1. Introduction
According to the U.S. Department of Energy (DOE), about 33% of the entire energy consumption of an office building is consumed by plug loads, which are expected to surge to 49% by 2030 [
1,
2]. In case of an office building, 95% of plug loads are consumed by computers (69%), monitors (9%), and computer peripheral devices (17%), except for severs and air handling units [
3].
In the past, the reduction of plug loads in office buildings was heavily dependent on the improvement of the behaviors of occupants, by raising their awareness about the importance of energy saving [
1,
3,
4,
5]. However, as the dependence on occupants’ behaviors inevitably caused inconvenience to occupants, it was difficult to expect continuous plug load saving effects. In recent years, the standby power off device has been widely used to reduce the unnecessary plug loads of computer peripheral devices of an office building [
1,
3].
However, the standby power off devices can save the plug loads of computer peripheral devices only when occupants turn off the computer; otherwise, it cannot reduce the plug loads. Therefore, the plug load saving effect using the existing standby power off devices was still dependent on occupants’ behaviors, for instance, their awareness to turn off computers. However, office building occupants usually do not pay for energy consumption, and the act of pulling off plugs is often perceived as inconvenience. As a result, unnecessary plug loads are wasted by the current office buildings. Against this backdrop, it is necessary to develop a way of reducing unnecessary plug loads of computers, monitors and computer peripheral devices without being dependent on behavioral tendencies.
2. Limitation of the Conventional Plug Load Saving Strategies
The existing plug load saving measures can be divided into the education-based method (namely, the improvement of the energy saving behavior of occupants), the software-based measures, and the hardware-based method [
3].
The education-based method aims at improving the energy saving behavior of the occupants, and has its own advantages; it does not incur any additional costs and can be applied to most of the plug-in devices. It involves turning off the unnecessary devices or pulling out the plugs whenever an occupant moves to another place. However, this inevitably causes inconvenience to the occupants, and energy saving is too much dependent on the behaviors of occupants to expect a continuous energy saving effect.
Although the software-based method that can be remotely controlled by a building superintendent does not incur additional costs, it cannot control computer peripheral devices, and a remote-control software needs to be installed to enable users to remotely control computers and monitors from a personal computer. Also, as it can terminate the operation of a computer or a monitor, it is likely to cause inconvenience to occupants.
The hardware-based method is to use a standby power off device or to replace the existing plug-in device with a highly efficient one. The mechanisms of standby power off devices can be divided into the scheduling-based method and the standby power detection and cut-off method.
The scheduling-based method is to connect plug-in devices with schedulers to a standby power off device, and to adjust the scheduler setting of the standby power off device to allow the plug-in devices to automatically go off. The method is effective in reducing the plug loads of the plug-in devices with built-in schedulers. However, it cannot respond to the irregular use of plug-in devices by the occupants.
The power detection & standby power-off method is to connect the power cable of a computer to the master outlet of the standby power-off device and computer peripheral devices to the controlled outlets. After the standby power-off device is installed, if an occupant turns off the computer, the standby power of the computer peripheral devices is automatically discontinued, or when an occupant turns on the computer, the power is supplied to computer peripheral devices. This method is effective in cutting off standby power. However, the reduction of plug loads is dependent on the occupant’s act of turning off the power of the computer.
The replacement method is to preplace a low efficient device with a high efficient device to save plug loads. This method is expected to achieve a higher energy saving efficiency than any other method, but the replacement method is not cost-efficient in most cases.
To make up for the shortcoming of the existing plug load reduction methods which are overly dependent on behavioral tendencies, the development of occupant-based plug-in controls is in a great demand in recent years [
1,
4,
6]. The occupant-based plugin device control is to collect real-time information about the presence or absence of occupants and, based on the occupant information, to control the plug-in devices.
Harris
et al. [
7] proposed a method of controlling computers and monitors through the bluetooth of smartphones after installing an occupant-based plugin device control software in a computer. However, as bluetooth consumes a greater amount of battery than Wifi, it is not widely used. Also, the study by Harris did not include the controlling of computer peripheral devices.
