A sensor-less LED dimming system based on daylight harvesting with BIPV systems Seunghwan Yoo,1 Jonghun Kim,1 Cheol-Yong Jang,1 and Hakgeun Jeong1,* 1
Energy Efficiency Department, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon, 305343, South Korea * [email protected]
Abstract: Artificial lighting in office buildings typically requires 30% of the total energy consumption of the building, providing a substantial opportunity for energy savings. To reduce the energy consumed by indoor lighting, we propose a sensor-less light-emitting diode (LED) dimming system using daylight harvesting. In this study, we used light simulation software to quantify and visualize daylight, and analyzed the correlation between photovoltaic (PV) power generation and indoor illumination in an office with an integrated PV system. In addition, we calculated the distribution of daylight illumination into the office and dimming ratios for the individual control of LED lights. Also, we were able directly to use the electric power generated by PV system. As a result, power consumption for electric lighting was reduced by 40 – 70% depending on the season and the weather conditions. Thus, the dimming system proposed in this study can be used to control electric lighting to reduce energy use cost-effectively and simply. ©2013 Optical Society of America OCIS codes: (040.5350) Photovoltaic; (230.3670) Light-emitting diodes; (220.2945) Illumination design; (350.4600) Optical engineering.
References and links 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.
D. Chwieduk, “Towards sustainable-energy buildings,” Appl. Energy 76(1-3), 211–217 (2003). A. M. Omer, “Energy, environment and sustainable development,” Renew. Sustain. Energy Rev. 12(9), 129–163 (2008). L. D. D. Harvey, “Reducing energy use in the building sector: measures, costs, and examples,” Energy Effic. 12, 2265–2300 (2009). C.-H. Tsuei, J.-W. Pen, and W.-S. Sun, “Simulating the illuminance and the efficiency of the LED and fluorescent lights used in indoor lighting design,” Opt. Express 16(23), 18692–18701 (2008). C.-H. Tsuei, W.-S. Sun, and C.-C. Kuo, “Hybrid sunlight/LED illumination and renewable solar energy saving concepts for indoor lighting,” Opt. Express 18(S4 Suppl 4), A640–A653 (2010). S. H. Lee and J. K. Kwon, “Distributed dimming control for LED lighting,” Opt. Express 21(S6), A917–A932 (2013). D. H. W. Li and J. C. Lam, “Evaluation of lighting performance in office buildings with daylighting controls,” Energy Build. 33(8), 793–803 (2001). W. Maranda and M. Piotrowicz, “Application of photovoltaics for daytime indoor lighting,” in Mixed Design of Integrated Circuits and Systems (MIXDES), Proceedings of the 18th International Conference (2011), pp. 529– 532. T. Miyazaki, A. Akisawa, and T. Kashiwagi, “Energy savings of office buildings by the use of semi-transparent solar cells for windows,” Renew. Energy 30(3), 281–304 (2005). D. H. Li, T. N. Lam, W. W. Chan, and A. H. Mak, “Energy and cost analysis of semi-transparent photovoltaic in office buildings,” Appl. Energy 86(5), 722–729 (2009). K. Kapsis and A. K. Athienitis, “Building integrated semi-transparent photovoltaics: energy and daylighting performance,” Proc. SPIE 8007, 800726 (2011). F. Rubinstein, M. Siminovitch, and R. Verderber, “Fifty percent energy savings with automatic lighting controls,” IEEE Trans. Ind. Appl. 29(4), 768–773 (1993). G. F. Min, E. Mills, and Q. Zhang, “Energy efficient lighting in China: Problems and prospects,” Energy Policy 25(1), 77–83 (1997). B. Cook, “High efficiency lighting in industry and commercial buildings,” Power Eng. J. 12(5), 197–206 (1998). T. Taguchi, “Present status of energy saving technologies and future prospect in white LED lighting,” IEEJ Trans. Electr. Electron. Eng. 3(1), 21–26 (2008).
