# Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation

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## Abstract

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## 1. Introduction

_{f}), perimeter floor area (A

_{p}), which is a measure of the daylit floor space, and total window glazing area (A

_{w}). Using the building simulation tool DOE-2.1, the researchers modeled these parameters as well as lighting installations. A daylight-linked dimming system was also modeled, which maintained 500 lx illuminance on the workplane. The authors also modeled shading for the windows to prevent excessive heating. The simulation tool gives annual energy saving results in terms of percentage. To establish a relationship between savings percentage and the room parameters, the authors varied the values of two ratios. The ratio A

_{w}/A

_{p}is an indicator of the size of the window to the area of the floor that is lit by daylight, while A

_{p}/A

_{f}indicates the size of the daylit area relative to the total area of the floor. The visible transmittance of the window (${\tau}_{w}$) also plays a role in daylight penetration. The aforementioned ratios were varied for different values of ${\tau}_{w}$ and the energy savings were calculated for each case from the DOE-2.1. The resultant curves were used by the researchers to develop a mathematical equation that relates the parameters with the percentage of energy savings${f}_{d}$, as given by Equation (1).

## 2. Methodology

#### 2.1. Development of the Proposed Method

- (1)
- Identification of simulation setup: The simulation software is required to model a room and obtain daylight illuminance predictions for the room. There are several criteria that are required from the software that will be used. At first, these requirements were identified. Then, the available software options were explored to find the software that meets the requirements.
- (2)
- Simulation of a test case and comparative case: Two separate cases were simulated. The first case is the test case, which represents a small private office. The second case is the comparative case. This room was developed based on the case of a previous study, for the purpose of comparison.
- (3)
- Development of the new method: The exact steps for the calculations in this proposed method were thoroughly developed and articulated. The parameters used for the method and the equations were clearly defined.
- (4)
- Finally, the calculation steps of the new method were applied to the test case and the comparative case. The calculations were performed using the data obtained from the simulation of the two cases. The final results from the test case gave the potential of annual energy savings from a small, model office room. The comparative case results provided a comparison between the results from a previous method and the new method.

#### 2.2. Identifying the Simulation Platform

## 3. Description of the Proposed Method

#### 3.1. Step 1–General Dimming

_{TI}) and the Initial Surrounding Area Lamps Load (P

_{SI}). For a simple case, these values can be calculated by assigning two groups of the installed luminaire as contributing to the task area and the surrounding area. If the number of luminaires contributing to the task area is N

_{T}and the number of luminaires contributing to the surrounding area is N

_{S}and if the load per installed luminaire is P

_{L},

#### 3.2. Step 2–Frequency Distribution

#### 3.3. Step 3–Daylight Dimming

#### 3.4. Step 4–Energy Calculations

_{D}, the Total Working Hours Per Year is simply,

## 4. Results from the Test Case

_{I}is the Total Initial Annual Energy Consumption, E

_{G}represents the Total Annual Energy Consumption after applying general dimming. E

_{DT}gives the Total Annual Energy Consumption at Task Area after daylight dimming, while E

_{DS}is the Total Annual Energy Consumption at Surrounding Area after applying daylight dimming. Then, E

_{D}gives the value of Total Annual Energy Consumption, calculated after applying the previous steps. Finally, the Energy Saving Potential from Daylight Utilization is given by S. All the energy values are given in Kilo Watt Hours (kWh).

## 5. Comparative Case Results

_{I}is the Total Initial Annual Energy Consumption, E

_{G}represents the Total Annual Energy Consumption after applying general dimming. E

_{DT}gives the Total Annual Energy Consumption at Task Area after daylight dimming, while E

_{DS}is the Total Annual Energy Consumption at Surrounding Area after applying daylight dimming. Then, E

_{D}gives the value of Total Annual Energy Consumption, calculated after applying the previous steps. Finally, the Energy Saving Potential from Daylight Utilization is given by S. All the energy values are given in Kilo Watt Hours (kWh).

