International Journal of Modern Research in Engineering & Management (IJMREM) ||Volume|| 1||Issue|| 4 ||Pages|| 08-16 ||April 2018|| ISSN: 2581-4540
Lighting Control of a Resisdential Building Using Hybrid Occypancy Sensor 1,
Mutiullah Memon, 2, Dr. Faheemullah Shaikh, 3, Dr. Pervez Hameed Shaikh 1, 2, 3,
Student M.E (Electrical Power) IICT, Mehran UET, Jamshoro; Assistant Prof. Electrical Engineering, Mehran UET, Jamshoro.
---------------------------------------------------------ABSTRACT------------------------------------------------The growing development and urbanization has made the alterations in the human life style and comfort requirement particularly in the offices and residential buildings. About 40-45% of world’s energy consumption is being consumed by these buildings and from this portion 20-25% is the share of the lighting loads only. So, the challenge of reduction of energy consumption by the lighting loads is yet to be addressed. Besides, human occupancy pattern and behavior also add to the power consumption. Human comfort and technological advancement is significant but the primary aim of the buildings is just to provide safety and comfort to the occupants. Several lighting control strategies have been employed up to now but among them occupancy detection control techniques are much sophisticated and sensitive in nature. Passive InfraRed (PIR) and Ultra Sonic (US) sensors are widely used for the purpose of occupancy detection because of their fast and robust response. These sensors provide the optimal use of lightings in multi-occupant buildings. This paper is of unique nature because both the sensors PIR and US are used in hybrid arrangement in order to utilize the characteristics of both just to enhance the performance of occupancy detection.
KEYWORDS: Lighting Control, Hybrid Occupancy Sensor, Energy Savings ----------------------------------------------------------------------------------------------------------------------------- ---------Date of Submission: Date, 14 April 2018 Date of Accepted: 19 April 2018 --------------------------------------------------------------------------------------------------------------------------------- ------
I.
INTRODUCTION
Energy Efficiency is becoming the major interest of research in the field of electrical engineering at present. This growing interest in the particular field lead to recognize more effective and smarter means of energy consumption keeping the global environment under consideration. This reduced use of energy means less energy bills, load reduction and above all reduces the environmental stresses. Research shows one third of the world’s energy consumption is shared by the buildings [1]. And among this lighting consumes almost 45% of the total energy consumption and this consumption can be reduced up to 60% by employing some lighting control strategy [2]. So, there is strong need to reduce the consumption of lighting load which in turn reduces the overall energy consumption which is the key factor for engineers at present time. Several methods were used to reduce this factor of energy that includes reduction of rating of lighting loads, reducing the power consumed by such loads, controlling the switching time of such lighting loads based on different approaches. Besides the energy reduction, human comfort has also got the high importance [3] because reducing energy consumption by disturbing the human comfort is not desired. Studies have shown that with the installation of appropriate lighting control techniques sufficient amount of energy can be conserved [4]. Nagy et al used the technique based on occupant centered lighting control and found that almost 13.4% reduction in energy without affecting human comfort [5]. Guo et al worked on the most commonly used sensors i-e PIR and US. After analyzing two different places it was concluded that 19% of the energy was conserved in an office building while 11% was conserved in school building [6]. Manzoor et al also worked on PIR along with RFID sensor to control the usage of lighting loads as well as other HVAC loads. They found almost 13% of power was reduced in a public-sector building and there are further more chances of reduction [7]. Haq et al described that different lighting control strategies or topologies can provide sufficient energy savings that would lead to a reduction in energy demand and would also positively impact on the environment [8]. Yun et al worked on automatic dimming control for lighting and occupancy pattern in order to find out the energy savings. They concluded that almost 43% of lighting consumption can be reduced in offices and by the change of occupancy pattern, the use of lighting loads can be increased by 50%. [9]. Wahl et al worked on PIR based approach to calculate the occupancy pattern and then calculated the energy consumed in an office building. PIR false triggering has been compensated using distributed sensor information [10].