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A132
16. R. P. Leslie, R. Raghavan, O. Howlett, and C. Eaton, “The potential of simplified concepts for daylight harvesting,” Lighting Res. Tech. 37(1), 21–40 (2005). 17. J. T. Kim and G. Kim, “Overview and new developments in optical daylighting systems for building a healthy indoor environment,” Build. Environ. 45(2), 256–269 (2010). 18. M. B. C. Aries and G. R. Newsham, “Effect of daylight saving time on lighting energy use: A literature review,” Energy Policy 36(6), 1858–1866 (2008). 19. C. P. Kurian, R. S. Aithal, J. Bhat, and V. I. George, “Robust control and optimisation of energy consumption in daylight—artificial light integrated schemes,” Lighting Res. Tech. 40(1), 7–24 (2008). 20. G. R. Newsham, M. B. C. Aries, S. Mancini, and G. Faye, “Individual control of electric lighting in a daylight space,” Lighting Res. Tech. 40(1), 25–41 (2008). 21. M. Warren, S. Selkowitz, O. Morse, C. Benton, and J. E. Jewell, “Lighting system performance in an innovative daylighted structure: an instrumented study,” in Proceedings of the 2nd International Daylighting Conference, Long Beach (1986), pp. 21–221. 22. F. Rubinstein, “Photoelectric control of equi-illumination lighting systems,” Energy Build. 6(2), 141–150 (1984). 23. A.-S. Choi, K.-D. Song, and Y.-S. Kim, “The characteristics of photosensors and electronic dimming ballasts in daylight responsive dimming systems,” Build. Environ. 40(1), 39–50 (2005). 24. E. S. Lee, D. L. DiBartolomeo, and S. E. Selkowitz, “Daylighting control performance of a thin-film ceramic electrochromic window: Field study results,” Energy Build. 38(1), 30–44 (2006). 25. H. Yang, G. Zheng, C. Lou, D. An, and J. Burnett, “Grid-connected building-integrated photovoltaics: a Hong Kong case study,” Sol. Energy 76(1-3), 55–59 (2004). 26. U. Herrmann, H. G. Langer, and H. van der Broeck, “Low cost DC to AC converter for photovoltaic power conversion in residential applications,” in 24th Annual IEEE Power Electronics Specialists Conference (1993), pp. 588–594. 27. D. H. W. Li, G. H. W. Cheung, and C. C. S. Lau, “A simplified procedure for determining indoor daylight illuminance using daylight coefficient concept,” Build. Environ. 41(5), 578–589 (2006). 28. L. Svilainis, “LED PWM dimming linearity investigation,” Displays 29(3), 243–249 (2008). 29. Korean Standard Information Centre, http://www.standard.go.kr. Accessed on November 24, 2013.
1. Introduction To reduce carbon emissions and promote green development, the need to reduce energy use in buildings has gradually increased [1–3]. Because 30% of the total energy use in buildings is for electric lighting, this area is an important target for reduction so that we are willing to exchange the present electric lightings with energy favorite LED lightings [4–6]. Also, there has been increasing interest in indoor lighting using daylight, because daylight comes from renewable solar energy and can reduce energy use and provide environmentally friendly lighting [7–11]. In general, indoor lighting is maintained at a constant illumination although the brightness of the external environment changes, using unnecessary electric energy. Many approaches have been attempted to reduce this waste energy in buildings in various fields of the lighting industry [12–15]. Among these approaches are widely used methods for reducing artificial light and saving energy when daylight reaches the windows of buildings, known as daylight harvesting [16–20]. Other popular methods include the use of on/off lighting controls that sense occupancy, and dimming controls that can supply the proper illumination to interior space and reduce excess energy use [21]. However, for both of these methods, many illuminance sensors are needed to control lighting and supply the proper illumination. These illuminance sensors are typically fabricated with cadmium sulfide (CdS), require an additional microcontroller unit (MCU), and the non-linear characteristics of the sensors result in large tolerances, although they are inexpensive and small. Photodiodes fabricated using semiconducting processes are small and have rapid response to changes in light. Nevertheless, these two types of sensors can be greatly influenced by movements of occupants and may malfunction. Many sensors are also needed inside and outside offices or rooms [22–24]. The other effort to reduce the energy use for indoor lighting is to use the photovoltaic system installed outside or on the roof of the office building [25]. This method is good to supply the electric power to operate the indoor lighting, but it should need additional batteries. And, in order to use the electric power generated by the photovoltaic system, the conversion process is needed, including converting DC to AC and AC to DC. These conversion processes could be one of reasons to reduce the efficiency of photovoltaic-based electric power supply system [26].
