Power consumption monitoring device

Abstract

Even if the consumed power of each device is not measured, it is possible to notify the possibility of a change in the consumed power of each device. The energy saving assistance device has an event occurrence time extracting section that refers to device operation history information included in a reference period and a specified period acquired from a device management device, extracts occurrence times of a prescribed event within the reference period and the object period, respectively; a change degree calculating section that calculates a change degree of a device operation pattern obtained from a distribution of the occurrence times of the prescribed event within the object period with respect to a device operation pattern obtained from a distribution of the occurrence times of the prescribed event within the reference period; and a display control section that prompts information about the change degree to a user.

Description

Technical Field

[0001] This invention relates to a power consumption monitoring device, and more particularly to the detection of changes in power consumption. Background Technology

[0002] In office buildings, energy-saving control plans are sometimes developed by predicting the electricity consumption for the next year based on the past performance of the equipment (such as electricity consumption over the past year and equipment operating history). However, changes to equipment (such as equipment upgrades or changes in operating modes) may lead to changes in electricity consumption and operating modes. Therefore, without reflecting these changes in electricity consumption forecasts, it is sometimes impossible to develop highly accurate energy-saving control plans.

[0003] Therefore, the following technique has been proposed in the past: based on the current waveform and voltage waveform of the power consumed by each device, when the power obtained by estimating the power from the measured value shows a change that is inconsistent with the power consumption pattern that represents the change in power consumption (e.g., Patent Document 1).

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2015-102526

[0007] Patent Document 2: Japanese Patent Application Publication No. 2017-067427

[0008] Patent Document 3: Japanese Patent Application Publication No. 2016-058029

[0009] Patent Document 4: Japanese Patent Application Publication No. 2019-049404

[0010] Patent Document 5: Japanese Patent Application Publication No. 2017-097578

[0011] Patent Document 6: Japanese Patent Application Publication No. 2007-226415

[0012] Patent Document 7: Japanese Patent Application Publication No. 2014-017542

[0013] Patent Document 8: International Publication No. 2017 / 090172 Summary of the Invention

[0014] The problem that the invention aims to solve

[0015] As mentioned above, the power consumption of equipment may also change when the operating mode of the equipment changes. However, in the prior art, in order to identify the changes in the power consumption of each device, it is necessary to be able to measure the power consumption of each device, which incurs the cost of the equipment used for measurement.

[0016] The purpose of this invention is to inform the possibility of changes in the power consumption of each device, even without measuring the power consumption of each device.

[0017] Methods for solving problems

[0018] The power consumption monitoring device of the present invention has a processor that, by referring to the device's operating history information, extracts the occurrence times of predetermined events during a reference period, which serves as a benchmark for analyzing the device's power consumption, and an object period, which serves as the object of analysis. The processor calculates the degree of change of the device's operating mode, obtained based on the distribution of the occurrence times of the predetermined events during the object period, relative to the device's operating mode, obtained based on the distribution of the occurrence times of the predetermined events during the reference period. The processor outputs the calculated degree of change.

[0019] Furthermore, the specified event is when the power supply to the device is turned on or off.

[0020] Furthermore, if the device is an air conditioning unit, the specified event is when the settings of the air conditioning unit are changed to meet the specified occurrence conditions.

[0021] In addition, the processor calculates KL divergence or JS divergence as the degree of change.

[0022] In addition, the processor calculates the KS test statistic or the Anderson-Darling test statistic as the degree of change.

[0023] Furthermore, when multiple events are set as the specified events, the processor calculates the degree of change for each event, weights the calculated degrees of change for each event, and calculates a single degree of change.

[0024] Invention Effects

[0025] According to the present invention, even without measuring the power consumption of each device, it is possible to notify the possibility of changes in the power consumption of each device. Attached Figure Description

[0026] Figure 1 This is a structural block diagram showing the energy-saving auxiliary device in this embodiment.

[0027] Figure 2 This is a hardware structure diagram of the energy-saving auxiliary device in this embodiment.

[0028] Figure 3 This is a flowchart illustrating the energy-saving auxiliary processing in this embodiment.

