of the plurality of buildings included in the at least one group,
Generating comparison data and potential saving amount data of the plurality of buildings based on the comparison result,
The energy saving guide providing unit
And provides fraud-generated comparison data and latent savings data to the target building.
11. The method of claim 10,
Wherein the energy prediction model comprises an energy demand prediction model and an energy production prediction model.
16. The method of claim 15,
The energy prediction model generation unit
An energy demand forecasting model generating unit for generating an energy demand forecasting model based on at least one of the heating and cooling index, the day of the week information, the holiday information, the resident number information, and the working time information of the target building; And
Further comprising an energy production prediction model generation unit for generating an energy production prediction model based on weather information,
Wherein the weather information includes at least one of a temperature, a cloudiness, a sunrise and a sunset, and a solar radiation amount.
11. The method of claim 10,
The group classification unit
Wherein the plurality of buildings having the same characteristics are grouped based on at least one of the heating / cooling index, the day of the week information, the holiday information, the resident person information, and the working time information.
11. The method of claim 10,
And an updating unit for periodically updating an energy prediction model of the target building based on the energy usage patterns of the plurality of monitored buildings.
11. The method of claim 10,
Multiple EMS platforms
Further comprising:
Each of the plurality of EMS platforms collecting an energy usage pattern from a corresponding building and generating a plurality of energy devices of the corresponding building based on an energy policy and an energy saving guide generated based on the energy usage pattern of the corresponding building The cloud EMS system, which operates.
20. The method of claim 19,
Wherein the plurality of EMS platforms comprises a first type of EMS platform
/ RTI >
The first type of EMS platform storing at least one of the energy policy and the energy saving guide and operating a plurality of energy devices of the corresponding building based on the energy policy and the energy saving guide; And
An EMS gateway for data transmission between the cloud EMS system and the plurality of energy devices
Gt; EMS < / RTI > system.
21. The method of claim 20,
Wherein the plurality of EMS platforms comprises a second type of EMS platform
Further comprising:
Wherein the second type of EMS platform comprises the policy administration unit,
Wherein the EMS gateway is built in the corresponding building.
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