In a study by Ken Christensen
et al. [
8], computers, monitors, and computer peripheral devices were connected to the standby power-off device, a control software was installed in a computer, while a control application was installed in a smartphone. Subsequently, the computers, monitors, and computer peripheral devices were controlled through the Wifi of the smartphone. When an occupant left the office room for a short period of time, the monitor would go off and the standby power of computer peripheral devices would be cut off. Also, the monitors and computer peripheral devices are turned off right before the occupant enters the office room. Therefore, a plug load saving effect can be achieved while minimizing the inconvenience of the occupant. However, in the study by Ken Christensen
et al., the computer was always turned on even when the occupant was absent for a short period, and an analysis on plug in saving quantities was not conducted. Also, another disadvantage is that the occupant, who was not obliged to pay for energy consumption, had to experience the inconvenience of installing an application in the smartphone.
The purpose of the study is to develop a new mechanism to control computers, monitors, and computer peripheral devices according to information about the presence or absence of occupants, using the Wifi and a standby power cutoff device, and installing a control software in a computer, but without the installation of an application in a smartphone. To this end, this study developed an occupant-based plug-in control software and analyzed plug load saving rates through an experiment.
5. Results and Discussion
To confirm the accuracy of the occupancy OBC-P software, experiments of the case of leaving the room and the case of occupying the room with a smart phone were performed 20 times, respectively. As a result of 100% accuracy, plug-in devices have been activated before the occupants occupy the room and deactivated after the occupants are out.
Figure 16,
Figure 17,
Figure 18,
Figure 19,
Figure 20 and
Figure 21 show the results of the experiment on the occupant-based plug-in device control, which was conducted by targeting a total of 10 occupants for two weeks. The baseline system was set as follows: after occupants came to work, they turned on plug-in devices, such as computers, monitors and computer peripheral devices; during the short leave period, they did not control the plug-in devices; when they went to home, they turned off the plug-in devices.
Figure 16 shows the plug load of Occupant A on Wednesday. Occupant A came to work at around 10 A.M. and went to home at around 2 P.M., and there were five short leaves between the clock-in time and the clock-out time. When Occupant A used the occupant-based plug in device control, the plug-in devices were automatically controlled during the short leave period, and as a results, unnecessary plug loads were reduced. When the occupant set the control to the Awake mode, it could reduce the plug loads by 10.2%, compared to the baseline system. In case of the Sleep mode, it can save the plug loads by 18.2%.
Figure 17 shows the total occupied time of Occupant A for two weeks and the plug load quantities. In case of Occupant A, the short leave period and the period from the clock-out time to the next clock-in time varied widely depending on the day of the week, and the plug load quantities changed accordingly. In most cases, a longer unoccupied time means a smaller plug load quantity. However, in cases where the unoccupied time was similar (Tuesday, Wednesday and Thursday of the second week), the plug load quantity in the Awake mode was decreased when the period from the clock-in time to the next clock-out time was increased. In the Sleep mode, when the unoccupied time was increased, the plug load quantity was decreased. These results show the differences in plug load quantities depending on the control mode during the short leave period, as seen in
Figure 16.
Figure 18 shows the plug loads of Occupant A by the unoccupied hours for two weeks. On Saturdays and Sundays, the occupant did not come to work, so the plug log quantity was the same. Except for Saturdays and Sundays, the unoccupied time varied depending on the day of the week. When the unoccupied time was increased, the plug load quantity was decreased. Also, in case that the unoccupied time was the same, the Sleep mode had the greatest plug load saving, followed by the Awake mode and the baseline system. In case of the baseline system, the plug load quantity was increased in some cases, even though the unoccupied time was increased (
).