[0029] Figure 4 It is a graph that uses probability density distribution to show the number of events occurring in each period of the baseline period and the target period in this embodiment.

[0030] Figure 5 It is a graph that uses cumulative probability distribution to show the number of events occurring in each period of the baseline period and the target period in this embodiment.

[0031] Figure 6 This diagram illustrates an example of the display of information related to the degree of change in the prompts given to the user in this embodiment.

[0032] Figure 7 This is another example of how information related to the degree of change in the prompts given to the user is displayed in this embodiment.

[0033] Figure 8 This is another example of how information related to the degree of change in the prompts given to the user is displayed in this embodiment.

[0034] Figure 9 This is another example of how information related to the degree of change in the prompts given to the user is displayed in this embodiment.

[0035] Figure 10 This is another example of how information related to the degree of change in the prompts given to the user is displayed in this embodiment. Detailed Implementation

[0036] The preferred embodiments of the present invention will now be described with reference to the accompanying drawings.

[0037] Figure 1 This is a structural block diagram showing the energy-saving auxiliary device 10 in this embodiment. The energy-saving auxiliary device 10 in this embodiment is one implementation of the power consumption monitoring device of the present invention. It is a device that utilizes the functions of a power consumption monitoring device to provide planners and others with information useful for formulating energy-saving control plans. The energy-saving auxiliary device 10 in this embodiment can be implemented using conventional hardware structures such as personal computers (PCs).

[0038] Figure 2 This is a hardware structure diagram of the computer that forms the energy-saving auxiliary device 10 in this embodiment. For example... Figure 2As shown, the energy-saving auxiliary device 10 is composed of a CPU1, ROM2, RAM3, a hard disk drive (HDD) 4 as a storage unit, a network interface (IF) 5 as a communication unit, and a user interface 6 including input units such as a mouse and keyboard and display units such as a monitor, connected to an internal bus 7.

[0039] Figure 1 Energy-saving auxiliary device 10 and equipment management device 20 are shown. Energy-saving auxiliary device 10 and equipment management device 20 are connected in a communicative manner via a network (not shown).

[0040] The equipment management device 20 collects and manages data from various devices installed in buildings and other facilities, such as air conditioners and lighting equipment, or from sensors corresponding to those devices. The collected data includes information on power on / off status, device status, and setpoints. The collected data is processed appropriately to generate equipment operation history information indicating the operating status of the equipment, which is stored in the equipment operation history information storage unit 21. The equipment operation history information includes the data collection date and time, the corresponding device identification information, device category, data category, status value, setpoint, and measured value.

[0041] The energy-saving auxiliary device 10 analyzes historical equipment operation information to generate planning assistance information, which is provided to users such as planners as auxiliary information to help formulate energy-saving control plans. The energy-saving auxiliary device 10 includes an equipment operation history information acquisition unit 11, an event occurrence time extraction unit 12, a change rate calculation unit 13, and a display control unit 14. Furthermore, structural elements not used in the description of this embodiment are omitted from the accompanying drawings.

[0042] The equipment operation history information acquisition unit 11 acquires equipment operation history information contained in a reference period and a specified period specified by the user from the equipment management device 20. The event occurrence time extraction unit 12, referring to the acquired equipment operation history information, extracts the occurrence times of specified events within the reference period and the target period, respectively. The variation degree calculation unit 13 calculates the variation degree of the equipment operation mode obtained based on the distribution of the occurrence times of specified events within the target period, relative to the equipment operation mode obtained based on the distribution of the occurrence times of specified events within the reference period. The display control unit 14 performs display control on the display to make the variation degree calculated by the variation degree calculation unit 13 visible.

[0043] In this embodiment, the key feature is that, in order to detect changes in power consumption, the operating mode of the equipment during a reference period is used as a benchmark, and an index such as "degree of change" is used to represent how much the operating mode of the equipment has changed during the target period. Therefore, the "reference period" in this embodiment refers to the period during which the operating mode of the equipment is determined as the benchmark for calculating the degree of change. On the other hand, the "target period" is the period during which the operating mode of the equipment is obtained as the object to be compared with the operating mode of the reference period when calculating the degree of change. In other words, the reference period is the period used as a benchmark for analyzing the power consumption of the equipment based on its operating mode. The target period is the period used for analyzing the power consumption of the equipment based on its operating mode.