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A133
Therefore, in this study, we introduce a new approach to controlling electric lighting using daylight harvesting through photovoltaic power generation in office buildings with buildingintegrated photovoltaic (BIPV) systems. The daylight distribution after transmitting through a window shows the exponential decay along the distance from the window so that we can expect the daylight distribution in the office. Also, the amount of daylight coming into the office are closely related to the amount of electric power generated by BIPV. Thus, without any illuminance sensors or photodiodes, artificial lighting in offices can be controlled through prediction of daylight inflow to maximize energy savings. In addition, by directly using the electric power generated by BIPV system, we can also maximize energy savings for indoor lighting because there is no conversion loss of converting DC to AC and AC to DC. For these purposes, we used energy-friendly light-emitting diodes (LED) using the power generated by BIPV systems. To confirm the effectiveness of our new approach, we simulated the dimming control system in a pilot test and calculated energy reduction and the resultant energy savings. 2. Methodology In an office building using photovoltaic power generation, we proposed an alternative artificial lighting control system based on dimming control without additional photo-sensors. As shown in Fig. 1, our novel method is specially designed for office buildings facing to south with integrated photovoltaic power generation systems. Based on the amount of power generated by the Building Integrated Photovoltaic (BIPV) system, we can determine the level of daylight passing through the windows, the daylight distribution inside the office, and calculate the dimming ratio according to our proposed algorithm without the need for photosensors in order to satisfy the minimum indoor illumination.
Fig. 1. Daylight harvesting and dimming control system for indoor lighting in an office building.
Generally, the levels of daylight reaching at the surface of window are varying with respect to the external weather conditions, Clear sky or Overcast sky, and also analogue to the levels at the surface of solar panel. The amount of daylight in clear sky is explicitly larger than that of daylight in overcast sky, but after reaching at the surface of window, the daylight distribution decreases exponentially with respect to the distance from the window [27]. Therefore, we can predict the daylight distribution in the office only with the amount of daylight at the surface of window. In addition, the amount of daylight at the surface of window can be expected by the amount of electric power generated by BIPV system because the amount of daylight outside is closely related to generating electric power of BIPV system. Furthermore, the electric power generated by BIPV system can be used to operate the light-
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A134
emitting diode (LED) lights without any conversion processes, leading to improving the energy savings in terms of energy efficiency. 2.1 Location and experimental configuration The office building modeled and examined in this study was located in central South Korea, specifically in the city of Daejeon. An office building with three floors was used as the research building facing to south, shown in Figs. 2(a) and 2(b). The longitude and the latitude of this building were 36.22°N and 127.22°E. The dimensions of the test office were 4 m wide, 6.5 m long and 2.7 m high.
Fig. 2. General illustration of the pilot test. (a) three-story building facing to south and (b) schematic view of the office.
2.2 Photovoltaic power generation and lighting system We installed photovoltaic power generation consisting of 60 W single-crystal silicon solar cells integrated on the wall of the office building. We used three LED lights in the test office with 52 W rated-power, 48 V differential output voltage, 4000 lm luminous flux, 5700 K color temperature, and more than 77 lm/W of luminous efficiency as shown in Table 1. LED lights have advantages for this light dimming system due to the linearity of their optical power and illumination [28], leading to controlling accurately and maximizing the energy savings. Table 1. Data-sheet of LED lightings used for dimming control Rated Power
Output Voltage
Luminous Flux
Color Temperature
Luminance Efficiency
52 W
48 V
4000 lm
5700 K
77 lm/W
2.3 Correlation between indoor illumination and external photovoltaic power generation In order to obtain the daylight distribution in the office, we first measured the indoor illuminations at different positions (1-6 m from the window) due to the daylight. Figure 3 shows the distribution trend of daylight along the distance from the window.
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A135
Fig. 3. Distribution trend of daylight along the distance from the window after transmitting through the window.