In contrast, the Awake mode showed a more remarkable decreasing in the plug load quantity than the baseline system, when the occupied time increased (
). In the Sleep mode, an increase in the unoccupied time always led to a decrease in the plug load quantity (
). The varying results of the Awake mode and the Sleep mode can be ascribed to differences in the short leave period and the unoccupied period from the clock-out time to the next clock-in time, as seen in
Figure 16. In other words, the Awake mode used a plug load of 94.34 W during the short leaves of occupants and a plug load of 2.39 W for an unoccupied period from the clock-out time to the next clock-out time. In contrast, the Sleep mode consumed a plug load of 4.05 W during the short leave of occupants, and used a plug load of 2.39 during a period when all the plug-in devices were deactivated by occupants. Therefore, the use of the Sleep mode enables the reduction of plug loads in proportion to the unoccupied time.
Figure 19 shows the plug load by hour during the unoccupied period of Occupant A and Occupant B. Even though Occupant A and Occupant B had similar unoccupied periods of time, their normal use power consumption and standby power consumption of computers, monitors and computer peripheral devices were different, and their short leave period and their unoccupied period from the clock-out time to the next click-in time were also different, leading to differences in the plug load quantities among occupants.
Figure 20 shows the plug load saving rates of 10 occupants during the weekday depending on the varying control modes. The Awake mode had the daily minimum plug load saving rate of 1.39%, the daily maximum plug load saving rate of 39.80%, and the average plug load saving rate of 18%. The Sleep mode saves a daily minimum plug load of 1.55%, the daily maximum plug load of 65.76%, and the average plug load of 26.93%. The reason why the Sleep mode had a higher average plug load saving rate than the Awake mode was that occupants additionally controlled the computer to the power save mode when they left the rooms for short leave.
Figure 21 shows the comparison of plug load quantities when 10 occupants used the occupant-based plug-in device control for two weeks. The Awake mode had a higher plug load saving rate by about 15% than the baseline system, while the Sleep mode could reduce the plug loads by about 26% compared to the baseline system.
6. Conclusions and Future Directions
This study was conducted to develop a way of reducing unnecessary plug loads while minimizing the inconvenience of occupants by using an occupant-based automatic control of computers, monitors and computer peripheral devices, all of which account for approximately 95% of plug loads of an office building. To this end, the study developed the OBC-P software which uses the Wifi of smartphones and standby power cutoff devices. The OBC-P software collects information about occupants who are connected to the AP administration page through the Wifi, and based on this information, it controls the power on/off of computers and monitors, while a standby power cutoff device is used to control the power of computer peripheral devices. In order to measure the plug load saving rate in case of the use of the occupant-based plug-in device, the experiment was conducted targeting 10 occupants in three research labs of the graduate school for two weeks. The results of the study can be summarized as follows:
- (1)
When an occupant went out for a short break, the Awake mode automatically switched the main monitor to the standby mode and interrupted the supply of standby power to computer peripheral devices. Also, it reactivated the main monitor and computer peripheral devices right before the occupant returned to the room. The Awake mode could reduce the plug loads of computers, monitors, and computer peripheral devices by 15% compared to the baseline system.
- (2)
When an occupant left the room for a short period of time, the Sleep mode automatically switched the main monitor to the standby mode and interrupted the supply of standby power to computer peripheral devices. Thus, since it switched the computer to the saving mode, more plug loads could be saved than with the Awake mode. However, the computer, main monitor and computer peripheral devices were reactivated only when the occupant moved the mouse or touched the keyboard button. The Sleep mode could reduce the plug loads of computers, monitors, and computer peripheral devices by 26% compared to the baseline system.
This study has its limitations. Some test subjects likely felt that the computer gets slow when they run OBC-P software for a long time (10 h or more). It is estimated to be associated with the performance of the computer. It was difficult to collect correct information about the presence or absence of occupants, with increasing distance between the occupants and their smartphones. Also, when an occupant was within the range to the wireless access point but had left his or her workspace, the plug-in devices were not controlled. Further studies need to be conducted using a sensor which can locate the position of those occupants who are not connected to the access point through the Wifi. In addition, when the occupant's smart phone is connected to the other Wifi access point in the adjacent area, it will have to be added, the algorithm for determining the occupied or not.