[0044] Both the reference period and the target period are based on historical equipment operating information, thus indicating they are past periods. Furthermore, in this embodiment, the degree of change in power consumption during the target period relative to the reference period is obtained; therefore, the reference period is considered a past period compared to the target period. For example, if the target period is this week, this month, or this year, the reference period can be set to last week, last month, or last year. Additionally, the reference period and the target period can be discontinuous. For example, if the target period is this month, the reference period can be set to the same month of last year. Moreover, in terms of comparison, it is preferable that the target period has the same length as the reference period; however, it is not necessary to have the same length. For example, the length of each period can be determined according to predetermined period setting conditions, such as periods under specific control and periods without specific control.

[0045] The structural elements 11 to 14 in the energy-saving auxiliary device 10 are realized through the coordinated operation of the computer that forms the energy-saving auxiliary device 10 and the program that operates in the CPU 1 mounted on the computer.

[0046] Furthermore, the program used in this embodiment can be provided by the communication unit, or it can be provided by a computer-readable recording medium such as a CD-ROM or USB memory. The program provided by the communication unit or the recording medium is installed on the computer, and the computer's CPU executes the program sequentially, thereby performing various processes.

[0047] Next, use Figure 3 The flowchart shown illustrates the energy-saving auxiliary processing in this embodiment.

[0048] First, the user inputs a reference period and a target period from the specified period designation screen (not shown) displayed on the energy-saving auxiliary device 10's display, specifying the degree of change in power consumption they wish to confirm. After receiving the reference period and target period specified by the user (step 110), the equipment operation history information acquisition unit 11 acquires the equipment operation history information contained in the reference period and target period from the equipment management device 20 (step 120).

[0049] Next, the event occurrence time extraction unit 12 extracts the occurrence time of the specified events within the reference period and the target period, respectively, by referring to the obtained equipment operation history information (step 130).

[0050] The defined events can be determined based on the categories and values ​​of data contained in the equipment's operating history information. A defined event is, for example, the switching on or off of the equipment's power supply. Specifically, it is a state change such as the power switching from off to on and vice versa. Furthermore, in the case of an air conditioning unit, it is an event where the air conditioning unit's settings are changed in a manner that meets defined occurrence conditions. These defined occurrence conditions include, for example, the air conditioning unit's set temperature increasing or decreasing, or increasing or decreasing by more than a specified temperature (e.g., 2 degrees Celsius or more). Additionally, it could be the air conditioning unit's set temperature being set to 25 degrees Celsius. Similarly, regarding the air conditioning unit's airflow, it could be increased or decreased by more than a specified threshold, or set to a strong setting. By analyzing the equipment's operating history information, the occurrence of the defined events exemplified above can be detected.

[0051] Furthermore, the specified event does not need to be a single event; it can consist of multiple events. However, for comparison purposes, the events to be extracted must be the same in both the baseline and object periods.

[0052] The specified events can be preset. Alternatively, when implementing energy-saving auxiliary processing, they can be specified by the user along with the baseline period and the target period. Furthermore, the user can specify the device that confirms the occurrence of the specified event. Here, it is explained that the device to be processed is embedded in the specified event (for example, set as "Device A is turned on" as the specified event), or it can be limited to one device by user specification, etc.

[0053] Next, the variation calculation unit 13 obtains the distribution of the occurrence times of the extracted events according to the reference period and the target period (step 140).

[0054] Figure 4 It is a graph that uses probability density distribution to show the number of events occurring within each period of the baseline period and the target period. Figure 4In this diagram, the horizontal axis represents time, and the vertical axis represents the probability density distribution. The horizontal axis represents time using a 24-hour day. That is, within each period, the occurrence of events is summed at each moment, and the sum becomes the number of events occurring at that moment. Then, the proportion of the number of events occurring at each moment to the total number of events occurring within that period constitutes the probability density distribution. Therefore, when integrating the probability density distribution over time t (=0~24), the result is 1.0.