_{G}), the initial energy consumption (E

_{I}) was used as the benchmark. In addition, since the separation of the task and surrounding areas was also introduced in the proposed method, this separation was not considered for the purpose of comparison. Hence, the required illuminance levels should be the same for both the task and surrounding areas (500 lx). The illuminance level predictions were considered only for the task area and considered to be the same for the whole workplane. Similarly, the distribution of the daylight levels into three ranges was not considered, and the values for the three ranges were considered to be the same. This means that the low, medium, and high daylight illuminance levels were the same for both the task and surrounding areas, and the value of which will be the average illuminance level of the task area (266 lx). This also means that the distribution of daylight penetration for the three ranges should be all equal, i.e., 33%.

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Nomenclature

Symbol | Name of the Parameter |

A_{f} | Total Floor Area |

A_{p} | Perimeter Floor Area |

A_{w} | Total Window Glazing Area |

${\tau}_{w}$ | Visible Transmittance Of The Window |

${f}_{d}$ | Percentage Of Energy Savings |

P_{TI} | Initial Task Area Lamps Load |

P_{SI} | Initial Surrounding Area Lamps Load |

N_{T} | Number Of Luminaires Contributing To The Task Area |

N_{S} | Number Of Luminaires Contributing To The Surrounding Area |

P_{L} | Load Per Installed Luminaire |

${P}_{I}$ | Total Installed Initial Lamps Load |

${L}_{TI}$ | Initial Lamps Illuminance Level For The Task Area |

${L}_{SI}$ | Initial Lamps Illuminance Level For The Surrounding Area |

${L}_{T}$ | Required Illuminance Level For The Task Area |

${L}_{S}$ | Required Illuminance Level For Surrounding Area |

${F}_{RT}$ | Power Reduction Factor For Task Area |

${F}_{RS}$ | Power Reduction Factor For Surrounding Area |

${P}_{T}$ | Current Task Area Lamps Load |

${P}_{S}$ | Current Surrounding Area Lamps Load |

${P}_{G}$ | Total Installed Lamp Load After General Dimming |

${L}_{T,LD/L}$ | Task Area Low D/L Average Illuminance Level |

${L}_{T,MD/L}$ | Task Area Medium D/L Average Illuminance Level |

${L}_{T,HD/L}$ | Task Area High D/L Average Illuminance Level |

${L}_{S,LD/L}$ | Surrounding Area Low D/L Average Illuminance Level |

${L}_{S,MD/L}$ | Surrounding Area Medium D/L Average Illuminance Level |

${L}_{S,HD/L}$ | Surrounding Area High D/L Average Illuminance Level |

${F}_{LT}$ | Task Area Annual Low D/L Penetration % |

${F}_{MT}$ | Task Area Annual Medium D/L Penetration % |

${F}_{HT}$ | Task Area Annual High D/L Penetration % |

${F}_{LS}$ | Surrounding Area Annual Low D/L Penetration |

${F}_{MS}$ | Surrounding Area Annual Medium D/L Penetration |

${F}_{HS}$ | Surrounding Area Annual High D/L Penetration |

${L}_{T,L}$ | Low D/L Lux Level Required At Task Area |

${L}_{T,M}$ | Medium D/L Lux Level Required At Task Area |

${L}_{T,H}$ | High D/L Lux Level Required At Task Area |

${L}_{S,L}$ | Low D/L Lux Level Required At Surrounding Area |

${L}_{S,M}$ | Medium D/L Lux Level Required At Surrounding Area |

${L}_{S,H}$ | High D/L Lux Level Required At Surrounding Area |

${F}_{RT,LD/L}$ | Low D/L Power Reduction Factor At Task Area |

${F}_{RT,MD/L}$ | Medium D/L Power Reduction Factor At Task Area |

${F}_{RT,HD/L}$ | High D/L Power Reduction Factor At Task Area |

${F}_{RS,LD/L}$ | Low D/L Power Reduction Factor At Surrounding Area |

${F}_{RS,MD/L}$ | Medium D/L Power Reduction Factor At Surrounding Area |

${F}_{RS,HD/L}$ | High D/L Power Reduction Factor At Surrounding Area |

${P}_{T,LD/L}$ | Low D/L Task Area Load |

${P}_{T,MD/L}$ | Medium D/L Task Area Load |

${P}_{T,HD/L}$ | High D/L Task Area Load |

${P}_{S,LD/L}$ | Low D/L Surrounding Area Load |

${P}_{S,MD/L}$ | Medium D/L Surrounding Area Load |

${P}_{S,HD/L}$ | High D/L Surrounding Area Load |

D | Annual Working Days |

T_{D} | Daily Working Hours |

${T}_{A}$ | Total Working Hours Per Year |

${T}_{LT}$ | Low D/L Working Hours At Task Area |

${T}_{MT}$ | Medium D/L Working Hours At Task Area |

${T}_{HT}$ | High D/L Working Hours At Task Area |

${T}_{LS}$ | Low D/L Working Hours At Surrounding Area |

${T}_{MS}$ | Medium D/L Working Hours At Surrounding Area |

${T}_{HS}$ | High D/L Working Hours At Surrounding Area |

${E}_{I}$ | Total Initial Annual Energy Consumption |

${E}_{G}$ | Total Annual Energy Consumption After General Dimming |

${E}_{DT}$ | Total Annual Energy Consumption At Task Area (With Daylight Dimming) |

${E}_{DS}$ | Total Annual Energy Consumption At Surrounding Area (With Daylight Dimming) |

