Saving energy using the sun as a lighting source PATRICIA ROMEIRO DA SILVA JOTA, MIRNA SUELY DOS SANTOS BRACARENSE Departamento de Pesquisa e Pós-graduação Centro Federal de Educação Tecnológica de Minas Gerais CEFET-MG Av. Amazonas 7675, 050-000 Belo Horizonte, Minas Gerais, Brazil Abstract: - In north-west of Europe and many other parts of the world people cannot rely on the direct light of the sun as their basic iluminant, because they only see the sun for about a third of the working hours. In Brazil and tropical areas around the world, we can see the sun almost ten to twelve hours per day. Because of that, we can take an advantage of the sunlight and save energy in lighting. To do that, we have to know how the architecture design contribute to the daylighting inside buildings. This paper study a case of school room architecture to know how the supplementary lighting can be reduced during the day. An statistical method has been used to analyse the data collected in a room scale model. Key-Words: - daylighting; solar power; save energy; Statistical analysis; Lighting; Scale model; Introduction Saving energy is a necessity of our society. The contribution of artificial lighting in the energy use in commercial buildings is 6% and residential buildings is %, as related by the Brazilian government. A good architecture design can reduce the necessity of supplementary lighting in most of the buildings parts during the day. But the supplementary light design made by the electrical engineer normally do not have in account the contribution of the architecture design. The engineer do not consider the existence of the window in that room. Because of that, the light level inside buildings is higher than the standard, principally near the windows. Most of the literature in this area coming from Europe, where the sky and climate is different from ours in tropics area. To use the sun as a source of light we have to take care because the thermal radiation. If the solar radiation is not used in a good way, the saving energy in a lighting can not compensate the supplementary energy that will be necessary in air conditioning. A good supplementary lighting scheme must be integrated with the daylighting in such a way that the dominant character of the daylighting is not lost. This is in contrast to the American system, in which the main source of light is manifestly the artificial lighting, the windows affording nothing more than a view outside []. Experimental studies have been made to determine the levels of supplementary lighting that are necessary for a good integration of daylight and artificial light. High levels of illumination shown to be necessary for efficient performance at work and cannot always be provided by natural light without introducing discomforts from excessive sky glare []. The study and measurement of daylight has both quantitative and qualitative aspects. We focus in this experiment the quantitative aspect of the problem. The quantity of daylight in the interior (Ei) of buildings is defined primarily in terms of the ratio of this quantity to the amount of daylight available from the unobstructed sky out of doors (Eo) expressed by the daylight factor (DF= Ei/Eo x 00%) []. To use the daylighting, we have to know how it is distributed inside buildings depending on the architecture design. To do that, we take the standard to design the schools in our State. The standard says that the windows size has to be /6 of the room area if there is no overhang and /5 otherwise. We have made some evaluations of the daylight factor as a response of different combinations of three factors such as window area, window location on the wall and the overhang. These evaluations have been done by a statistical method multi-level factorial design in a scale model simulating a room []. Experiment Description There are many factors related to daylight levels inside buildings. We choose three factors to study in a scale model under natural sky conditions [,5].
The model has been done in a scale one twentieth simulating a square room 7x7 meter by.8 height ceiling with removable walls with a window and a removable overhang, that can be seen in figure and. Each experiment has been composed of eight tests, each one with all combination of the three factors. The scale model has removable walls with different combinations and a removable overhang, as shown in figure. Fig. : the scale model with overhang. Despite the disadvantages of making daylight measurements with a natural sky, the results will be more close to the reality. Sky conditions changed quickly, and the level of light may alter during the brief period between the readings. Because of that, the measurement of daylight requires the simultaneous or near simultaneous measurements of the exterior and interior illumination []. In the experiment we have used two luximeters, model ICEL LD-500 in the tests, as shown in figure. For more accuracy we have calibrated them before the measurements. Fig. : Scale model with removable walls. Fig. : Scale model and the luximeters. The collected data of each experiment has been made systematically in the afternoon by two persons. They are subject to experimental errors so we have made three days experimentation and the data has been analyzed carefully. The tests have been done in a random order and put in order just for statistical analyses[]. The sky conditions were partly clouded in the days of the experiments, typical of summer season. Fig. : The room and the grid. The interior illumination readings have been done at the working plane 0.85 m high. The room is divided out into a grid of modular squares, creating sixteen points for the readings in four rows normal to the window, as shown in figure. The window s wall has been set toward south at CEFET-MG campus. The geography coordinates found by GPS x L model Garmin are latitude 9º56`8 south and longitude º59`59.6 west. Statistical Experimental Design Statistical experimental design should be efficient and cost less money. Our goal in this experiment is identify how the factors interact in daylight levels inside buildings using a statistical method Multi- Level Factorial Design. There are three factors that we analyse in this investigation and each one has two levels, it is called - level factorial design [].
