KR20110125541A - Apparatus, system and method for data collection - Google Patents

Abstract

PURPOSE: A data collection apparatus, a data collection system, and a data collection method are provided to perform a control process which uses energy in a limited range by switching power of various energy utilization devices. CONSTITUTION: A first receiving device(21) receives energy related data from one or more sensors. A second receiving device(22) receives energy price information according to time from a user or central server. An estimation device(23) receives energy variation usage information and a sum of energy usage per a time interval predetermined from the first receiving device. The estimation device estimates a sum of energy consumption or an amount of the energy consumption after a predetermined time by receiving the energy price information according to the time from the second receiving device.

Description

Data Acquisition Devices, Data Acquisition Systems, and Data Collection Methods {Apparatus, System and Method for Data Collection}

The present invention relates to a data collection device, a data collection system, and a data collection method, in particular, in line with the trend of efficiently utilizing limited energy resources, such as smart grid and smart meter technologies being developed and energy price fluctuation plans are implemented. The approach to predicting future energy use information allows for more active control of energy use.

Until now, various kinds of energy such as electricity, gas, and water were supplied in accordance with the maximum demand, and energy prices were fixed.

However, in recent years, as a way to more efficiently use the limited energy resources and reduce energy consumption, a way to differentiate the energy price by time zone or season is being considered.

In this regard, as a technology for promoting the efficient use of energy, a smart grid or a smart meter is of interest.

Smart Grid is a next-generation power grid that optimizes energy efficiency and creates new added value by integrating information technology (IT) into the power grid, allowing power providers and consumers to exchange real-time information in both directions.

From the perspective of the energy consumer, the smart grid finds the time that is most reasonable for them and uses energy as the price of energy changes.

Smart meters are digital meters that add communication capabilities, allowing for real-time investigation of power usage or two-way communication between power providers and consumers.

Therefore, the meter can be remotely read without visiting the home, and real-time metering enables accurate measurement of power consumption, resulting in cost savings and energy savings.

In addition, since the energy use information of the consumer can be provided through a communication network such as the Internet, the consumer can check his energy use information anytime, anywhere using various communication means such as a web, a mobile phone, a TV receiver.

Energy-related technologies, such as smart grids and smart meters, enable proactive energy management.

However, energy is constantly being used continuously and due to the nature of limited resources, not only the current energy use situation but also information on future energy use has an important effect on the supply or consumption of energy.

Accordingly, the present invention has been made to meet the above needs, by collecting data related to energy and using it to predict the future energy consumption or energy use amount to enable a more proactive approach to the use or supply of energy. The purpose of the present invention is to provide a data collection device, a data collection system, and a data collection method.

In order to achieve the above object, a first embodiment of a data collection device according to the present invention comprises: first receiving means for receiving energy-related data from at least one or more sensors; Second receiving means for receiving energy price information with time from a central server or a user; And a prediction for receiving a predetermined sum of energy usage hourly and energy variation usage information from the first receiving means, and receiving energy price information according to time from the second receiving means, and predicting an energy usage or an energy use amount after a predetermined time. It comprises a means.

A second embodiment of a data collection device according to the present invention comprises: first receiving means for receiving energy related data from at least one or more sensors; Second receiving means for receiving energy price information with time from a central server or a user; And receiving energy usage information according to time from the first receiving means, calculating price of energy use amount per hour and a change rate thereof based on the received price information of energy according to time from the second receiving means. And predicting means for predicting energy usage or energy usage amount after time.

A first embodiment of a data collection system according to the present invention comprises: first receiving means for receiving energy related data from at least one or more sensors; Second receiving means for receiving energy price information with time from a central server or a user; And a prediction for receiving a predetermined sum of energy usage hourly and energy variation usage information from the first receiving means, and receiving energy price information according to time from the second receiving means, and predicting an energy usage or an energy use amount after a predetermined time. Means;

A second embodiment of a data collection system according to the present invention comprises: first receiving means for receiving energy related data from at least one or more sensors; Second receiving means for receiving energy price information with time from a central server or a user; And receiving energy usage information according to time from the first receiving means, calculating price of energy use amount per hour and a change rate thereof based on the received price information of energy according to time from the second receiving means. Prediction means for predicting energy usage or energy usage amount after time.

Prediction means of the data collection device and the data collection system according to the present invention can predict the actual billing amount to be billed to the user as the energy use amount by using the information on the charging policy of the company that supplies the energy.

The information on the charging policy of the company that supplies the energy may include information such as basic fees, taxes, and fee benefits that are basically charged.

The data collection device and the data collection system according to the present invention may further include a device control means for controlling at least one or more energy using devices according to the energy usage or the energy use amount predicted by the prediction means.

When the energy-using device is an electric device using electric energy, the device control means may transmit a device control signal to a power switch device for turning on / off power of the corresponding energy-using device in response to each of the energy-using devices. .

The device control means preferentially cuts off the energy supply to the energy-efficient device using energy, preferentially cuts off the energy supply to the energy-using device which can further reduce the maximum energy use, or load set by the user. Energy-using devices can be controlled according to a control schedule.

The data collection device and the data collection system according to the present invention may further include transmission means for transmitting information related to energy use to another device.

The transmission means may transmit the energy usage information and the energy usage amount information predicted through the prediction means to the central server, the user's mobile terminal, an IHD (In Home Display), and the like.

The transmission means may transmit information regarding a result of the device control means controlling the energy-using device to the central server, the user's mobile terminal, an In Home Display (IHD), and the like.

The transmission means may transmit a warning message to the user's mobile terminal or IHD (In Home Display) when the energy usage amount or the energy use amount estimated by the prediction means exceeds a preset upper limit value. In this case, the upper limit value may be set to an upper limit value at a specific time point or an upper limit value for use during a specific period of time.

The first receiving means, the second receiving means, the predicting means, the device control means, and the transmitting means constituting the data collecting device and the data collecting system according to the present invention are each configured as separate devices and configured to interface with each other through a predetermined communication network. Alternatively, all may be integrated into one device, or one or more combinations may be configured into one device and interface with other devices.

A first embodiment of a data collection method according to the present invention includes a first receiving step of receiving energy related data from at least one or more sensors; A second receiving step of receiving energy price information according to time from a central server or a user; And a prediction for receiving a predetermined sum of energy usage hourly and energy variation usage information from the first receiving step, receiving energy price information according to time from the second receiving step, and predicting an energy usage or an energy use amount after a predetermined time. A step is made.

A second embodiment of a data collection method according to the present invention includes a first receiving step of receiving energy-related data from at least one or more sensors; A second receiving step of receiving energy price information according to time from a central server or a user; And receiving energy usage information according to time from the first receiving step, receiving price information of energy according to time from the second receiving step, calculating a sum of a predetermined amount of energy use per hour and a rate of change thereof, And a prediction step of predicting energy usage or energy usage amount after time.

In the predicting step of the data collection method according to the present invention, the billed amount to be actually billed to the user may be predicted as the energy use amount by using information on a billing policy of a company that supplies energy.

The information on the charging policy of the company that supplies the energy may include information such as basic fees, taxes, and fee benefits that are basically charged.

The first and second embodiments of the data collection method according to the present invention further comprise a device control step of controlling the supply of energy to at least one energy-using device according to the energy usage or energy use amount predicted in the prediction step. It can be made, including.

In the device control step, when the energy-using device is a device using electric energy, the device control signal may be transmitted to a power switch device for turning on / off power of the corresponding energy-using device in response to each of the energy-using devices.

The device control step may preferentially block energy supply to energy-efficient devices that are not energy efficient, preferentially block energy supply to energy-using devices that may further reduce the maximum energy usage, or loads set by the user. Energy-using devices can be controlled according to a control schedule.

The first and second embodiments of the data collection method according to the present invention may further include a transmitting step of transmitting information related to energy use to another device.

The transmitting step includes the energy usage information, the energy use amount information, and the information about the result of controlling the energy use device through the device control step. The central server, the mobile terminal of the user, and IHD (In Home) Display).