${E}_{D}$ | Total Annual Energy Consumption |

$S$ | Energy Saving Potential From Daylight Utilization |

lx | Unit of illuminance level, lux |

m | Unit of distance, meter |

m^{2} | Unit of area, square meters |

kWh | Unit of electrical energy, Kilo Watt Hours |

## References

- Price, L.; Levine, M.D.; Zhou, N.; Fridley, D.; Nathniel, A.; Lu, H.; McNeil, M.; Zheng, N.; Qin, J.; Ping, Y. Assessment of China’s energy-saving and emission-reduction accomplishments and opportunities during the 11th Five Year Plan. Energy Policy
**2011**, 39. [Google Scholar] [CrossRef] [Green Version] - Mills, B.; Schleich, J. Residential energy-efficient technology adoption, energy conservation, knowledge, and attitudes: An analysis of European countries. Energy Policy
**2012**, 49. [Google Scholar] [CrossRef] - Cai, W.; Lai, K.-H.; Liu, C.; Wei, F.; Ma, M.; Jia, S.; Jiang, Z.; Lv, L. Promoting sustainability of manufacturing industry through the lean energy-saving and emission-reduction strategy. Sci. Total Environ.
**2019**, 665. [Google Scholar] [CrossRef] [PubMed] - Tanaka, K. Review of policies and measures for energy efficiency in industry sector. Energy Policy
**2011**, 39. [Google Scholar] [CrossRef] - US Department of Energy. Buildings Energy Data Book. Available online: http://buildingsdatabook.eren.doe.gov/DataBooks.aspx (accessed on 29 August 2013).
- Li, D.H.W.; Cheung, K.L.; Wong, S.L.; Lam, T.N.T. An analysis of energy-efficient light fittings and lighting controls. Appl. Energy
**2010**, 87, 558–567. [Google Scholar] [CrossRef] - Martirano, L. A smart lighting control to save energy. In Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, Prague, Czech Republic, 15–17 September 2011; pp. 132–138. [Google Scholar]
- Energy Saving Trust. Energy Efficient Lighting—Guidance for Installers and Specifiers; Energy Saving Trust: London, UK, 2006; Volume CE61. [Google Scholar]
- Khan, N.; Abas, N. Comparative study of energy saving light sources. Renew. Sustain. Energy Rev.
**2011**, 15, 296–309. [Google Scholar] [CrossRef] - Ul Haq, M.A.; Hassan, M.Y.; Rahman, H.A.; Abdullah, H.; Abdullah, M.P.; Hussin, F.; Bandi, M. Energy saving in lighting from T5 lamp retrofit—A case study. In Proceedings of the 2013 IEEE Student Conference on Research and Development, Putrajaya, Malaysia, 16–17 December 2013. [Google Scholar]
- Ul Haq, M.A.; Hassan, M.Y.; Abdulah, H.; Rahman, H.A.; Abdulah, M.P.; Hussin, F.; Said, D.M. A review on lighting control technologies in commercial buildings, their performance and affecting factors. Renew. Sustain. Energy Rev.
**2014**, 33, 268–279. [Google Scholar] [CrossRef] - Williams, A.; Atkinson, B.; Garbesi, K.; Page, E.; Rubinstein, F. Lighting Controls in Commercial Buildings. LEUKOS
**2012**, 8, 161–180. [Google Scholar] [CrossRef] - Li, D.H.W.; Lam, J.C. Evaluation of lighting performance in office buildings with daylighting controls. Energy Build.
**2001**, 33, 793–803. [Google Scholar] [CrossRef] - Onaygıl, S.; Güler, Ö. Determination of the energy saving by daylight responsive lighting control systems with an example from Istanbul. Build. Environ.
**2003**, 38, 973–977. [Google Scholar] [CrossRef] - Krarti, M.; Erickson, P.M.; Hillman, T.C. A simplified method to estimate energy savings of artificial lighting use from daylighting. Build. Environ.
**2005**, 40, 747–754. [Google Scholar] [CrossRef] - Ihm, P.; Nemri, A.; Krarti, M. Estimation of lighting energy savings from daylighting. Build. Environ.
**2009**, 44, 509–514. [Google Scholar] [CrossRef] - Li, D.H.W.; Tsang, E.K.W. An analysis of measured and simulated daylight illuminance and lighting savings in a daylit corridor. Build. Environ.