After measuring the daylight distribution, we obtained that the daylight after passing through the window decreased exponentially in Eq. (1).
x ) + α2 (1) 1.09 In Eq. (1), the daylight distribution denoted by y was plotted along the distance from the window, and the constants can be defined as a decreasing factor of daylight along the distance of x. α1 and α2 are dimension-less structural factors coming from the dimension of office. These two structural factor can be obtained simply by experimental measurement with respect to the office structure. Especially, α1 is related to window to wall (WW) ratio. This ratio means the initial value of daylight at the time of passing through the window with respect to the daylight outside. Also, α2 is related to a distance from the window to the wall inside office. In this study, the long of office is 6.5 m from the window. To obtain the correlation between the distribution of daylight in the office and the electric power generated by the BIPV, we monitored indoor illumination during working hours from Feb. 27, 2012 to Mar. 1, 2012. Indoor illumination was measured using an illuminometer 0.75 m above the floor and 6 m from the window as shown in Fig. 4. y = α1 exp(−
Indoor Illumination (lx)
200 180 160 140
50 40 30
120 100
20
80 60
10
40 20
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
External PV Power (W)
Indoor Illumination, Feb 27, 2012 Indoor Illumination, Feb 28, 2012 Indoor Illumination, Feb 29, 2012 Indoor Illumination, Mar 1, 2012 PV Power, Feb 27, 2012 PV Power, Feb 28, 2012 PV Power, Feb 29, 2012 PV Power, Mar 1, 2012
220
0
Time (h) Fig. 4. Correlation between indoor illumination at 6 m from the window (left, colored line) and external PV power (right, dotted line) during working hours from Feb 27, 2012 to Mar 1, 2012.
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A136
Over the working hours measured, photovoltaic power generation varied with the change in indoor illumination from the window. The weather was clear sky (parabolic curves) on Feb. 27, Feb. 29, and Mar. 1 and overcast sky (non-parabolic curve) on Feb. 29. We then calculated the absolute ratio of indoor illumination to the amount of photovoltaic power generation to obtain the conversion factor as shown in Fig. 5, which averaged 4.24. This conversion factor can allow the prediction of illumination one-dimensionally in the office, e.g., at 1, 2, 3, 4, and 5 m, and it is described as Eq. (2). L(x) = P(t) β {α1 exp(−
x ) + α2} 1.09
(2)
where P(t) is the amount of photovoltaic power generation with time, β is the conversion factor, x is the distance from window, and α1 and α2 are structural factors related to test office in this study. 8
Absolute Ratio (Illumination/PV Power)
Conversion Factor = 4.24 6
4
2
0 2 2 2 012 012 201 201 201 1, 2 2, 2 27, 28, 29, r r Feb Feb Feb Ma Ma
Fig. 5. Absolute ratio of indoor illumination 6 m inside the office to photovoltaic power generation outside the office.
For the experimental test of target office in this study, we obtained a conversion factor β of 4.24 and structural factors α1 and α2 of 45.11 and 0.84, respectively. The structural factors vary with the dimensions of the office, the type, direction, and reflectance of the windows, etc. Based on Eq. (2) representing the correlation between photovoltaic power generation and indoor illumination, we were able to predict the indoor illumination from daylight at each point in the office. 2.4 Calculation of the dimming ratio Using the correlation between photovoltaic power generation and indoor illumination at 6 m in the office, we first obtained the equation for indoor illumination due to the daylight distribution in Eq. (2). To calculate the dimming ratio for each of the three LED lights, we obtained the input signal P, which is a power generated by BIPV. And, we also calculated the indoor illumination 0.75 m above the floor at each point corresponding to the lights, i.e., 1 m, 3.7 m, and 6 m away from the window. The expected indoor illumination at each point, Lx, can be obtained using Eq. (3): Lx [lx] = P × 4.24 × {45.11× exp(−
x ) + 0.84} 1.09
(3)
where P is the power generated by the BIPV system at a specific time and x is the distance from the window. Once the indoor illumination at each point was determined, we calculated the dimming ratio for each of the LED lightings by using Eq. (4):
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A137
Dimx [%] =
LR − Lx × 100, LR
(4) if Dim x ≤ 0, then Dim x = 0 and if 0
Energy Efficiency Department, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon, 305343, South Korea * [email protected]
Abstract: Artificial lighting in office buildings typically requires 30% of the total energy consumption of the building, providing a substantial opportunity for energy savings. To reduce the energy consumed by indoor lighting, we propose a sensor-less light-emitting diode (LED) dimming system using daylight harvesting. In this study, we used light simulation software to quantify and visualize daylight, and analyzed the correlation between photovoltaic (PV) power generation and indoor illumination in an office with an integrated PV system. In addition, we calculated the distribution of daylight illumination into the office and dimming ratios for the individual control of LED lights. Also, we were able directly to use the electric power generated by PV system. As a result, power consumption for electric lighting was reduced by 40 – 70% depending on the season and the weather conditions. Thus, the dimming system proposed in this study can be used to control electric lighting to reduce energy use cost-effectively and simply. ©2013 Optical Society of America OCIS codes: (040.5350) Photovoltaic; (230.3670) Light-emitting diodes; (220.2945) Illumination design; (350.4600) Optical engineering.
