One type of switchable mirrors as they are researched at the Fraunhofer ISE consist of a layer of a Mg and Ni mixture5, where both elements are evaporated or sputtered at the same time. A second layer of Palladium (Pl) is needed as a catalyst for the hydrogen — activated switching process. This multiple layer is obviously much more complex than a single layer. Therefore, it has to be proved that it is also possible to attach a switchable mirror face selectively. Already showed above in figure 7 and figure 8, is a SEM image of an applied switchable mirror coating. The edges of the coating are sharp and the geometry is as expected, but in this way it is not possible to distinguish whether the structure of the layer itself is suitable for optical switching. In Table 1, the results of some measurements of the hemispherical transmission of the structure shown in figure 7 for several incidence angles in both states of the switchable mirror are presented. The effect of switching from the reflecting to the clear state reaches a maximum for high incidence angles, while for small angles the effect is small. This is the result one would expect when using this arrangement. Unfortunately, on high incident angles the measurement error was increasing due to the small available sample size and the available measurement setup itself. Therefore, this measurements can only give a qualitative idea of the possible results, but they are still suitable to demonstrate the feasibility of the concept. As mentioned above, the use of switchable mirrors need a new structure. The optical properties of the switchable mirrors, e. g. the minimisation of the absorptance in its clear state, are still subject for further research, and they are changing for different samples. So we had to work with varying parameters for the simulation of the coating. Figure 11 shows a first concept of a controllable light shading structure using switchable mirrors. The parabolic design was chosen because this should be easy to realise on a large scale with the existing technology of interference lithography. The coating is attached to the area marked with bold lines. The function of the structure is shown schematically. Light of low incident angles will pass through the structure in both states of the coating. For large incident angles in the reflective-state the light will be reflected, while for the transparent state most light will pass through. Therefore one can

control the intensity of the direct sun, with this system while diffuse light will still be transmitted. Figure 12 shows the result of a raytracing simulation of this design. The calculated hemispherical transmission as a function of the incidence angle is plotted. The solid line represents the structure with the coating in its mirror-state. For this first analysis, a constant reflectance of 0.9 and an absorptance of 0.1 has been assumed. Further work will include the exact optical properties, but these values proved to be a good estimation. By changing the structure parameters like the aspect ratio as well as the ratio of the coated area to the non-coated area, the angle of incidence, where the transmittance reaches its minimum can be adjusted. The dotted lines are the upper and lower limits for the transparent state, depending on the coating parameters that are to be expected. The upper line represents the transmission of the non-coated structure, i. e. zero absorptance of the mirror in the clear state, whereas the lower line was calculated with a coating of 50% transmittance in the clear state. It is estimated that a transmittance of more than 60% is reachable. The shown structure still has big potential for optimising e. g. to increase the transmission in the clear state. Not only the coating itself can reach a higher transmittance, but it should be also possible to increase the transmittance of the non-coated structure e. g. by changing the index of refraction and optimisation of the geometry. For this purpose detailed parameter studies will be carried out in future works. Beside the optimisation of the transmittance also several applications with different cut-off angles will be studied

The regional programme "ETP" (energy technology programme) supports R&D projects in the fields of energy efficiency and RES in Upper Austria. So far 79 R&D projects and 153 thesis papers have been supported, including several of the developing, testing & demonstration innovations in commercial buildings (especially regarding to "passive house buildings").

Additionally an R&D centre (ASiC — Austrian Solar Innovation Centre) was set up to support the local solar companies in their research activities and a solar R&D laboratory is under planning.

Innovative Financing Mechanisms

In order to support innovative financing mechanisms, such as third party financing (TPF), a regional TPF programme is managed by O. O. Energiesparverband. The successful programme has so far supported 45 municipalities with the implementation of energy efficiency projects. Throughout the whole process, the programme provides detailed information, advice and guidance to local authorities and companies interested in TPF. It supports the innovative financing scheme and can be used to finance the retrofitting of buildings, street lighting etc. within the municipalities.

The programme was extended to cover also company buildings, as well as investments in energy efficiency and in the construction or retrofitting of installations. It is expected that the new programme will give a strong boost to retrofitting large buildings and installations, and that it will trigger new (large) RES installations.

Quite attractive is also the financial support for renewable energy installations in companies, which covers up to 44 % of the investment costs for solar thermal installations and biomass.