www.ijmrem.com
IJMREM
Page 8
Lighting Control of a Residential Building… Thus, to encourage conservation of energy on artificial lighting use, besides the energy efficient luminaries such as LEDs [11], various control strategies have been designed and proposed. Of which, the technological developments in the arena of information and communication technology, occupancy detection systems are sophisticated and sensitive in nature. In addition, Passive Infrared (PIR) sensors are the dominant detection systems used in buildings for occupancy detection. Moreover, ultrasonic sensors offer additional support for the modern occupancy detection which is capable of providing information on occupant activity, location, number and information related user presence [12]. These developments provide optimal lighting use in multi-occupant buildings. Research shows that there is still potential of work in the field of occupancy sensors in a way that the sensors commonly used i-e PIR and US suffered from some drawbacks of “False off” and “False on” [5,8]. Because of these problems occupants complained about the automated system that within their presence, the lighting loads were switched off and vice versa. These drawbacks created the motivation to work with the same sensors (being simple in operation). Eventually such issues need to be solved in order to provide at most comfort to the occupants. The paper is organized as follows. Section II explains the background Hybrid Occupancy Sensor including the circuit arrangement and operational flow chart. Section II details the case study and hardware implementation of the proposed model. Section IV deals with the results. Finally, the findings and conclusions will be discussed in Section V.
II.
HYBRID OCCUPANCY SENSOR
The word Hybrid means the combination of two things. In this case Hybrid also gives a sense of cascade arrangement. The two conventional occupancy sensors i-e Passive Infra-Red (PIR) and Ultra Sonic (US) are connected in hybrid arrangement in such a way that PIR sensor works as primary occupancy detector giving signal to the US sensor that ultimately triggers the Relay. There are two hybrid circuits containing the PIR and US sensors. Circuit 1 is used to switch ON the lights while circuit 2 is used to switch OFF the lights. These sensors of the two circuits are interfaced with each other through Micro controller using Arduino Programming Software. The circuit arrangement for the hybrid occupancy sensor is shown in Fig. 1. OCCUPANT TIME RECORDER
PIR Sensor
Ultra Sonic (US) Sensor
CONTROL ACTION
LIGHTS ON/OFF
OCCUPANCY COUNTER
Fig. 1 Hybrid Occupancy Sensor The operational flow chart for the proposed model is shown in Fig. 2. As shown in flow chart, the switching of lighting loads will only be performed only if both the sensors are activated. The case, if any of the sensors is not triggered or activated, the relay will be in the same position. In this manner the drawback of both sensors of False off and False on can be removed.
www.ijmrem.com
IJMREM
Page 9
Lighting Control of a Residential Building… START
OCCUPANCY
LOW
PIR 1
PIR 2
HIGH
HIGH
ULTRA SONIC 2
ULTRA SONIC 1
MOTION DETECTION
MOTION DETECTION
NO
YES YES
COUNT NUMBER (2)
NO
COUNT NUMBER (1)
COUNT NUMBER (2)= COUNT NUMBER (1)
HIGH SIGNAL TO REALY
SWITCH ON THE LIGHTS
LOW SIGNAL TO REALY
SWIT CH OFF THE LIGHTS END
Fig. 2 Operational Flow chart of Hybrid Occupancy Sensor III.
CASE STUDY
A residential building with three rooms was taken under consideration in order to implement the proposed circuit. This was to find out the occupancy patterns in all the rooms and finally the energy savings which is the ultimate purpose of this work. The occupancy was under observations from 08:00 AM to 12:00 AM for 16 Hours. After this time period the lights were manually turned off. The Plan view of the residential house under consideration is shown in Fig. 3. The details of the rooms along with the occupancy is drafted in Table 1. The 3D view of a single room along with the lighting loads arrangement is shown in Fig. 4. The arrangement for the lighting loads for the rest of the rooms is same as that of Fig. 4
Fig. 3 Plan view of a residential house www.ijmrem.com
IJMREM
Page 10
Lighting Control of a Residential Building‌
Fig. 4 3D view of a room showing position of lighting loads Table 1 Details of house Location Room 1
Area (ft2) 143
Load (W) 64
No: of occupants 2
Room 2
143
64
3
Room 3
154
64
1
Occupant Type House Members House Members House Members
The lighting load for one single room of a house is 64W. Thus, the overall lighting load of a house (3 rooms) will be 192W (approx.). Fig. 5 shows the hardware model of the hybrid occupancy sensor for plug and play operation and data collection.