References and links 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.
D. Chwieduk, “Towards sustainable-energy buildings,” Appl. Energy 76(1-3), 211–217 (2003). A. M. Omer, “Energy, environment and sustainable development,” Renew. Sustain. Energy Rev. 12(9), 129–163 (2008). L. D. D. Harvey, “Reducing energy use in the building sector: measures, costs, and examples,” Energy Effic. 12, 2265–2300 (2009). C.-H. Tsuei, J.-W. Pen, and W.-S. Sun, “Simulating the illuminance and the efficiency of the LED and fluorescent lights used in indoor lighting design,” Opt. Express 16(23), 18692–18701 (2008). C.-H. Tsuei, W.-S. Sun, and C.-C. Kuo, “Hybrid sunlight/LED illumination and renewable solar energy saving concepts for indoor lighting,” Opt. Express 18(S4 Suppl 4), A640–A653 (2010). S. H. Lee and J. K. Kwon, “Distributed dimming control for LED lighting,” Opt. Express 21(S6), A917–A932 (2013). D. H. W. Li and J. C. Lam, “Evaluation of lighting performance in office buildings with daylighting controls,” Energy Build. 33(8), 793–803 (2001). W. Maranda and M. Piotrowicz, “Application of photovoltaics for daytime indoor lighting,” in Mixed Design of Integrated Circuits and Systems (MIXDES), Proceedings of the 18th International Conference (2011), pp. 529– 532. T. Miyazaki, A. Akisawa, and T. Kashiwagi, “Energy savings of office buildings by the use of semi-transparent solar cells for windows,” Renew. Energy 30(3), 281–304 (2005). D. H. Li, T. N. Lam, W. W. Chan, and A. H. Mak, “Energy and cost analysis of semi-transparent photovoltaic in office buildings,” Appl. Energy 86(5), 722–729 (2009). K. Kapsis and A. K. Athienitis, “Building integrated semi-transparent photovoltaics: energy and daylighting performance,” Proc. SPIE 8007, 800726 (2011). F. Rubinstein, M. Siminovitch, and R. Verderber, “Fifty percent energy savings with automatic lighting controls,” IEEE Trans. Ind. Appl. 29(4), 768–773 (1993). G. F. Min, E. Mills, and Q. Zhang, “Energy efficient lighting in China: Problems and prospects,” Energy Policy 25(1), 77–83 (1997). B. Cook, “High efficiency lighting in industry and commercial buildings,” Power Eng. J. 12(5), 197–206 (1998). T. Taguchi, “Present status of energy saving technologies and future prospect in white LED lighting,” IEEJ Trans. Electr. Electron. Eng. 3(1), 21–26 (2008).