**2005**, 40, 973–982. [Google Scholar] [CrossRef] - Tregenza, P.R.; Waters, I.M. Daylight coefficients. Light. Res. Technol.
**1983**, 15, 65–71. [Google Scholar] [CrossRef] - Tregenza, P.R. The daylight factor and actual illuminance ratios. Light. Res. Technol.
**1980**, 12, 64–68. [Google Scholar] [CrossRef] - Li, D.; Lau, C.; Lam, J. Predicting daylight illuminance by computer simulation techniques. Light. Res. Technol.
**2004**, 36, 113–129. [Google Scholar] [CrossRef] [Green Version] - Bellia, L.; Cesarano, A.; Minichiello, F.; Sibilio, S. De-Light: A software tool for the evaluation of direct daylighting illuminances both indoors and outdoors—comparison with Superlite 2.0 and Lumen Micro 7.1. Build. Environ.
**2000**, 35, 281–295. [Google Scholar] [CrossRef] - Reinhart, C.F.; Herkel, S. The simulation of annual daylight illuminance distributions–A state-of-the-art comparison of six RADIANCE-based methods. Energy Build.
**2000**, 32, 167–187. [Google Scholar] [CrossRef] - Mardaljevic, J. Beyond Daylight Factors: An example study using daylight coefficients. In Proceedings of the CIBSE National Lighting Conference, York, UK, 9 July 2000; pp. 177–186. [Google Scholar]
- Krüger, E.L.; Fonseca, S.D. Evaluating daylighting potential and energy efficiency in a classroom building. J. Renew. Sustain. Energy
**2011**, 3. [Google Scholar] [CrossRef] - Bunjongjit, S.; Ananwattanaporn, S.; Ngaopitakkul, A.; Jettanasen, C.; Patcharoen, T. Design and application of daylight-based lighting controller on LED luminaire. Appl. Sci.
**2020**, 10. [Google Scholar] [CrossRef] - Hajjaj, M.; Miki, M.; Shimohara, K. The effect of utilizing distributed intelligent lighting system for energy consumption in the office. Appl. Sci.
**2020**, 10, 2004. [Google Scholar] [CrossRef] [Green Version] - Xiong, J.; Tzempelikos, A.; Bilionis, I.; Karava, P. A personalized daylighting control approach to dynamically optimize visual satisfaction and lighting energy use. Energy Build.
**2019**, 193. [Google Scholar] [CrossRef] - Bellia, L.; Fragliasso, F. Automated daylight-linked control systems performance with illuminance sensors for side-lit offices in the Mediterranean area. Autom. Constr.
**2019**, 100. [Google Scholar] [CrossRef] - Li DH, W.; Li, S.; Chen, W. Estimating the switching frequency and energy saving for daylight-linked lighting on-off controls. Energy Procedia
**2019**, 158. [Google Scholar] [CrossRef] - Ul Haq, M.A.; Hassan, M.Y.; Abdullah, H.; Rahman, H.A.; Abdullah, M.P.; Hussin, F. A method for evaluating energy saving potential in lighting from daylight utilization. In Proceedings of the 2014 IEEE International Power and Energy Conference (PECon), Kuching, Malasia, 1–3 December 2014. [Google Scholar]
- Shikder, S.H.; Price, A.; Mourshed, M. Evaluation of four artificial lighting simulation tools with virtual building reference. In Proceedings of the European Simulation and Modelling Conference (ESM 2009), Leicester, UK, 26–28 October 2009; EUROSIS-ETI: Ostend, Belgium, 2009; pp. 430–437. [Google Scholar]
- Ali, N.A.M.; Fadzil, S.F.S.; Mallya, B.L. Improved illumination levels and energy savings by uplamping technology for office buildings. In Proceedings of the 2009 International Association of Computer Science and Information Technology—Spring Conference, Singapore, 17–20 April 2009; pp. 598–603. [Google Scholar] [CrossRef]
- Parise, G.; Martirano, L. Daylight impact on energy performance of internal lighting. In Proceedings of the 2011 IEEE Industry Applications Society Annual Meeting (IAS), Orlando, FL, USA, 9–13 October 2011. [Google Scholar] [CrossRef]
- Ryckaert, W.R.; Lootens, C.; Geldof, J.; Hanselaer, P. Criteria for energy efficient lighting in buildings. Energy Build.
**2010**, 42, 341–347. [Google Scholar] [CrossRef]