The transmitting step may transmit a warning message to the user's mobile terminal or an IHD (In Home Display) when the energy usage or energy usage amount estimated in the prediction step exceeds a preset upper limit. In this case, the upper limit value may be set to an upper limit value at a specific time point or an upper limit value for use during a specific period of time.

According to the present invention, it is possible to predict a future energy consumption or an energy use amount within a reasonable range from energy related data such as energy use used by an energy-using device.

The predicted information can be applied to various fields in order to promote efficient use of energy, thereby more actively approaching the rationalization of energy use.

For example, by turning on / off various energy-using devices in energy consumers such as homes, offices, and companies, it is possible to control the subsequent energy use within a limited range.

The energy use trend and the prediction result may be transmitted to the user's mobile terminal, etc. to help the user to adjust his energy consumption pattern.

In addition, forecasting information for each energy source can be passed on to energy suppliers to help them plan their energy supply.

In this way, the energy consumer or supplier can control the energy use situation in advance so that the limited resource energy can be used more effectively.

1 shows a first embodiment of a data collection device according to the present invention;
2 to 5 are examples of a method of predicting future energy usage or future energy usage amount,
6 and 7 illustrate an example of a method of predicting an energy use amount from an estimated energy use amount.
8 to 11 illustrate an example in which future energy usage or energy use amount is reduced by using an alternative energy source at an energy consumer.
12 shows a second embodiment of a data collection device according to the present invention;
13 and 14 are examples of a method of predicting energy usage from future energy use amounts;
15 is another example of a data collection device according to the present invention;
16 is another example of a data collection device according to the present invention;
17 is an embodiment of a data collection system according to the present invention;
18 and 19 are examples for explaining the role of the device control means,
20 is an example for explaining a power switch device;
21 is a flowchart of a first embodiment of a data collection method according to the present invention;
22 is a flowchart of a second embodiment of a data collection method according to the present invention;
23 is a flowchart for explaining an embodiment of a data collection method including a device control step and a transmission step;
24 is an example of an energy price structure;
25 is an example of a display screen on which energy usage information is displayed.

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

In the context of the present invention, energy means any one of electricity, gas, and water, unless specifically mentioned.

1 shows a first embodiment of a data collection device 20-1 according to the present invention, and includes a first receiving means 21, a second receiving means 22, and a predicting means 23. As shown in FIG.

The first receiving means 21 receives energy-related data from at least one or more sensors 13.

The sensor 13 is a device capable of detecting various kinds of information related to energy use, wherein energy supplied from the energy supply company 12 is used through each energy use device 16-1 to 16-k of the energy consumer. It may be an electronic meter for measuring the condition.

A specific example of such a sensor 13 is a smart meter, and the energy consumer may be provided with various types of alternative energy sources 14.

The energy-related data received by the first receiving means 21 from the sensor 13 may be variously configured as necessary, and energy usage information is an example. The energy usage information may be provided for each energy using device that uses energy, or may be provided as a total usage amount.

In addition, if the sensor 13 can provide information related to energy prices, this information may also be included.

The first receiving unit 21 uses the energy-related data received from the sensor 13 to grasp a predetermined sum of energy consumption per hour and fluctuation usage information of energy, and transmit the information to the prediction means 23.

The sum of the hourly energy usage delivered by the first receiving means 21 to the prediction means 23 refers to the sum of the energy usage at each predetermined time.

That is, if the predetermined time is a unit of time, the sum of energy usage at every hour is grasped. If the predetermined time is a unit of day, the sum of daily energy usage is grasped.

For example, if the sum of energy consumption at time point t1 is Q1 and more energy is used by dQ during the unit time from t1, then the sum of energy usage at present time point t2 after the unit time from t1 is' Q1 + dQ ', and the energy usage is dQ.

The second receiving means 22 receives the energy price information over time from the central server 11 connected through the communication network.

The central server 11 is a server that provides energy price information over time through a communication network by an energy provider or a licensed business that can provide energy price information to each user. The central server 11 may transmit energy price information through various communication networks such as a wireless mesh, a power line communication network, and an internet network.

In addition, the second receiving unit 22 may receive energy price information according to time from the user 10-1.

In this case, the second receiving unit 22 provides a user interface (UI) for the user 10-1 to input energy price information over time, or the user 10-1 provides a personal computer ( It can receive the energy price information input from other devices such as PC (Personal Computer) by communicating with the device.

The predicting means 23 receives a predetermined sum of energy consumption per hour and fluctuation amount of energy information from the first receiving means 21, and receives energy price information according to time from the second receiving means 22. Estimate usage or energy use.

Here, after a certain time refers to a future time point for predicting energy usage or energy use amount, it may be set in units of days, weeks, months, years, etc., or may be set to a specific time point in the future. An example of a particular point in time of the latter example may be a point in time at which the user is prescribed to pay for energy use, such as the last day of the month.

The prediction means 23 may predict a future energy usage or an energy usage amount by using a predetermined sum of hourly energy usage and energy usage information.

2 to 5, various methods of predicting means 23 predicting the sum of energy usage as future energy usage will be described.

It is assumed that the sum of energy usage at a certain time t1 in the past was Q1, the sum of energy usage at a present time t2 is Q2, and the sum of energy usage at some future time t3 to be predicted is Q3.

First, the prediction means 23 calculates a change rate of energy use, and the change rate of energy use may be calculated as 'dQ ÷ dt'. Where dt is 't2-t1' and dQ is 'Q2-Q1' as the variable use amount of energy.

2A illustrates an example of using a linear method for predicting a sum of future energy usage, and the sum Q3 of energy usage at some point in time t3 in the future may be predicted as in Equation 1 below.

3A shows an example of using weights to predict the sum of future energy usage.

The method using the weight may be configured in various ways, and one example thereof may be a method of applying the weight 'C' to a value greater than 1, 1, or less than 1 according to a change rate of energy usage. In this case, the sum Q3 of energy consumption at a certain time t3 in the future may be predicted as in Equation 2 below.

4A illustrates an example of using an exponential curve to predict a sum of future energy usage, and the sum Q3 of energy usage at a certain time point t3 in the future may be predicted as in Equation 3 below.

Here, the value a may be determined based on a change rate of energy usage.

FIG. 5A illustrates an example of using a log curve to predict a future sum of energy usage, and the sum Q3 of energy usage at a certain time point t3 in the future may be predicted as shown in Equation 4 below.

Here, the value a may be determined based on a change rate of energy usage.

As described above, when the sum of future energy usage is predicted, the prediction means 23 may predict the future energy use amount through various methods.

The energy use amount predicted by the prediction means 23 through the sum of the energy use as described above corresponds to the sum of the energy use, and is the sum of the energy use amount used by the user until the corresponding time in the future.

One way to predict the sum of energy use for a given point in the future is to use the sum of the forecasted energy use and the unit energy price.

Future energy prices may be current energy prices or may change over time.

In addition, the energy price may not change depending on the energy usage, or may be progressively changed according to the change in the energy usage.

According to the structure of the energy price information that can be received from the user 10-1 or the central server 11 through the second receiving means 22 will be described a specific method for predicting the sum of the future energy use amount. .

If the energy price is fixed, the energy price information has a simple structure such as Won / KWh, Won / KVarh, Won / KVAh.

However, energy prices may have various structures, such as progressive, time of use pricing, critical peak pricing, and real-time pricing.

Table 1 below shows an example of a progressive agent in which the unit price increases as energy consumption increases when energy is electricity.

Section 1 Second section Section 3 4th section ... Segment range [Kwh] To 100 101-200 201-300 301-400 ... Unit price (KRW / Kwh) 55.10 113.80 168.30 248.60 ...

FIG. 24A shows a time-based tariff (TOU) mainly used in shopping malls, factories, large buildings, etc., and prices of electricity vary according to time zones. 24B shows a critical peak rate plan (CPP), wherein the price of electricity varies depending on the time of day, and especially the price in the peak period is very high. 24C shows a real time plan (RTP), wherein the price of electricity fluctuates in real time.