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A132
16. R. P. Leslie, R. Raghavan, O. Howlett, and C. Eaton, “The potential of simplified concepts for daylight harvesting,” Lighting Res. Tech. 37(1), 21–40 (2005). 17. J. T. Kim and G. Kim, “Overview and new developments in optical daylighting systems for building a healthy indoor environment,” Build. Environ. 45(2), 256–269 (2010). 18. M. B. C. Aries and G. R. Newsham, “Effect of daylight saving time on lighting energy use: A literature review,” Energy Policy 36(6), 1858–1866 (2008). 19. C. P. Kurian, R. S. Aithal, J. Bhat, and V. I. George, “Robust control and optimisation of energy consumption in daylight—artificial light integrated schemes,” Lighting Res. Tech. 40(1), 7–24 (2008). 20. G. R. Newsham, M. B. C. Aries, S. Mancini, and G. Faye, “Individual control of electric lighting in a daylight space,” Lighting Res. Tech. 40(1), 25–41 (2008). 21. M. Warren, S. Selkowitz, O. Morse, C. Benton, and J. E. Jewell, “Lighting system performance in an innovative daylighted structure: an instrumented study,” in Proceedings of the 2nd International Daylighting Conference, Long Beach (1986), pp. 21–221. 22. F. Rubinstein, “Photoelectric control of equi-illumination lighting systems,” Energy Build. 6(2), 141–150 (1984). 23. A.-S. Choi, K.-D. Song, and Y.-S. Kim, “The characteristics of photosensors and electronic dimming ballasts in daylight responsive dimming systems,” Build. Environ. 40(1), 39–50 (2005). 24. E. S. Lee, D. L. DiBartolomeo, and S. E. Selkowitz, “Daylighting control performance of a thin-film ceramic electrochromic window: Field study results,” Energy Build. 38(1), 30–44 (2006). 25. H. Yang, G. Zheng, C. Lou, D. An, and J. Burnett, “Grid-connected building-integrated photovoltaics: a Hong Kong case study,” Sol. Energy 76(1-3), 55–59 (2004). 26. U. Herrmann, H. G. Langer, and H. van der Broeck, “Low cost DC to AC converter for photovoltaic power conversion in residential applications,” in 24th Annual IEEE Power Electronics Specialists Conference (1993), pp. 588–594. 27. D. H. W. Li, G. H. W. Cheung, and C. C. S. Lau, “A simplified procedure for determining indoor daylight illuminance using daylight coefficient concept,” Build. Environ. 41(5), 578–589 (2006). 28. L. Svilainis, “LED PWM dimming linearity investigation,” Displays 29(3), 243–249 (2008). 29. Korean Standard Information Centre, http://www.standard.go.kr. Accessed on November 24, 2013.
1. Introduction To reduce carbon emissions and promote green development, the need to reduce energy use in buildings has gradually increased [1–3]. Because 30% of the total energy use in buildings is for electric lighting, this area is an important target for reduction so that we are willing to exchange the present electric lightings with energy favorite LED lightings [4–6]. Also, there has been increasing interest in indoor lighting using daylight, because daylight comes from renewable solar energy and can reduce energy use and provide environmentally friendly lighting [7–11]. In general, indoor lighting is maintained at a constant illumination although the brightness of the external environment changes, using unnecessary electric energy. Many approaches have been attempted to reduce this waste energy in buildings in various fields of the lighting industry [12–15]. Among these approaches are widely used methods for reducing artificial light and saving energy when daylight reaches the windows of buildings, known as daylight harvesting [16–20]. Other popular methods include the use of on/off lighting controls that sense occupancy, and dimming controls that can supply the proper illumination to interior space and reduce excess energy use [21]. However, for both of these methods, many illuminance sensors are needed to control lighting and supply the proper illumination. These illuminance sensors are typically fabricated with cadmium sulfide (CdS), require an additional microcontroller unit (MCU), and the non-linear characteristics of the sensors result in large tolerances, although they are inexpensive and small. Photodiodes fabricated using semiconducting processes are small and have rapid response to changes in light. Nevertheless, these two types of sensors can be greatly influenced by movements of occupants and may malfunction. Many sensors are also needed inside and outside offices or rooms [22–24]. The other effort to reduce the energy use for indoor lighting is to use the photovoltaic system installed outside or on the roof of the office building [25]. This method is good to supply the electric power to operate the indoor lighting, but it should need additional batteries. And, in order to use the electric power generated by the photovoltaic system, the conversion process is needed, including converting DC to AC and AC to DC. These conversion processes could be one of reasons to reduce the efficiency of photovoltaic-based electric power supply system [26].