[0055] The variation calculation unit 13 can obtain the operating mode of the processing target device based on the distribution of the occurrence times of specified events within the reference period. Figure 4 (The dotted line shown). Similarly, the variation calculation unit 13 can obtain the operating mode in the processing device based on the distribution of the occurrence times of specified events during the object period (as shown by the dotted line). Figure 4 (The solid line shown).

[0056] Next, the variability calculation unit 13 compares the operating modes of each period and calculates the variability of the operating mode corresponding to the target period relative to the operating mode corresponding to the reference period (step 150). In this embodiment, the KL (Kullback-Leibler) divergence of the distribution is calculated as the variability. When the distribution of the occurrence time of events (operating mode) in the reference period is set as p(t), and the distribution of the occurrence time of events (operating mode) in the target period is set as q(t), the variability (KL divergence KL(p||q)) can be calculated using the following formula.

[0057] KL(p||q)=Σ t p(t)log(p(t) / q(t))

[0058] Furthermore, the variability calculation unit 13 can also calculate the JS (Jensen-Shannon) divergence of the distribution as the variability. In this case, the variability (JS divergence JS(p||q)) can be calculated using the following formula.

[0059] JS(p||q)=(KL(p||q)+KL(q||p)) / 2

[0060] In addition, the variability calculation unit 13 can also calculate the KS (Kolmogorov-Smirnov) test statistic of the cumulative distribution as the variability. Figure 5 This is a graph that uses cumulative probability distributions to show the number of events occurring within each period of the baseline and target periods. Figure 5 In the diagram, the horizontal axis represents time, and the vertical axis represents the cumulative probability distribution.

[0061] The variation calculation unit 13 can obtain the operating mode of the processing target device based on the cumulative distribution of the occurrence times of specified events within a reference period. Figure 5 (The dotted line shown). Similarly, the variation calculation unit 13 can obtain the operating mode in the processing device based on the cumulative distribution of the occurrence times of specified events during the object period. Figure 5 (The solid line shown).

[0062] When the cumulative distribution of the occurrence times of events during the baseline period (operation mode) is set as P(t), and the distribution of the occurrence times of events during the target period (operation mode) is set as Q(t), the degree of change (KS test statistic KS(P,Q)) can be calculated using the following formula.

[0063] KS(P, Q) = sup t |P(t)-Q(t)|

[0064] In addition, the Anderson-Darling test statistic can also be calculated as a measure of variability.

[0065] Furthermore, as described above, multiple events can be set as defined events. When multiple events are set, the variation calculation unit 13 calculates the variation degree for each event. Then, by calculating the average, median, maximum, and minimum values ​​of the variation degrees of each event, a single variation degree is calculated for the device. At this time, weighting can also be applied based on the events. For example, events such as turning the device's power on and off have a relatively large impact on power consumption, so they are given a relatively large weight. In addition, events such as raising the temperature setting of the air conditioner by 1 degree have a relatively small impact on power consumption, so they are given a relatively small weight.

[0066] A relatively large variability value indicates that the operating mode of the equipment changes relatively significantly within the target period compared to the operating mode within the baseline period. Changes in operating mode can be caused by variations in the timing and frequency of events. If only the timing of events changes, the frequency remains the same, and therefore, the equipment's power consumption may not change significantly. However, changes in the frequency of events will affect the equipment's power consumption. For example, in the case of an air conditioning unit, an increase in the number of events lowering the set temperature during summer is considered an increase in power consumption. Conversely, an increase in the number of events lowering the set temperature during winter is considered a decrease in power consumption. In this case, the power consumption changes relatively significantly.

[0067] Therefore, if the change in power consumption exceeds a predetermined threshold, the display control unit 14 determines that the power consumption has changed significantly and notifies the user. This allows the user to consider whether the energy-saving control plan needs to be re-evaluated. However, in this embodiment, the change is not limited to the magnitude of the change; when the change calculation unit 13 calculates the change, the display control unit 14 displays information related to the change on the display (step 160).