If the energy price is fixed, if the sum of future energy usage is predicted, the sum of the energy usage can be easily estimated by multiplying the estimated energy usage by the energy price.

For example, if the sum of the predicted energy usage is 210Kwh and the energy price is 100 won / Kwh, the sum of the energy use amount may be calculated as '210 × 100'.

However, if energy prices fluctuate over time or with energy usage, such as progressive, time-of-day, critical peak, and real-time plans, these energy price structures should be reflected.

As one method for this, the predicting means 23 detects the fluctuation amount of energy dQ on a time interval that can reflect the change in energy price for each period from the present point in time to the future point in time, for example, 1 hour. In addition, the sum of energy use amounts can be predicted by adding all of the dQ multiplied by the energy price in the corresponding time interval.

That is, when the energy price changes, the sum M3 of the future energy use amount may be predicted as shown in Equation 5 below.

Where i denotes each time interval, Pi is the energy price in time interval i, and dQi is the variable usage of energy in time interval i.

Mc is the sum of the energy use amount at the present time point when the prediction is performed, and can be calculated by adding up the variable usage amount dQ of energy for each time period in the past and multiplied by the energy price in the corresponding time period. This Mc value can be calculated and maintained by the prediction means 23 for each time interval.

At this time, when the energy price changes with time as in the example shown in FIG. 24, Pi may use the energy price corresponding to the time interval, but in the case of the progressive agent, the sum of energy consumption up to the time interval should be considered.

However, since the sum of energy usage is already known, the energy price corresponding to the time interval can be obtained immediately.

The time interval may be further subdivided into 1 minute, 5 minutes, 10 minutes, 15 minutes, 30 minutes and the like.

At this time, the prediction means 23 may store and maintain the energy usage amount or energy use amount for each time period in the past as a load profile, and also maintain the energy usage amount or energy use amount for each time period in the future to be predicted. Can be.

In addition, the information may be transmitted to a user's mobile terminal or an IHD (In Home Display) through a transmission means to be described below, so that the user may be informed of energy usage amount or energy use amount for each time interval in the past or in the future.

Another way for the prediction means 23 to predict the sum of the energy use amount from the predicted sum of the energy use amount is to use the correspondence information between the sum of the energy use amount and the sum of the energy use amount.

An example of such a method will be described with reference to FIGS. 6 and 7.

It is assumed that the sum of energy use amounts to M1 when the sum of energy usage is Q1 at a point in time in the past t1, and the sum of energy use amounts to M2 when the sum of energy usage is Q2 at present time t2.

6A illustrates an example of using a linear method for predicting a sum of future energy use amount. If the sum of energy use amount is Q3 at some point in time t3 in the future, the sum M3 of energy use amount at that point in time is represented by the following equation. It can be predicted as 6.

7A is an example of using an exponential curve to predict the sum of future energy use amounts, and may be appropriately applied especially when energy prices are applied as progressive agents.

If the sum of the energy usage is Q3 at some point in time t3 in the future, the sum M3 of the energy usage amount may be predicted as shown in Equation 7 below.

Here, the a value may be determined based on the progressive agent or 'dM / dQ' of the energy price.

In the example shown in Figs. 6 and 7, the correspondence relation information between the sum of the energy usage and the sum of the energy usage amount can be maintained by the prediction means 23, and the central server 11 or the user 10-1 as necessary. You can also get input from).

8A, 9A, 10A, and 11A correspond to FIGS. 2A, 3A, 4A, and 5A, respectively, and when the alternative energy source 14 is present at the energy consumer, the sum of future energy usage is present. It is shown that the energy consumption at the time can be reduced than the sum.

For example, if the energy is electricity, an alternative source of energy, such as wind turbines or solar power plants, may not be used by the consumer, or may sell electricity to the utility. It may be.

When such a situation occurs, the energy usage information received from the sensor 13 fluctuates in a direction in which the energy usage decreases, and the fluctuation amount of energy has a negative slope.

6B and 7B respectively correspond to FIGS. 6A and 7A. When the variable amount of energy use has a negative slope as described above, the sum M3 of the amount of energy use predicted at any point in time in the future t3 is also illustrated. It shows a decrease from the current energy use amount M2.

FIG. 12 shows a second embodiment of a data collection device 20-2 according to the present invention, which comprises a first receiving means 21, a second receiving means 22, and a predicting means 23. As shown in FIG. .

The first receiving means 21 receives energy-related data from at least one or more sensors 13.

The sensor 13 is a device capable of detecting various kinds of information related to energy use, wherein energy supplied from the energy supply company 12 is used through each energy use device 16-1 to 16-k of the energy consumer. It may be an electronic meter for measuring the condition.

A specific example of such a sensor 13 is a smart meter, and the energy consumer may be provided with various types of alternative energy sources 14.

The energy-related data received by the first receiving means 21 from the sensor 13 may be variously configured as necessary, for example, energy usage information.

The energy usage information may be provided for each energy using device that uses energy, or may be provided as a total usage amount. In addition, if the sensor 13 can provide information related to energy prices, this information may also be included.

The second receiving means 22 receives the energy price information over time from the central server 11 connected through the communication network.

In addition, the second receiving unit 22 may receive energy price information according to time from the user 10-1. In this case, the second receiving unit 22 provides a user interface (UI) for the user 10-1 to input energy price information over time, or the user 10-1 provides a personal computer ( It can receive the energy price information input from other devices such as PC (Personal Computer) by communicating with the device.

The predicting means 23 receives the energy usage information over time from the first receiving means 21 and the energy price information over time from the second receiving means 22, and calculates the sum of the predetermined amount of energy use per hour and its rate of change. Calculate and predict energy usage or energy usage after a certain time.

Here, after a certain time refers to a future time point for predicting energy usage or energy use amount, it may be set in units of days, weeks, months, years, etc., or may be set to a specific time point in the future.

An example of a particular point in time of the latter example may be a point in time at which the user is prescribed to pay for energy use, such as the last day of the month.

The sum of the amount of energy used per hour calculated by the prediction means 23 means the sum of the amount of used energy at each predetermined time.

If the time is a unit of time, the sum of energy use is calculated at every hour, and if the time is a day, the sum of energy use is calculated every day.

For example, if the sum of the amount of energy used in the past t1 is M1 and the amount of energy used by dM has increased during the time of the unit from t1, the amount of energy used at the present time t2 has elapsed from t1. The sum is 'M1 + dM'.

The sum of the energy use amount corresponding to the time from t1 to t2 may be calculated as the product of the energy consumption input through the first receiving means 21 and the energy price input through the second receiving means 22.

The method of predicting the energy use amount or the energy use amount in the future may be variously configured by the predicting means 23 by using a predetermined sum of energy use amount per hour and the change rate thereof.

2 to 5, various methods of predicting means 23 predicting the sum of energy use amount as future energy use amount will be described.

It is assumed that the sum of the energy use amount is M1 at some time t1 in the past, the sum of the energy use amount is M2 at the present time t2, and the sum of the energy use amount is M3 at some point t3 in the future to be predicted.

The rate of change of the amount of energy used can then be calculated as 'dM ÷ dt'. Where dM is 'M2-M1' and dt is 't2-t1'.

2B illustrates an example of using a linear method for predicting a sum of future energy use amounts. At some time in the future, the sum M3 of energy use amounts may be predicted as in Equation 8 below.

3B is an example of using weights to predict future sums of energy prices, and the method of using weights may be variously configured.

One example is a method of applying the weight 'C' to a value greater than 1, 1, or less than 1 depending on the rate of change of the amount of energy used. At some point in time t3, the sum M3 of the amount of energy used may be predicted as in Equation 9 below.

4B illustrates an example of using an exponential curve to predict a sum of future energy use amounts. At some point in time in the future, the sum M3 of energy use amounts may be predicted as in Equation 10 below.

Here, the value a may be determined based on the rate of change of the energy consumption amount or the progressive agent of the energy price.