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A133
Therefore, in this study, we introduce a new approach to controlling electric lighting using daylight harvesting through photovoltaic power generation in office buildings with buildingintegrated photovoltaic (BIPV) systems. The daylight distribution after transmitting through a window shows the exponential decay along the distance from the window so that we can expect the daylight distribution in the office. Also, the amount of daylight coming into the office are closely related to the amount of electric power generated by BIPV. Thus, without any illuminance sensors or photodiodes, artificial lighting in offices can be controlled through prediction of daylight inflow to maximize energy savings. In addition, by directly using the electric power generated by BIPV system, we can also maximize energy savings for indoor lighting because there is no conversion loss of converting DC to AC and AC to DC. For these purposes, we used energy-friendly light-emitting diodes (LED) using the power generated by BIPV systems. To confirm the effectiveness of our new approach, we simulated the dimming control system in a pilot test and calculated energy reduction and the resultant energy savings. 2. Methodology In an office building using photovoltaic power generation, we proposed an alternative artificial lighting control system based on dimming control without additional photo-sensors. As shown in Fig. 1, our novel method is specially designed for office buildings facing to south with integrated photovoltaic power generation systems. Based on the amount of power generated by the Building Integrated Photovoltaic (BIPV) system, we can determine the level of daylight passing through the windows, the daylight distribution inside the office, and calculate the dimming ratio according to our proposed algorithm without the need for photosensors in order to satisfy the minimum indoor illumination.
Fig. 1. Daylight harvesting and dimming control system for indoor lighting in an office building.
Generally, the levels of daylight reaching at the surface of window are varying with respect to the external weather conditions, Clear sky or Overcast sky, and also analogue to the levels at the surface of solar panel. The amount of daylight in clear sky is explicitly larger than that of daylight in overcast sky, but after reaching at the surface of window, the daylight distribution decreases exponentially with respect to the distance from the window [27]. Therefore, we can predict the daylight distribution in the office only with the amount of daylight at the surface of window. In addition, the amount of daylight at the surface of window can be expected by the amount of electric power generated by BIPV system because the amount of daylight outside is closely related to generating electric power of BIPV system. Furthermore, the electric power generated by BIPV system can be used to operate the light-
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A134
emitting diode (LED) lights without any conversion processes, leading to improving the energy savings in terms of energy efficiency. 2.1 Location and experimental configuration The office building modeled and examined in this study was located in central South Korea, specifically in the city of Daejeon. An office building with three floors was used as the research building facing to south, shown in Figs. 2(a) and 2(b). The longitude and the latitude of this building were 36.22°N and 127.22°E. The dimensions of the test office were 4 m wide, 6.5 m long and 2.7 m high.
Fig. 2. General illustration of the pilot test. (a) three-story building facing to south and (b) schematic view of the office.
2.2 Photovoltaic power generation and lighting system We installed photovoltaic power generation consisting of 60 W single-crystal silicon solar cells integrated on the wall of the office building. We used three LED lights in the test office with 52 W rated-power, 48 V differential output voltage, 4000 lm luminous flux, 5700 K color temperature, and more than 77 lm/W of luminous efficiency as shown in Table 1. LED lights have advantages for this light dimming system due to the linearity of their optical power and illumination [28], leading to controlling accurately and maximizing the energy savings. Table 1. Data-sheet of LED lightings used for dimming control Rated Power
Output Voltage
Luminous Flux
Color Temperature
Luminance Efficiency
52 W
48 V
4000 lm
5700 K
77 lm/W
2.3 Correlation between indoor illumination and external photovoltaic power generation In order to obtain the daylight distribution in the office, we first measured the indoor illuminations at different positions (1-6 m from the window) due to the daylight. Figure 3 shows the distribution trend of daylight along the distance from the window.
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A135
Fig. 3. Distribution trend of daylight along the distance from the window after transmitting through the window.