. The Factors Levels In this statistical analysis, each factor will change between two values, and all combinations of these values will be analysed. Table presents the values of the three factors, and Table shows all the analysed combinations. Table : The factors ( cm ) and their levels. Factor Low level ( - ) High level ( + ) (A) Window area* 87 980 (B) Overhang** 0 00 (C) Window location** 5 6.7 (Lintel height ) *cm **cm Table : Shows all the combination of the factors levels Order tc A B C () 87 0 5 a 980 0 5 b 87 00 5 ab 980 00 5 5 c 87 0 6.7 6 ac 980 0 6.7 7 bc 87 00 6.7 8 abc 980 00 6.7 The observations are not analysed separately because the experiment provide mathematically independent or orthogonal assessments of the effects of each factors under study. The number of observations (tc) is determined by taking the number of levels () to the power of the number of factors (K). The experiment has 8 observations (8 tests in each experiment), or in statistical terms, there would be 8 treatments combinations (tc), as shown in table. The experiment has been run in three days and the response is the average of them, expressed by the quantitative parameter that describes daylighting in a building that is the daylight factor (DF). Yates order is a convention of alternating -`s and +`s produces an order in the experimental design and can be seen in the table. The signal + is the high level of the factor and the is the low level of the factor. For each one of this combination, the DF total is calculated. The DF total is the average value of the DF in each of the 6 points inside the room for all the three days measurements. Table shows one measurement of the factor A, B and C in high level on the third day. Table : The factors in Yates order, the response of the experiment is the daylight factor (DF total ). Single Interaction effects effects Order tc A B C AB AC BC ABC DF total - - - + + + -.9 a + - - - - + +.9 b - + - - + - +. ab + + - + - - -. 5 c - - + + - - +.6 6 ac + - + - + - -.7 7 bc - + + - - + -. 8 abc + + + + + + +.7 Table : The measurements of one test of the experiment; Ei is the illumination indoors and Eo is the illumination outdoors. Factor A 980 (+) Test abc Factor B 00 (+) Day 0-march 0 Factor C 6.7 (+) Time 5: to5:6 Point Ei (lux) Eo (lux) DF 60 700. 57 500.6 0 500 0.9 67 600 0.8 5 0 5000.0 6 68 00.8 7 7 500. 8 78 00 0.8 9 0 000. 0 67 900.9 75 800. 8 700 0.9 80 500. 577 00.8 5 8 00. 6 6 00 0.8 Total 08 5500 Average 655.5 7.5.9 The value.9 in the end of table is the average value of the DF in that test. Each test is repeated times in different days. The Df total is the average of the DF, DF and DF for each test tc. Results
Plotting the DF values of the table we can obtain the figure 5. The distributing of the daylight factor DF is not constant across the room. The daylight factor near the window is much higher than the remotes points. Figure 6 presents the same points without overhang. It can been seen, comparing figure 5 and 6, that the presence of overhang decreases the DF near the window. The asymmetry in the graphics may be due to outside obstructions, such trees, sufficient to cause it, even if the room is symmetrical []. Table 5: Shows the DF for each combination of each day and the DF total. Order tc A B C DF DF DF DF total () 87 0 5.9.6..9 a 980 0 5.0..5.9 b 87 00 5..0.5. ab 980 00 5.... 5 c 87 0 6.7.8.6..6 6 ac 980 0 6.7.0.8..7 7 bc 87 00 6.7...8. 8 abc 980 00 6.7.5.6.9.7.5.5 DF.5.5 0.5.5.5.5.5 5 5.5 6 window distance (m) Fig. 5 Factors A, B and C in high level (order 8 abc table 5) DF 0 9 8 7 6 5.5.5.5.5 5 5.5 6 window distance (m) Fig.6 Factor A and C in high level and B in low level (order 6 ac table 5) The overhang reduces the variation between the point.5m distant from the window (,5,9, in figure ) to the point 5.6m distant from the window (, 8, and 6 in figure ) from 9.5% to.5%, as shown in figures 5 and 6. The average differences for the three single factors by summing the responses at low levels (- `s) and high levels (+`s) give us the simple effect, table. These results are free of interactions effects because the orthogonal design. Table : Differences between responses averages. Factor Difference Factor A-window -0. area Factor B-overhang -. Factor C-lintel +0. The results of table means that: Factor A: Growing factor A between the two values the value of DF will reduce. This result is not