5B illustrates an example of using a log curve to predict the sum of future energy use amounts. At some point in time t3, the sum M3 of energy use amounts may be estimated as in Equation 11 below.

Here, the value a may be determined based on the rate of change of the energy consumption amount or the progressive agent of the energy price.

When the sum of future energy usage amounts is predicted as described above, the prediction means 23 may predict future energy usage through various methods.

The energy usage predicted by the prediction means 23 through the sum of the energy usage amounts as described above corresponds to the sum of the energy usage amounts, which is the sum of the energy usages used by the user until the corresponding time in the future.

One way of predicting the sum of energy usage for a given point in the future is to use the sum of the predicted energy use and the unit energy price.

Future energy prices may be current energy prices or may change over time. In addition, the energy price may not change depending on the amount of energy used, or may change gradually depending on the change in energy use.

We will look at specific ways to predict future sums of energy usage based on the structure of energy prices.

If the energy price is fixed, when the sum of future energy use is predicted, it is possible to easily estimate the future sum of energy use by dividing the energy price by the estimated sum of energy use.

For example, if the sum of the estimated energy use amount is 21,000 won and the energy price is 100 won / Kwh, the energy use may be calculated as '21, 000 ÷ 100 '.

However, energy prices can have various structures that vary over time, such as progressive, time of use pricing, critical peak pricing, and real-time pricing.

In this way, if the energy price has a variable structure, the energy price structure should be reflected.

As a method to this end, grasp the amount of change dM of the amount of energy used in the time interval that can reflect the change in energy price for a period from the present point in time to a certain point in the future, for example, one hour, and the corresponding time in each dM The sum of the energy prices divided by the intervals can be added to predict the sum of energy usage.

That is, when energy prices change, such as progressive, time-of-day, critical peak, and real-time plans, the sum of future energy consumption Q3 may be estimated as in Equation 12 below.

Where i denotes each time interval, Pi is the energy price in time interval i, and dMi is the amount of change in energy use in time interval i.

Qc is the sum of the energy consumption at the present time point when the prediction is performed, and since the energy consumption in each past time period is input through the first receiving means 21, it can be easily understood.

Pi may use the energy price corresponding to the time interval when the energy price changes with time as shown in FIG. 24.

However, in the case of the progressive agent, the energy consumption up to the corresponding time interval should be taken into consideration, and it can be predicted by considering the maximum amount used in each interval range.

As an example, assume that the currently estimated amount of energy used is 40,000 won. In Table 1, the maximum amount used for the first to fourth sections is 5,510 won, 11,380 won, 16,830 won, and 24,860 won, respectively.

If you add 5,510 won, 11,380 won, and 16,830 won, it's 33,720 won, and if you subtract 33,720 won from 40,000 won, it's 6,280 won. The unit price of the fourth section is 248.6 won, so the energy consumption in the fourth section is 25.26 Kwh (calculated as 6280 ÷ 248.6). That is, the energy consumption for the estimated use amount of 40,000 won can be estimated to be 325.26 Kwh.

The energy usage prediction method of the progressive agent may naturally be applied to the amount of energy used for each time interval.

The time interval may be further subdivided into 1 minute, 5 minutes, 10 minutes, 15 minutes, 30 minutes and the like.

At this time, the prediction means 23 may store and maintain the energy usage amount or energy use amount for each time period in the past as a load profile, and also maintain the energy usage amount or energy use amount for each time period in the future to be predicted. Can be.

Such information may be transmitted to a user's mobile terminal or an IHD (In Home Display) through a transmission means, which will be described below, to inform the user of energy usage or energy usage amount for each time period in the past or in the future.

Another way for the prediction means 23 to predict the sum of energy usage from the predicted sum of energy usage amounts is to use correspondence information between the sum of energy usage amounts and the sum of energy usage amounts.

An example of such a method of predicting the sum of future energy usage will be described with reference to FIGS. 13 and 14.

It is assumed that the sum of the energy usage was Q1 when the sum of the energy usage amounts was M1 at a point in time in the past t1, and the sum of the energy usage was Q2 when the sum of the energy usage amounts was M2 at the present time t2. Then, the amount of change dM of energy use amount is 'M2-M1' and the amount of change dQ of energy use amount is 'Q2-Q1'.

FIG. 13A is an example of using a linear method for predicting a sum of future energy usage. If the sum of energy use amounts is M3 at some point in time t3 in the future, the sum of energy consumption Q3 at that point in time is expressed by Equation 13 below. It can be predicted as

14A is an example of using an exponential curve to predict the sum of future energy usage, and may be suitably applied, particularly when energy prices are applied as progressive agents. If the sum of the energy use amount is M3 at any point in time t3 in the future, the sum Q3 of energy use at that point in time may be predicted as in Equation 14 below.

Here, the a value may be determined based on the progressive agent or 'dQ / dM' of the energy price.

The predicting means 23 may maintain correspondence information between the sum of the energy use amounts and the sum of the energy use amounts as shown in the examples shown in FIGS. 13 and 14. In addition, if necessary, the prediction means 23 may be input from the central server 11 or the user 10-1.

8B, 9B, 10B, and 11B correspond to FIGS. 2B, 3B, 4B, and 5B, respectively, and when the alternative energy source 14 exists at an energy consumer, the sum of future energy use amounts is It can be shown that the energy consumption at the present time can be reduced.

For example, if the energy is electricity, an alternative source of energy, such as wind turbines or solar power plants, may not be used by the consumer, or may sell electricity to the utility. It may be.

In this case, the energy usage information received from the sensor 13 fluctuates in a direction in which the energy usage decreases, and thus the rate of change of the energy usage amount has a negative slope.

13B and 14B correspond to FIGS. 13A and 14A, respectively, and show that the sum of future energy usage may be reduced because the amount of change in the amount of energy used decreases when an alternative energy source is used at the energy consumer. have.

In the data collection apparatuses 20-1 and 20-2 of the first and second embodiments, the prediction means 23 can not only predict future energy consumption or energy use amount for all energy-using devices, but also sensors. When the energy usage information for each energy use device is received from (13), it is a matter of course that the energy use device can be predicted.

In addition, the prediction means 23 may predict various types of energy usage related information related to future energy usage or energy usage amount.

As a specific example, the prediction means 23 may predict the amount of energy to be actually billed to the user by using the information on the charging policy of the energy supply company 12 as the amount of energy used.

If the energy is electricity, the information about the charging policy of the energy supply company 12 may include information such as basic fees, taxes, power factor rates, and rate benefits that are basically charged. Taxes may include VAT or various funds, and the rate benefit means that certain industries, such as the knowledge services industry, are priced less expensively than other industries.

When the energy price information received from the user 10-1 or the central server 11 follows the progressive system as shown in Table 2 below, a specific example of predicting the amount of energy to be actually charged to the user will be described.

Section 1 Second section Section 3 4th section ... Segment range [Kwh] To 100 101-200 201-300 301-400 ... Unit price (KRW / Kwh) 55.10 113.80 168.30 248.60 ... Base rate (KRW) 370 820 1,430 3,420 ...

The actual charges to be charged to the user are 'electricity charge + surcharge', the electricity charge is 'power consumption × unit price + base charge', the surcharge is 'power industry base fund + VAT', and the electricity industry base fund is electric charge It is assumed that 3.7% of VAT and VAT is 10% of electric bill.

The current date is April 21, 2010, and the electricity bill is due at the end of each month, and the electricity used from April 1 to April 20 collected from the sensor 13 is 230 Kwh, April 19 The electricity consumption of is 218Kwh.

If the predetermined time is one unit (24 hours), the rate of change 'dQ ÷ dt' of energy consumption is 12 Kwh since dQ is 12 Kwh and dt is '1'.

In the case of using the linear relationship shown in FIG. 2A, the remaining days until the end of April are 10 days (April 21 to April 30), and thus the electricity consumption at the future point of April 30 is 350 Kwh. do. This value is calculated as '230 + 12 × 10'.