After measuring the daylight distribution, we obtained that the daylight after passing through the window decreased exponentially in Eq. (1).
x ) + α2 (1) 1.09 In Eq. (1), the daylight distribution denoted by y was plotted along the distance from the window, and the constants can be defined as a decreasing factor of daylight along the distance of x. α1 and α2 are dimension-less structural factors coming from the dimension of office. These two structural factor can be obtained simply by experimental measurement with respect to the office structure. Especially, α1 is related to window to wall (WW) ratio. This ratio means the initial value of daylight at the time of passing through the window with respect to the daylight outside. Also, α2 is related to a distance from the window to the wall inside office. In this study, the long of office is 6.5 m from the window. To obtain the correlation between the distribution of daylight in the office and the electric power generated by the BIPV, we monitored indoor illumination during working hours from Feb. 27, 2012 to Mar. 1, 2012. Indoor illumination was measured using an illuminometer 0.75 m above the floor and 6 m from the window as shown in Fig. 4. y = α1 exp(−
Indoor Illumination (lx)
200 180 160 140
50 40 30
120 100
20
80 60
10
40 20
9:00
10:00
11:00
12:00
13:00
14:00
15:00
16:00
17:00
External PV Power (W)
Indoor Illumination, Feb 27, 2012 Indoor Illumination, Feb 28, 2012 Indoor Illumination, Feb 29, 2012 Indoor Illumination, Mar 1, 2012 PV Power, Feb 27, 2012 PV Power, Feb 28, 2012 PV Power, Feb 29, 2012 PV Power, Mar 1, 2012
220
0
Time (h) Fig. 4. Correlation between indoor illumination at 6 m from the window (left, colored line) and external PV power (right, dotted line) during working hours from Feb 27, 2012 to Mar 1, 2012.
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A136
Over the working hours measured, photovoltaic power generation varied with the change in indoor illumination from the window. The weather was clear sky (parabolic curves) on Feb. 27, Feb. 29, and Mar. 1 and overcast sky (non-parabolic curve) on Feb. 29. We then calculated the absolute ratio of indoor illumination to the amount of photovoltaic power generation to obtain the conversion factor as shown in Fig. 5, which averaged 4.24. This conversion factor can allow the prediction of illumination one-dimensionally in the office, e.g., at 1, 2, 3, 4, and 5 m, and it is described as Eq. (2). L(x) = P(t) β {α1 exp(−
x ) + α2} 1.09
(2)
where P(t) is the amount of photovoltaic power generation with time, β is the conversion factor, x is the distance from window, and α1 and α2 are structural factors related to test office in this study. 8
Absolute Ratio (Illumination/PV Power)
Conversion Factor = 4.24 6
4
2
0 2 2 2 012 012 201 201 201 1, 2 2, 2 27, 28, 29, r r Feb Feb Feb Ma Ma
Fig. 5. Absolute ratio of indoor illumination 6 m inside the office to photovoltaic power generation outside the office.
For the experimental test of target office in this study, we obtained a conversion factor β of 4.24 and structural factors α1 and α2 of 45.11 and 0.84, respectively. The structural factors vary with the dimensions of the office, the type, direction, and reflectance of the windows, etc. Based on Eq. (2) representing the correlation between photovoltaic power generation and indoor illumination, we were able to predict the indoor illumination from daylight at each point in the office. 2.4 Calculation of the dimming ratio Using the correlation between photovoltaic power generation and indoor illumination at 6 m in the office, we first obtained the equation for indoor illumination due to the daylight distribution in Eq. (2). To calculate the dimming ratio for each of the three LED lights, we obtained the input signal P, which is a power generated by BIPV. And, we also calculated the indoor illumination 0.75 m above the floor at each point corresponding to the lights, i.e., 1 m, 3.7 m, and 6 m away from the window. The expected indoor illumination at each point, Lx, can be obtained using Eq. (3): Lx [lx] = P × 4.24 × {45.11× exp(−
x ) + 0.84} 1.09
(3)
where P is the power generated by the BIPV system at a specific time and x is the distance from the window. Once the indoor illumination at each point was determined, we calculated the dimming ratio for each of the LED lightings by using Eq. (4):
#199889 - $15.00 USD Received 22 Oct 2013; revised 2 Dec 2013; accepted 10 Dec 2013; published 16 Dec 2013 (C) 2013 OSA 13 January 2014 | Vol. 22, No. S1 | DOI:10.1364/OE.22.00A132 | OPTICS EXPRESS A137
Dimx [%] =
LR − Lx × 100, LR
(4) if Dim x ≤ 0, then Dim x = 0 and if 0