considered, because the value of the window size is varies between to 50% of the wall. Factor B: the existence of overhang the lower the DF inside buildings. The overhang reduce the light entrance near the window, reducing the glare too. Factor C: The high level of the lintel give more light inside building. This result is expected as the window open near the working surface (the sill is almost the same height of the working plane []) give more efficiency of the opening. The biggest effect is caused by factor B in the low level, the effect of an obstruction - Overhang outside the window is to reduce the penetration of light []. The results of the measurements under this methodology shows that the biggest simple effect is caused by factor B (overhang) in the low level (-). The tests with no overhang had bigger response (DF) than the others, its an expect result. The State standard demands for a class room that: the combination of the size of the window has to be: window high level and an overhang in high level too. Figures 7 and 8 shows that the best combination will be obtained without overhang. But the existence of overhang reduce the glare effect. In this case the best result is the bigger window with the overhang as the standard demand. There is not interaction effects between factor B (overhang) and the factor C ( lintel), no matter their levels, the effect caused by the factor C (- and +) is the same for factor B (- and +).
DF - %,5,5,5 0,5 0 low(-) Overhang high(+) A+ A- The lintel became interesting when it forces that the window s sill becomes more close to the working surface. The size of the window does not give good results, probably because the values used is in the range of % to 50% of the wall area. These values are taken according to the standard of our State. New measurements will be made. Fig. 7 Interaction between factors A and B DF - %,5,5,5 0,5 0 low(-) Window area - A high(+) Fig. 8 Interaction between factors A and B 5 Conclusions The sun is a very important source of energy The visible radiation spectrum, called light, is an important part of its electromagnetic radiation. We need the light inside buildings during the day and the night. During the day, we can take part of the natural light coming from the sun to reduce the supplementary lighting. Lighting is a great load of commercial and residential buildings. When we desire in save energy in buildings we have to reduce energy to illuminate these buildings. We can reduce the energy changing the illumination system like a lamp and the reactor and/or taking advantage of daylighting. To use the daylighting we have to know how the architecture design contribute for the light entrance inside building to design the supplementary lighting. B+ B- The experimental methodology used will be review in other range of the factor s level and better luximeters will be used for more accuracy of the readings. The method multi-level factorial design achieved the goal in the analyses of this experiment and brought out clearly the simple effects and the interaction effects of three factors in their two levels under study. References: []R. G. Hopkinson, Architectural Physics Lighting, Department of Scientific and Industrial Research Building Research Station London, (96), 60. []N. k. Bansal, G. Hauser, G. Minke, Passive Handbook of Building Passive Building Design, Elsevier Science B. V. Amsterdam, London, N. Y.,Tokio, (99). []T. B. Barker, Quality for Experimental Design,Second Edition, revised and Expanded Marcel Deckker, Inc. N. Y.,Basel, Hong Kong. (99), 7. []U. Del Carlo, Iluminação Natural Estudo através de Modelos, UNICAMP Faculdade de Engenharia de Limeira, Seção Gráfica do IPT. São Paulo, (97), 78. [5]M. A. Magalhães, Medidas de luz natural através de aberturas laterais Variações decorrentes do uso de vidro, Anais do III Encontro Nacional I Encontro Latino- Americano - Conforto do Ambiente Construído, Depto. De Tecnologia da Construção, FAU UFRJ ( 995). This paper study three factors that change the daylighting factor. They are: window area, overhang and lintel. It has been showed that for the range of the choose values, the overhang is the more important factor. The overhang decreases the daylighting factor but the illumination inside building became less variable when we cross the room going to remote point of window. This is a good character because we have less glare.