Since electricity consumption is 350 Kwh, referring to Table 2, the electric charge is calculated as '100 × 55.1 + 100 × 113.8 + 100 × 168.3 + 50 × 248.6 + 3,420'. The final item here is 3,420 won.

That is, the electricity bill is 49,570 won, and the surcharge is 6,791.09 won (calculated as '49, 570 × 0.037 + 49,570 × 0.1 '). Accordingly, the actual amount to be charged to the user is 56,361.09 won.

In this way, you can add basic fees or taxes to predict the actual energy bill you will pay, and a billing policy that calculates the actual bill to be charged to you based on whether your energy source is a home or a company, or other circumstances. May be set in various ways.

Referring to FIG. 15, the data collection apparatuses 20-1 and 20-2 of the first and second embodiments of the present invention include a user interface means 24, a device control means 25, and a transmission means 26. It can be made further comprising a combination of one or more of).

The user interface means 24 allows the user 10-1 to input various information or commands to the data collection devices 20-1 and 20-2 using various input devices such as a keypad or a touch screen.

The user interface means 24 may include a display module to provide a visual interface screen to the user 10-1.

In particular, the user interface means 24 is a mobile terminal number for the user 10-1 to receive information related to energy use, information for determining a situation in which energy use is excessive, and an upper limit value on energy consumption or energy use amount. And various information related to the operation of the data collection devices 20-1 and 20-2, such as a load control schedule for controlling the energy-using device.

In addition, when the second receiving means 22 is configured to receive the energy price information over time from the user 10-1, the user interface means 24 may allow the user to input the energy price information over time. It can be configured to be.

The device control means 25 controls at least one or more energy use devices according to the future energy use or energy use amount predicted by the prediction means 23.

The energy use devices 16-1 to 16-k refer to various devices that consume energy by being located at an energy consumption destination.

The method of controlling the energy-using devices 16-1 to 16-k by the device control means 25 may be variously configured as necessary, and in particular, the control of supplying or blocking energy to the energy-using device may be performed. Can be.

The transmission means 26 transmits information related to energy use to other devices such as the user's mobile terminal 17-1, IHD (17-2: In Home Display), or the central server 11. .

The transmission means 26 may transmit information through various methods such as wired / wireless local area communication, an interface through an internet network, and an interface through a mobile communication network.

FIG. 16 shows specific examples of the data collection apparatuses 20-1 and 20-2 of the first and second embodiments of the present invention.

The processor 160-1 may be configured using a central processing unit (CPU), a microprocessor, or the like. Each of the elements and information may be provided through a system bus 160-10 having various structures. It controls the data collection device 20-1, 20-2 collectively while sending and receiving.

Random Access Memory (RAM) 160-2 as main memory temporarily stores computer programs or data that processor 160-1 will access immediately.

The video adapter 160-4 visually outputs the operation state of the data acquisition device or information to be presented to the user through the display module 160-5, and the display module 160-5 is a liquid crystal display (LCD) or the like. It may have various shapes and structures such as an LED (Light Emitting Diode).

The input device interface 160-6 may allow a user to input information or commands related to operations of the data collection devices 20-1 and 20-2 using various input devices 160-7, such as a keypad or a touch screen. Make sure

The network interface 160-8 allows the data collection apparatuses 20-1 and 20-2 to exchange various information, particularly energy price information, with the central server 11 through a communication network.

In the local communication unit 160-9, the data collection apparatuses 20-1 and 20-2 may include a sensor 13, an energy use device 16-1 to 16-k, a user portable terminal 17-1, and an IHD ( 17-2) It can communicate with various other devices.

Two or more local communication units 160-9 may be provided when it is necessary to communicate with two or more other devices.

Despite its name, the local communication unit 160-9 is configured to communicate with other devices in the vicinity of the energy consumer or to interface with a wide area communication network such as a mobile communication network through wired serial communication, wireless local area communication, and power line communication. Can be.

The storage medium 160-3 stores driving programs necessary for the operations of the data collection devices 20-1 and 20-2 and various kinds of data.

The role of the storage medium 160-3 may be performed by a read only memory (ROM). However, in order to store information that is stored or deleted from time to time and must be maintained regardless of whether power is supplied, reading and writing of digital data is required. It should be as non-volatile as possible. The storage medium may have various structures and performances as necessary, such as internal, external, removable, or non-removable.

The driving program stored in the storage medium 160-3 is a computer program that allows the data collection apparatuses 20-1 and 20-2 to perform their roles.

The driving program may be configured in various ways, and at least of the program module and the second receiving means 22 to enable the data collecting apparatuses 20-1 and 20-2 to serve as the first receiving means 21. Program module to perform a role, and a program module to perform the role of the predicting means (23).

The driving program also serves as a program module and device control means 25 that allow the data collection devices 20-1 and 20-2 to perform the role of the user interface means 24 to interface with the user. It may include a program module to enable, and a program module to perform the role of the transmission means (26).

When the data collection devices 20-1 and 20-2 start operation, the processor 160-1 transfers the driving program stored in the storage medium 160-3 to the main memory device 160-2. And by executing, it controls so that the data collection device 20-1, 20-2 of each embodiment to be described above or described below to perform its role.

16 is only an example for better understanding of the description, and the data collection apparatuses 20-1 and 20-2 according to the present invention may be configured in various ways depending on the embodiments.

FIG. 17 shows an embodiment of a data collection system according to the invention, wherein the data collection system comprises at least a first receiving means 21, a second receiving means 22 and a predicting means 23.

The data collection system may further comprise a combination of one or more of the user interface means 24, the device control means 25 and the transmission means 26.

The first receiving means 21, the second receiving means 22, the predicting means 23, the user interface means 24, the device control means 25, and the transmitting means 26 of the data collection system are separate devices, respectively. It can be configured to operate while exchanging information with each other via the local communication network 18, such as a home network system of the energy consumer.

In addition, one or more roles of the first receiving means 21, the second receiving means 22, the predicting means 23, the user interface means 24, the device control means 25, and the transmitting means 26 of the data collection system. May be configured to perform integrally on a single device.

In the former example, the role of the user interface means 24 may be performed in a personal computer (PC) or digital TV (TV) system connected to the local communication network 18, and the device control means 25 The role of may be a main controller (not shown) of the home network system that integrates and controls the control of each energy-using device 16-1 to 16-k.

The local communication network 18 may be configured using various communication methods such as wired / wireless local area communication or power line communication.

The local communication network 18 is not only meant to be an integrated network connecting each device provided at the energy consumer, but should be understood as a communication network in a comprehensive sense including a network in which each device transmits and receives information individually.

The first receiving means 21 of the data collection system receives the energy-related data from the sensor 13 provided at the energy consumer, the second receiving means 22 from the central server 11 or the user 10-1. Receive energy price information.

The first receiving means 21, the second receiving means 22 and the predicting means 23 of the data collecting system play the same role as that of the data collecting device 20-1 of the first embodiment described above, or Since the data collection device 20-2 of the second embodiment performs the same role as predicting the energy consumption or the amount of energy used in the future, redundant description will be omitted.

Now, embodiments of the user interface means 24, the device control means 25, and the transmission means that can be included in the data collection device and the data collection system according to the present invention will be described.

The device control means 25 controls the supply of energy to at least one energy use device 16-1 to 16-k according to the future energy use or energy use amount predicted by the prediction means 23. do.

Referring to FIG. 18, the device control means 25 determines whether it is necessary to control the energy supply to each energy use device according to the future energy use or energy use amount predicted by the prediction means 23 (S181). ).

If it is determined in step S181 that there is a need for control on the energy-using device (S182), the device control means 25 executes control on the corresponding energy-using device determined to be in need of control (S183).

In operation S 181, the device control means 25 may determine various situations in which it is determined that control of each energy-using device is necessary.

One example is that it is determined that the control of the energy-using device is necessary when the future energy consumption or energy use amount predicted by the predicting means 23 exceeds a preset upper limit value.