**Figure 2.**CAD view and 3D render of test case simulation [30].

Calculated Parameter | Result |
---|---|

E_{I} | 843.36 kWh |

E_{G} | 701.69 kWh |

E_{DT} | 25.85 kWh |

E_{DS} | 88.73 kWh |

E_{D} | 114.58 kWh |

Energy Saving Potential From Daylight Utilization, S | 83.67% |

Calculated Parameter | Result |
---|---|

E_{I} | 534.63 kWh |

E_{G} | 320.97 kWh |

E_{DT} | 56.93 kWh |

E_{DS} | 28.28 kWh |

E_{D} | 85.21 kWh |

Energy Saving Potential From Daylight Utilization, S | 73.45% |

Parameter | Value |
---|---|

Total floor area of the building, A_{f} | 15.95 m^{2} |

Perimeter floor area, A_{p} | 15.95 m^{2} |

Perimeter to total floor ratio, A_{p}/A_{f} | 1 |

Visible transmittance of the window glazing, ${\tau}_{w}$ | 0.72 |

Total window glazing area, A_{w} | 2.32 m^{2} |

Daylight aperture, ${\tau}_{w}\frac{{A}_{w}}{{A}_{p}}$ | 0.105 |

Coefficient a | 72.86 |

Coefficient b | 19.36 |

Percent annual energy savings, f_{d} | 63 |

Calculation | Benchmark Energy Consumption (kWh) | Energy Consumption After Daylight Dimming (kWh) | Energy Saving (%) |
---|---|---|---|

Without considering general dimming, task/surrounding areas, and daylight ranges | 481.92 | 152.79 | 68.30 |

Considering all parameters of proposed method | 320.97 | 85.21 | 73.45 |

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## Share and Cite

**MDPI and ACS Style**

Haq, M.A.u.; Islam, A.; Shihavuddin, A.; Maruf, M.H.; Al Mansur, A.; Hassan, M.Y.
Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation. *Symmetry* **2020**, *12*, 1313.
https://doi.org/10.3390/sym12081313

**AMA Style**

Haq MAu, Islam A, Shihavuddin A, Maruf MH, Al Mansur A, Hassan MY.
Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation. *Symmetry*. 2020; 12(8):1313.
https://doi.org/10.3390/sym12081313

**Chicago/Turabian Style**

Haq, Mohammad Asif ul, Aminul Islam, ASM Shihavuddin, Md Hasan Maruf, Ahmed Al Mansur, and Mohammad Yusri Hassan.
2020. "Enhanced Energy Savings in Indoor Environments with Effective Daylight Utilization and Area Segregation" *Symmetry* 12, no. 8: 1313.
https://doi.org/10.3390/sym12081313