Fig. 5 Hardware arrangement of hybrid occupancy sensor
www.ijmrem.com
IJMREM
Page 11
Lighting Control of a Residential Building‌ Fig. 6 and Fig. 7 shows the circuits connected at the exit and entrance of Room 1 respectively.
Fig. 6 Circuit connected at exit of room
Fig. 7 Circuit connected at entrance of room IV.
RESULTS AND DISCUSSIONS
When the Hybrid occupancy sensor circuits were installed at the entrance and exit locations of Room 1, Room 2 and Room 3 individually, the occupancy behavior was observed. The occupancy behavior for the room 1 is shown in Fig. 8. In Fig. 8, the shaded portion shows the time during which the occupancy is present in the room while the unshaded portion indicates the unoccupied room. The detailed occupancy pattern is tabulated in Table 2. In the same way, Fig. 9 and Fig. 10 shows the occupancy behavior in Room 2 and Room 3 respectively. The detailed occupancy pattern for Room 2 and Room 3 is also tabulated in Table 2.
www.ijmrem.com
IJMREM
Page 12
Lighting Control of a Residential Building… Table 2. Details of occupancy (in mins) of Room 1, Room2 & Room3 Room 1
Room 2
17 25 28 32 20 00 16 25 34 00 47 19 19 16 24 24 346
Occupancy No (Mins)
35 49 29 44 32 35 54 53 53 34 24 60 35 60 42 21 660
Occupancy Yes (Mins)
25 11 31 16 28 25 6 7 7 26 36 00 25 00 18 39 300
Occupancy No (Mins)
31 28 23 27 39 32 15 29 00 39 42 42 31 60 12 43 493
Occupancy Yes (Mins)
29 32 37 33 21 28 45 31 60 21 18 18 29 00 48 17 467
Occupancy No (Mins)
Occupancy Yes (Mins)
Period 08:00 to 09:00 09:00 to 10:00 10:00 to 11:00 11:00 to 12:00 12:00 to 13:00 13:00 to 14:00 14:00 to 15:00 15:00 to 16:00 16:00 to 17:00 17:00 to 18:00 18:00 to 19:00 19:00 to 20:00 20:00 to 21:00 21:00 to 22:00 22:00 to 23:00 23:00 to 00:00 Total (Mins)
Room 3
43 35 32 28 40 60 44 35 26 60 13 41 41 44 36 36 614
AVERAGE OCCUPANCY PATTERN IN ROOM 1
OCCUPANCY (NO)
1
0.5
0
TIME (HOURS)
Fig. 8 Average Occupancy Pattern in Room
www.ijmrem.com
IJMREM
Page 13
Lighting Control of a Residential Building…
AVERAGE OCCUPANCY PATTERN IN ROOM 2 OCCUPANCY (NO)
1
0.5
0
TIME (HOURS)
Fig. 9 Average Occupancy Pattern in Room 2
AVERAGE OCCUPANCY PATTERN IN ROOM 3 OCCUPANCY (NO)
1
0.5
0
TIME (HOURS)
Fig. 10 Average Occupancy Pattern in Room 3 From the data tabulated in Table 2, the energy consumption can be calculated with and without hybrid occupancy sensor by taking load of 24W LED bulb only. The energy consumed by each room with and without hybrid occupancy sensor is tabulated in Table 3 and Fig. 11 shows the graphical representation. Table 3. Comparative Energy Consumption with and without hybrid occupancy sensor
1 2 3
Without Occupancy Sensor (kWh/day) 0.384 0.384 0.384
With Occupancy Sensor (kWh/day) 0.186 0.12 0.144
Difference ((kWh/day) 0.198 0.264 0.24
Total
1.152
0.45
0.702
Room
www.ijmrem.com
IJMREM
Change (%) 51.5 68.8 62.5 61
Page 14
Lighting Control of a Residential Building‌
Energy Consumption (kWh/day)
COMPARATIVE AVERAGE ENERGY CONSUMPTION 1.4 1.2 1 0.8 0.6 0.4 0.2 0 Room 1
Room 2
Without Occupancy Sensor
Room 3
Total
With Occupancy Sensor
Fig. 11 Comparative Energy Consumption by the lighting loads in Room 1, Room2& Room 3 and Total Energy Consumption with and without occupancy Sensor
V.