In this case, the upper limit value information may be fixed in advance or may be set by the user through the user interface means 24.

In addition, it may be variously configured which energy-using device to control the device control means 25 in step S183.

Referring to FIG. 19, the device control means 25 is information that is fixed in advance or information that can be set by the user through the user interface means 24, and the energy efficiency information for each device, the energy consumption information for each device, and the load. It may be configured to determine which energy-using device to control using device control information such as control schedule information.

As an example, the device control means 25 may preferentially block the supply of energy to energy use devices having poor energy efficiency.

As another example, the device control means 25 may preferentially block the supply of energy to the energy consuming device, which may further reduce the maximum energy usage.

In this case, which energy-using device should be controlled to further reduce the maximum energy consumption may be determined based on energy efficiency of each device or based on energy consumption of each device.

As another example, the device control means 25 may block the supply of energy to each energy use device according to a preset load control schedule. Here, the load control schedule refers to the sequence of energy-using devices to supply or cut off energy.

The energy use devices 16-1 to 16-k controlled by the device control means 25 may be electrical devices, in which case the device control means 25 transmits the device control signals to the power switch device to use each energy. You can control the device.

The power switch device refers to a device capable of turning on / off power input to each energy use device according to a device control signal transmitted from the device control means 25, and may have various structures and shapes.

Referring to FIG. 20A, the power switch device 201 may be configured to have contacts 202-1 ˜ 202-k for connecting or opening a power line 203 drawn into various energy using devices.

The communication unit 201-1 receives the device control signal transmitted by the device control unit 25 and transmits it to the contact driver 201-2, and the contact driver 201-2 transmits the corresponding energy using device according to the device control signal. By connecting or opening the contacts 202-1 to 202-k of each power line 203 drawn in, it is possible to control whether power is supplied to each of the energy using devices 16-1 to 16-k.

Referring to FIG. 20B, the power switch device 205 may include fastening pins 205-1 and 205-2 that may be attached to or detached from the wall outlet 204 or the fasteners 204-1 and 204-2 of the multi-outlet connected to the wall outlet. It may also be configured to have fasteners 205-3 and 205-4 to which the power plug 206 of any energy using device 16-1 can be connected.

The communication unit 205-7 of the power switch device 205 receives the device control signal transmitted by the device control unit 25 and transmits the received device control signal to the contact driver 205-8, and the contact driver 205-8 is a device. According to the control signal, whether or not to supply power to the corresponding energy using device 16-1 may be controlled by connecting or opening the contact 205-6 connected to the corresponding energy using device 16-1.

The structure of the power switch device 205 described with reference to FIG. 20B may be provided inside an individual energy use device.

In order for the device control means 25 to control each energy use device 16-1 to 16-k individually, each contact point 202-1 to 202-k in FIG. 20A or each power switch device 205 in FIG. 20B. It should be possible to know which energy devices are connected.

The method for this purpose may be variously configured, and as an example, the type of energy-using device to be connected to each contact 202-1 to 202-k of FIG. 20A may be defined in advance. As another example, an energy-using device connected to each of the contacts 202-1 to 202-k of FIG. 20A or the power switch device 205 of FIG. 20B can be set by the user through the user interface means 24. have.

The transmission means 26 serves to transmit information related to energy use to another device. The transmission means 26 may be configured in various ways depending on the need for which device to transmit which information in what circumstances. Can be.

Examples of the information to be transmitted by the transmission means 26 include current energy usage information or energy usage amount information, future energy usage information or energy usage amount information predicted through the prediction means 23, and the like.

Current or future energy use information and energy use amount information may be provided as a whole or may be provided for each energy use device.

Such information may be transmitted to the central server 11, the user's mobile terminal 17-1, the IHD 17-2 (In Home Display), and the like.

Another example of information to be transmitted by the transmission means 26 is a warning message.

For example, when the energy usage amount or the energy use amount predicted by the prediction means 23 exceeds the preset upper limit value, a warning message is transmitted to the user's mobile terminal 17-1 or IHD 17-2 (In Home Display). Can be.

Here, the upper limit value is previously defined as an average value or can be set by the user through the user interface means 24. The upper limit value may also be set to an upper limit value at a specific time point or an upper limit value for use during a specific time period.

In the case of the embodiment in which both the device control means 25 and the transmission means 26 are included, the transmission means 26 turns on / off the power of any energy-using device, for example, as a result of the device control means 25 controlling the energy-using device. Information about whether the information is turned off can be transmitted to the central server 11, the user's mobile terminal 17-1, and the IHD 17-2 (In Home Display).

In addition, as described above, the prediction means 23 may maintain information on energy usage or energy use amount for each time period in the past or in the future, and in this case, the transmission means 26 may use energy use amount or energy use amount for each time period. The information can be transmitted to the user's mobile terminal 17-1 or IHD (17-2: In Home Display).

Referring to FIG. 21, a first embodiment of a data collection method according to the present invention will be described.

First, energy-related data including energy usage information is received from at least one or more sensors, and energy price information according to time is received from the central server (S211). At this time, the energy price information over time may be configured to be directly input by the user.

A sensor is a meter that measures energy use. A specific example of the sensor is a smart meter. The energy usage information may be information for each energy use device or may be overall usage information.

In addition, the predetermined sum of energy consumption per hour and the amount of change in energy are grasped, and the rate of change in energy use is calculated (S212).

In step S212, the sum of energy consumption per hour predetermined refers to the sum of energy consumption at each predetermined time.

In other words, if the predetermined time is a unit of time, the sum of energy usage is determined at every hour, and if the predetermined time is a unit of day, the sum of energy usage is determined every day.

Then, the sum of energy use can be used to calculate the change in energy use and the change rate of energy use.

Now, based on the sum of the energy usage calculated in step S212 and the change rate information of the energy usage, the energy usage or the energy usage amount after a predetermined time is predicted (S213).

Here, after a predetermined time refers to a future time point for predicting energy usage or energy use amount, it may be set in units of days, weeks, months, years, etc., or may be set to a specific time point in the future.

An example of a particular point in time of the latter example may be a point in time at which the user is prescribed to pay for energy use, such as the last day of the month.

The method of predicting the future energy usage or the amount of energy used by using the sum of the hourly energy usage and the change rate of the energy usage determined in step S213 may be variously configured.

Specific examples in this regard are the same as those in which the predicting means 23 predicts the future energy consumption or the amount of energy used in the data collection device 20-1 of the first embodiment. Shall be.

In operation S213, as described with reference to FIGS. 2A, 3A, 4A, and 5A, the sum of future energy usage may be estimated using various linear methods or nonlinear methods.

If the sum of future energy use is predicted, the sum of future energy use can be predicted according to the structure of energy price.

If the energy price is fixed, the sum of the predicted energy usage can be multiplied by the energy price to easily predict the future sum of energy use.

However, if the energy price has a variable structure such as a progressive system, time-of-day rate plan, critical peak rate plan, real-time rate plan, or the like, the energy consumption may be reduced by using the method shown in Equation 5 or as described with reference to FIGS. 6 and 7. The correspondence information between the sum and the sum of the energy use amounts can be used to predict the sum.

In addition, when there is an alternative energy source at the energy consumer as shown in FIGS. 8A, 9A, 10A, and 11A, the sum of future energy consumption may be lower than the sum of energy consumption at the present time. Accordingly, the sum of future energy use amounts may also be reduced, as in the examples shown in FIGS. 6B and 7B.

A second embodiment of a data collection method according to the present invention will be described with reference to FIG. 22.

First, energy-related data including energy usage information is received from at least one or more sensors, and energy price information according to time is received from the central server (S221). At this time, the energy price information over time may be configured to be directly input by the user.

A sensor is a meter that measures energy use. A specific example of the sensor is a smart meter. The energy usage information may be information for each energy use device or may be overall usage information.

The sum of the predetermined amount of energy use per hour and the rate of change thereof are calculated (S222).