[0068] Furthermore, the output destination of the information is not limited to the display. For example, the information can be saved to a file and output to a storage unit such as an HDD4 for storage. Alternatively, the information can be sent to other devices via a network. In this embodiment, the display shows the information, so a display control unit 14 is provided; however, it is sufficient to provide an output control unit corresponding to the output destination of the information.

[0069] Figures 6-8 This is a diagram showing an example of information (hereinafter simply "information") related to the degree of change in the prompts given to the user. Figure 6 This shows the probability density distribution of the occurrence time of a power-on event for a certain device (e.g., device A) during both the reference period and the object period. Figure 7 The probability density distributions of the occurrence times of the power-off event of device A are shown for both the reference period and the object period. Figure 8 This shows the cumulative distribution of the occurrence times of the power-on events of device A during both the baseline period and the object period. In each graph, the horizontal axis represents time, as shown below. Figure 4 As explained, it shows 24 hours in a day. Figure 6 , 7 The vertical axis represents the probability density distribution. Figure 8 The vertical axis represents its cumulative distribution.

[0070] Figure 6 The probability distribution is shown by calculating the KL divergence as the degree of variability. Figure 4 The corresponding graph shows the degree of change, allowing the user to understand the extent of the change in power consumption; however, it doesn't specify what kind of change has occurred. Therefore, in this embodiment, as... Figures 6-8 As illustrated, specific changes in operating modes are displayed in a visually recognizable manner.

[0071] also, Figure 9 This is a graph showing an example of how the degree of variation for each device is displayed in the form of a bar chart. (See reference...) Figure 9 The chart shown allows users to see that the operating mode of device B has changed significantly compared to the previous month.

[0072] Figure 10This is a graph showing an example of how heatmaps can be used to illustrate the changes in the degree of change for each device since the previous month. (See reference...) Figure 10 The charts shown allow users to see the extent to which the operating modes of each device have changed compared to the same month last year.

[0073] As explained above, according to this embodiment, information that can assist the user in formulating an energy-saving control plan can be displayed. Therefore, by referring to the displayed information, the user can take measures such as re-evaluating the energy-saving control plan, primarily for equipment with significant variability.

[0074] Label Explanation

[0075] 1: CPU; 2: ROM; 3: RAM; 4: Hard disk drive (HDD); 5: Network interface (IF); 6: User interface (UI); 7: Internal bus; 10: Energy-saving auxiliary device; 11: Equipment operation history information acquisition unit; 12: Event occurrence time extraction unit; 13: Change degree calculation unit; 14: Display control unit; 20: Equipment management device; 21: Equipment operation history information storage unit.

Claims

1. A power consumption monitoring device, characterized in that, The power consumption monitoring device has a processor. The processor, by referring to the device's operating history information, extracts the occurrence times of specified events during both the baseline period (used as a reference for analyzing the device's power consumption) and the object period (the period being analyzed). The processor calculates the degree of change of the device's operating mode, obtained based on the distribution of the occurrence times of the specified events during the object period, relative to the device's operating mode obtained based on the distribution of the occurrence times of the specified events during the reference period. The processor outputs the calculated degree of change. The degree of change is based on the operating mode of the equipment during the baseline period, representing the change in the operating mode of the equipment during the target period. The processor calculates the KL divergence or JS divergence as the degree of change, or the processor calculates the KS test statistic or Anderson-Darling test statistic as the degree of change.

2. The power consumption monitoring device according to claim 1, characterized in that, The specified event is when the power supply to the device is turned on or off.

3. The power consumption monitoring device according to claim 1, characterized in that, In the case that the device is an air conditioning device, the specified event is when the settings of the air conditioning device are changed in a manner that meets the specified occurrence conditions.

4. The power consumption monitoring device according to claim 1, characterized in that, When multiple events are defined as the specified events, the processor calculates the degree of change for each event, weights the calculated degrees of change for each event, and calculates a single degree of change.

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