CONCLUSIONS & FUTURE WORK
The paper presented a case study on the Hybrid Occupancy Sensor installed in 3 Rooms of a residential house with a variable number of occupants. The control action was set based on the entrance and exit of the occupant irrespective of fixed time delay or preset time. From the results, we found that both energy consumption and demand can be minimized by introducing hybrid occupancy sensor without having any impact on human comfort. Furthermore, the hindrances in the application of these sensors, false off and false on, have been improvised by using two different circuits for the ON and OFF operation. Other issues, such as the lights being turned OFF in the presence of the occupant in the work place, are also resolved. Future work can also be made so as to increase the sensitivity of the sensors because these sensors are quite sensitive during their operation. Different types of other sensors can also be installed along with PIR and US so as to increase the efficiency of the system. Moreover, the same system may also be used to control the other types of loads like HVAC at residential buildings, at office premises and other public buildings such as shopping malls, apartments, etc. It can be made wireless with the help of advance data acquisition technology like Bluetooth and Wi-Fi. This will avoid the chances of false operation where possible. Along with hardware models, simulation of such systems can be done in order to decrease the chances of false operation. Along with this, Solar Panels can also be incorporated just to supply power to whole lighting system of a building and sensors system.
[1] [2] [3]
[4] [5] [6] [7]
REFERENCES Nagy, Z., Yong, F. Y., & Schlueter, A. (2016). Occupant centered lighting control: a user study on balancing comfort, acceptance, and energy consumption. Energy and Buildings, 126, 310-322. de Bakker, C., Aries, M., Kort, H., & Rosemann, A. (2017). Occupancy-based lighting control in openplan office spaces: A state-of-the-art review. Building and Environment, 112, 308-321.. Meerbeek, B., van Druenen, T., Arts, M., van Loenen, E., & Aarts, E. (2014, November). Impact of blinds usage on energy consumption: automatic versus manual control. In European Conference on Ambient Intelligence (pp. 158-173). Springer, Cham.. Pandharipande, A., & Caicedo, D. (2015). Smart indoor lighting systems with luminaire-based sensing: A review of lighting control approaches. Energy and Buildings, 104, 369-377.. Nagy, Z., Yong, F. Y., Frei, M., & Schlueter, A. (2015). Occupant centered lighting control for comfort and energy efficient building operation. Energy and Buildings, 94, 100-108.. Guo, X., Tiller, D. K., Henze, G. P., & Waters, C. E. (2010). The performance of occupancy-based lighting control systems: A review. Lighting Research & Technology, 42(4), 415-431. Manzoor, F., Linton, D., & Loughlin, M. (2012, September). Occupancy monitoring using passive RFID technology for efficient building lighting control. In RFID Technology (EURASIP RFID), 2012 Fourth International EURASIP Workshop On (pp. 83-88). IEEE..
www.ijmrem.com
IJMREM
Page 15
Lighting Control of a Residential Building‌ [8]
[9] [10]
[11]
[12]
ul Haq, M. A., Hassan, M. Y., Abdullah, H., Rahman, H. A., Abdullah, M. P., Hussin, F., & Said, D. M. (2014). A review on lighting control technologies in commercial buildings, their performance and affecting factors. Renewable and Sustainable Energy Reviews, 33, 268-279. Yun, G. Y., Kim, H., & Kim, J. T. (2012). Effects of occupancy and lighting use patterns on lighting energy consumption. Energy and Buildings, 46, 152-158. Wahl, F., Milenkovic, M., & Amft, O. (2012, December). A distributed PIR-based approach for estimating people count in office environments. In Computational Science and Engineering (CSE), 2012 IEEE 15th International Conference on (pp. 640-647). IEEE. Magno, M., Polonelli, T., Benini, L., & Popovici, E. (2015). A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings. IEEE Sensors Journal, 15(5), 2963-2973.. Labeodan, T., Zeiler, W., Boxem, G., & Zhao, Y. (2015). Occupancy measurement in commercial office buildings for demand-driven control applications—A survey and detection system evaluation. Energy and Buildings, 93, 303-314.
www.ijmrem.com
IJMREM
Page 16