In step S222, the sum of the predetermined amount of energy use per hour refers to the sum of the amount of energy use at each predetermined time.

That is, if the predetermined time is a unit of time, the sum of the amount of energy used at every hour is grasped.

The rate of change can then be calculated using the sum of the energy usage per hour.

Now, based on the sum of the amount of energy used in step S222 and the change rate information, the energy use amount or the energy use amount after a predetermined time is predicted (S223).

Here, after a predetermined time refers to a future time point for predicting energy usage or energy use amount, it may be set in units of days, weeks, months, years, etc., or may be set to a specific time point in the future.

An example of a particular point in time of the latter example may be a point in time at which the user is prescribed to pay for energy use, such as the last day of the month.

The method of predicting future energy usage or energy usage amount using the sum of the hourly energy usage amount determined in step S223 and the change rate thereof may be variously configured.

Specific examples in this regard are the same as those in which the predicting means 23 predicts the future energy consumption or the amount of energy used in the data collection device 20-2 of the second embodiment. Shall be.

In operation S223, the sum of future energy use amounts may be predicted using various linear methods or nonlinear methods as in the example described with reference to FIGS. 2B, 3B, 4B, and 5B.

When the sum of future energy use amounts is predicted, the sum of energy use can be predicted according to the structure of the energy price.

If the energy price is fixed, it is easy to estimate the future sum of energy use by dividing the energy price by the estimated sum of energy use.

If the energy price has a variable structure such as progressive, time-of-day, critical peak rate, real-time rate, etc., the energy use amount is used as in the example of Equation 12 or described with reference to FIGS. 13 and 14. The relationship between the sum of the sum and the sum of the energy consumption can be used to predict.

In addition, when there is an alternative energy source at the energy consumer, as in the examples shown in FIGS. 8B, 9B, 10B, and 11B, the sum of future energy use amounts may be lower than the sum of energy use amounts at the present time. As a result, the sum of future energy usage may be reduced, as shown in the example of FIGS. 13B and 14B.

The data collection method of the first embodiment and the second embodiment according to the present invention further comprises a device control step of controlling the supply of energy to at least one energy-using device according to the energy usage or energy use amount predicted in steps S213 and S223. It can be made, including.

In addition, the data collection method of the first embodiment and the second embodiment according to the present invention may further comprise a transmitting step for transmitting information related to the use of energy to various other devices.

A specific embodiment relating to the device control step (S233) and the transmission step (S235) will be described with reference to FIG.

First, an apparatus or system operating according to the data collection method according to the present invention provides a user interface for inputting corresponding information according to a user's operation information setting command (S231-1), and the user inputs it through a user interface. The operation information is stored and maintained (S231-2).

The type of information that a user can input through the user interface may be variously configured as necessary.

For example, the mobile terminal to receive the upper limit information on the energy consumption or the amount of energy used as reference information for identifying the state of excessive energy use, the energy efficiency information for each device, the energy consumption information for each device, the load control schedule information, and the warning message. Terminal numbers; and the like.

In the device control step (S233), it is determined whether it is necessary to control the energy supply to each energy-using device according to the future energy usage or energy use amount predicted in step S213 of FIG. 21 or step S223 of FIG. -One).

If it is determined in step S233-1 that there is a need for control on the energy-using device (S233-2), control is performed on the corresponding energy-using device determined to be in need of control (S233-3).

The situation in which step S233-1 determines that control of each energy-using device is necessary may be variously configured.

One example is the determination that control of an energy-using device is necessary when the predicted future energy use or energy use amount exceeds a preset upper limit.

In this case, the upper limit value information may be fixed in advance or may be set by the user through steps S231-1 and S231-2.

In addition, in step S233-3, which energy-using device is to be controlled may be variously configured.

As an example, it is possible to preferentially cut off the energy supply to energy-efficient devices using energy, or to cut off energy supply to energy-using devices that can further reduce the maximum energy usage.

As another example, the energy supply to each energy-using device may be cut off according to a preset load control schedule. Here, the load control schedule refers to the sequence of energy-using devices to supply or cut off energy.

The energy-using device controlled through the device control step S233 may be an electric device. In this case, the device control step S233 may be a power switch device for turning on / off power of the corresponding energy-using device in response to each energy-using device. A method of transmitting a device control signal can be used.

The power switch device may be configured in various ways, an example of which has been described with reference to FIG. 20.

In the transmitting step (S235), the device or system operating in accordance with the data collection method according to the present invention to the other devices, such as the future energy consumption or the amount of energy consumption predicted in step S213 of FIG. 21 or step S223 of FIG. It is determined whether it is necessary to transmit (S235-1).

If it is necessary to transmit the determination result information in step S235-1 (S235-2), the corresponding information is transmitted to various devices such as a central server, a user's mobile terminal, IDH (In Home Display) (S235-3).

In the transmission step (S235) to which device to send what information under what circumstances can be configured in various ways as necessary.

Examples of the information to be transmitted in the transmission step (S235) may include current energy usage information or energy usage amount information, predicted future energy usage information or energy usage amount information, and the like. Current or future energy use information and energy use amount information may be provided as a whole or may be provided for each energy use device.

Such information may be transmitted to a central server, a user's mobile terminal, and an IHD (In Home Display).

Another example of the type of information to be transmitted in the transmission step S235 may be a warning message.

For example, if the future energy consumption or energy use amount predicted in step S213 of FIG. 21 or step S223 of FIG. 22 exceeds a preset upper limit value, a warning message may be transmitted to a user's mobile terminal or an IHD (In Home Display). .

Here, the upper limit value may be defined as an average value in advance, or may be set by the user, and may be set as an upper limit value at a specific time point or an upper limit value for use during a specific period of time.

In addition, in the transmission step (S235), as a result of controlling the energy-using device through the device control step (S233), for example, information on which energy-using device is turned on / off is displayed on the central server, the user's mobile terminal, and the IHD ( In Home Display).

FIG. 25 illustrates an example of a display screen 250 in which electricity usage information is displayed when energy is electricity. The current electricity usage information, current electricity use amount information, estimated electricity use information, and predicted electricity use amount information are present. The amount is displayed in the usage item S250-1, the current charge item 250-2, the estimated usage item 250-3, and the estimated charge item 250-4.

The figures shown are related to the above example, which predicted the actual billing fee to the user as 56,361.09 won, rounded off below the decimal point.

Such a screen may be output from various devices. For example, the mobile terminal 17-1 or the IHD 17-2 of the user who is output through the display module 160-5 of the data collection device shown in FIG. 16 or receives the energy usage information through the transmission means 26. ) May be output.

It is to be understood that the present invention is not limited to the above-described embodiment, and various changes and modifications may be made by those skilled in the art without departing from the technical spirit of the present invention. to be.

11: central server 12: energy supply company
13: sensor 20-1,20-2: data acquisition device
14: Alternative energy sources 16-1 to 16-k: Energy-using devices
17-1: User's Mobile Device 17-2: IHD
18: local communication network 21: first receiving means
22: second receiving means 23: predicting means
24: user interface means 25: device control means
26: transmission means 201, 205: power switch device

Claims (51)

In the data collection device for energy management,
First receiving means for receiving energy related data from at least one sensor;
Second receiving means for receiving energy price information with time from a central server or a user; And
Prediction means for receiving a predetermined sum of energy usage hourly and energy fluctuation usage information from the first receiving means, and receiving energy price information over time from the second receiving means to predict the energy usage or energy use amount after a predetermined time Data collection device comprising a. In the data collection device for energy management,
First receiving means for receiving energy related data from at least one sensor;
Second receiving means for receiving energy price information with time from a central server or a user; And
Receives energy usage information over time from the first receiving means, receives energy price information over time from the second receiving means, calculates a sum of a predetermined amount of energy use per hour, and a change rate thereof, A data collection device comprising prediction means for predicting the energy usage or the amount of energy used. The method according to claim 1 or 2,
The energy collection device, characterized in that any one of electricity, gas, water. The method according to claim 1 or 2,
And the sensor comprises a smart meter. The method according to claim 1 or 2,
And the predicting means predicts the amount of bill to be actually billed to the user using the amount of energy using the information on the billing policy of the company supplying the energy. The method of claim 5, wherein
The energy is electricity,
And the information regarding the charging policy of the company supplying the energy includes information on at least one of a basic fee, a tax, and a fee benefit, which are basically charged at least. The method according to claim 1 or 2,
And a device control means for controlling the supply of energy to at least one energy-using device according to the energy usage or energy use amount predicted by the prediction means. The method of claim 7, wherein
The energy using device is an electric device,
And the device control means transmits a device control signal to a power switch device for turning on / off the power of the corresponding energy using device in response to each of the energy using devices. The method of claim 7, wherein
And said device control means preferentially interrupts the supply of energy to energy-efficient devices having poor energy efficiency. The method of claim 7, wherein
And said device control means preferentially interrupts the supply of energy to energy-using devices which can further reduce the maximum energy usage. The method of claim 7, wherein
And the device control means cuts off energy supply to the energy-using device according to a load control schedule set by a user. The method according to claim 1 or 2,
And a transmission means for transmitting information related to the use of energy to another device. The method of claim 12,
The transmission means is a data collection device, characterized in that for transmitting at least one of the energy usage information and the energy usage amount information predicted through the prediction means to the central server. The method of claim 12,
The transmission means is a data collection device, characterized in that for transmitting at least one of the energy usage information and the energy usage information estimated by the prediction means to the user's portable terminal or IHD (In Home Display). The method of claim 12,
And the transmission means transmits a warning message to a user's mobile terminal or an IHD (In Home Display) when the energy usage amount or the energy usage amount estimated by the prediction means exceeds a preset upper limit value. The method of claim 15,
And the upper limit value is set to an upper limit value at a specific time point or an upper limit value for use during a specific time period. The method of claim 7, wherein
It further includes a transmission means for transmitting information related to the use of energy to other devices,
And the transmitting means transmits at least one of information relating to the result of controlling the energy-using device to at least one of the central server, a user's mobile terminal, and an IHD (In Home Display). In the data collection system for energy management,
First receiving means for receiving energy related data from at least one sensor;
Second receiving means for receiving energy price information with time from a central server or a user; And
Prediction means for receiving a predetermined sum of energy usage hourly and energy fluctuation usage information from the first receiving means, and receiving energy price information over time from the second receiving means to predict the energy usage or energy use amount after a predetermined time Data collection system comprising a. In the data collection system for energy management,
First receiving means for receiving energy related data from at least one sensor;
Second receiving means for receiving energy price information with time from a central server or a user; And
Receives energy usage information over time from the first receiving means, receives price information of energy over time from the second receiving means, calculates a sum of a predetermined amount of energy use per hour, and a change rate thereof, A data collection system comprising prediction means for predicting future energy use or energy use amount. The method of claim 18 or 19,
And said energy is one of electricity, gas, and water. The method of claim 18 or 19,
And the sensor comprises a smart meter. The method of claim 18 or 19,
And the predicting means predicts the amount of bill to be actually charged to the user using the amount of energy using the information on the charging policy of the company that supplies the energy. The method of claim 22,
The energy is electricity,
And wherein the information about the charging policy of the company that supplies the energy includes information about at least one of the basic fees, taxes, and fee benefits that are at least basically charged. The method of claim 18 or 19,
And a device control means for controlling the supply of energy to at least one energy-using device according to the energy usage or energy use amount predicted by the prediction means. The method of claim 24,
The energy using device is an electric device,
And the device control means transmits a device control signal to a power switch device for turning on / off the power of the corresponding energy using device in response to each of the energy using devices. The method of claim 24,
And said device control means preferentially interrupts the supply of energy to energy use devices which are not energy efficient. The method of claim 24,
And said device control means preferentially interrupts the supply of energy to energy-using devices that can further reduce the maximum energy usage. The method of claim 24,
And the device control means cuts off energy supply to the energy-using device according to a load control schedule set by a user. The method of claim 18 or 19,
And a transmission means for transmitting information related to energy use to another device. The method of claim 29,
And the transmission means transmits at least one of energy usage information and energy usage amount information predicted through the prediction means to the central server. The method of claim 29,
The transmission means is a data collection system, characterized in that for transmitting at least one of the energy usage information and the energy usage amount information predicted by the prediction means to a user's portable terminal or an IHD (In Home Display). The method of claim 29,
And the transmission means transmits a warning message to a user's mobile terminal or an IHD (In Home Display) when the energy usage amount or the energy usage amount predicted by the prediction means exceeds a preset upper limit value. 33. The method of claim 32,
And the upper limit value is set to an upper limit value at a specific time point or an upper limit value for use during a specific time period. The method of claim 24,
It further includes a transmission means for transmitting information related to the use of energy to other devices,
And the transmitting means transmits information on the result of controlling the energy-using device to at least one of the central server, a mobile terminal of the user, and an IHD (In Home Display). In the data collection method for energy management,
A first receiving step of receiving energy related data from at least one sensor;
A second receiving step of receiving energy price information according to time from a central server or a user; And
Prediction step of receiving a predetermined sum of energy usage hourly and energy fluctuation usage information from the first receiving step, and receiving energy price information according to time from the second receiving step to predict the energy usage or energy use amount after a predetermined time Data collection method comprising a. In the data collection method for energy management,
A first receiving step of receiving energy related data from at least one sensor;
A second receiving step of receiving energy price information according to time from a central server or a user; And
Receives energy usage information according to time from the first receiving step, receives price information of energy according to time from the second receiving step, calculates a sum of a predetermined amount of energy use per hour, and a change rate thereof, and then sets a predetermined time A data collection method comprising a prediction step of predicting the future energy usage or energy use amount. The method of claim 35 or 36,
And said energy is one of electricity, gas, and water. The method of claim 35 or 36,
And the sensor comprises a smart meter. The method of claim 35 or 36,
The predicting step is a data collection method, characterized in that for predicting the actual billing amount to be billed to the user using the information on the billing policy of the company that supplies the energy. The method of claim 39,
The energy is electricity,
And wherein the information about the charging policy of the company that supplies the energy includes information about at least one of the basic fees, taxes, and fee benefits that are at least basically charged. The method of claim 35 or 36,
And a device control step of controlling an energy supply to at least one energy-using device according to the energy use or energy use amount predicted in the prediction step. 42. The method of claim 41 wherein
The energy using device is an electric device,
And the device control step transmits a device control signal to a power switch device for turning on / off the power of the corresponding energy using device in response to each of the energy using devices. 42. The method of claim 41 wherein
And the device control step preferentially cuts off the energy supply to the energy use device having low energy efficiency. 42. The method of claim 41 wherein
And the device control step preferentially cuts off the energy supply to the energy-using device which can further reduce the maximum energy usage. 42. The method of claim 41 wherein
The device control step of the data collection method, characterized in that to cut off the energy supply to the energy-using device according to the load control schedule set by the user. The method of claim 35 or 36,
And transmitting the information related to the use of energy to another device. The method of claim 46,
The transmitting step is a data collection method characterized in that for transmitting at least one of the energy usage information and the energy usage amount information predicted through the prediction step to the central server. The method of claim 46,
The transmitting step is a data collection method, characterized in that for transmitting at least one of the energy usage information and the energy usage amount information predicted through the prediction step to a user's portable terminal or IHD (In Home Display). The method of claim 46,
The transmitting step is a data collection method, characterized in that for transmitting the warning message to the user's mobile terminal or the IHD (In Home Display) when the energy usage or energy consumption amount predicted in the prediction step exceeds a predetermined upper limit value. The method of claim 49,
And the upper limit value is set to an upper limit value at a specific time point or an upper limit value for use during a specific time period. The method of claim 46,
The transmitting step is a data collection method characterized in that for transmitting at least one of the central server, the user's portable terminal and the IHD (In Home Display) information on the result of controlling the energy-using device.

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