The solar radiation entering the building consists of directly transmitted short wavelength radiation and heat flux from the absorbed radiation in the window. Together with the inter­nal gains, these solar gains may at some times reduce the heating demand to zero. In such periods, the gains lead to temperatures higher than the set temperature. This occurs mostly in summer, but also in shorter periods during winter time. Due to the higher indoor temperature, the transmission and ventilation losses are increased compared to a case without solar gains. This excess of losses represents the part of the gains, which is not utilized. With TRNSYS, the utilized part of solar gains can not be calculated directly. One possibility is to calculate the heating energy demand for two simulations, one with and one without solar gains. The difference in heating energy demand defines the utilized solar

gains. Note, that the proper time interval for such a study is not arbitrary. If a simulation is run without solar gains for the whole year, the transition period from summer to winter is not modelled correctly. In the summer, the building usually heats up several degrees over the set temperature. The corresponding stored heat can reduce the utilisation of solar gains in the transition period to winter. Without solar gains during summer, this effect is completely suppressed. On the other side, of course, the time interval for the simulation must be considerably longer than the time constant of the buildings, which could be up to several days. Therefore, the utilization of solar gains is calculated on a monthly basis. in this study, the year is divided into 12 months of equal length with 730 hours. This ap­proach requires two subsequent simulations for every analysed month. After simulating a period of several weeks to guarantee independence of initial conditions, the demand of heat energy H0(m) and solar gains S0(m) are calculated for month No. m. In a second simulation over the same period of time, and under exactly the same boundary conditions, the direct and diffuse solar radiation is reduced to a smaller value or zero on all outside window glass surfaces only for month No. m (at the end of the simulation period). The so­lar radiation on the opaque surfaces (including window frames) is not changed. This has been achieved by a simple modification of the subroutine "DWINDOW" within the TRNSYS building model "Type 56". The resulting demand of heat and the solar gains are H1(m) and Si(m), respectively. The utilization factor tj of solar gains through the transparent parts of the building is now given by the results of both simulations:

with m running over all months of the heating period (usually September to May). For a complete suppression of solar radiation with S1(m) = 0, the usable solar gains are given by Su(m) = tj(m)S0(m) = H1(m) — H0(m), which is the saving in heating demand provided by the solar radiation. For the results shown in the next section, S1(m) = 0 was used for all m.

Results

The utilisation factor p, calculated according Eq. 1, is shown in Fig. 3 for the two objects with the highest (object 1) and lowest (object 4) utilisation factor of the four analysed ob­jects. The two plots show results for weather data representing a cold and warm European region, with all other parameters kept constant. Whereas the maximum of the utilization factor within 0.9 < p < 1.0 for the core winter time is quite high for all buildings and both weather conditions, the utilization of solar gains varies significantly in autumn and spring. In these periods, the total gains (internal and solar) can balance the losses (transmission and ventilation), so that the heating demand is zero. This is especially valid for the high performance buildings (objects 3 and 4) and/or in warm climate (Milan), and leads to small utilization factors p or even p = 0.

To analyse the major influences on the utilization factor, variations of the construction type of the walls, of window size and distribution and of total heat loss have been studied. The results are presented in form of the total and utilized solar gains in the heating period, i. e. in September to May. The integration of these monthly simulation results over the heating period in Trier is shown in Fig. 4 (left side). The ratio of utilized solar gains to total solar gains is given in the figure as a percentage. The left graph shows the solar gains for the buildings in their original construction. The right graph shows the solar gains for the same buildings, but with a modified construction type of the outer opaque envelope. The origi­nally massive buildings were changed to a light construction and vice versa. All values given in Table 2 are hereby not changed, for example the sizes and U-values of walls and windows remain constant. Only the type of constructions for walls, roof and ground floor (see Table 1) were interchanged between objects 1 and 2, and between objects 3 and 4. A comparison of the left and right graph in Fig. 4 shows, that the utilized solar gains do not depend strongly on the type of construction. The differences in utilized solar gains be­tween the massive and the light construction type of otherwise the same building is less than 10% for all four objects and for weather data from Trier (as shown in Fig. 4), Milan and Stockholm. In general, buildings with massive construction have slightly higher utiliza­tion factor than those with light construction. The putative exemption from this rule for ob­ject 3 (see Fig. 4) is due to the shading strategy against overheating (above 24 °C). With-

Fig. 4: Total and usable solar gains in the period September to May. The percentage in the columns is the fraction of usable solar gains during this period. The left graph shows the solar gains for the 4 objects in their original construction. The right graph shows results for modified simulation models, where the type of wall construction has been changed from massive to light and from light to massive, respectively. Thereby, the U-values for the building envelopes were not modified.

out active shading, the utilisation factor for the massive version is p = 55%, somewhat higher than for the light version, which in this case is only p = 53%.

Regardless of construction type, the houses with the lowest heating demand (objects 3 and 4) take advantage of significantly lower utilised solar gains than the "standard" low — energy buildings (objects 1 and 2). Note, that also the amounts of not-utilized solar gains are quite different for the buildings. The amount of such not-utilized solar gains gives an indication of possible overheating problems in the building. For example, object 1 requires roughly 5 times more heating than object 4, but object 4 has even more total solar gains than object 1. This results in a very low utilisation factor for object 4 and at the same time a much more significant potential overheating problem in summer. The simulation presented here, without ambitious shading and cooling, reveals such overheating problems. Only additional ventilation of 1 ach/h and shading of 50% is applied, if the temperature exceeds 24 °C and lasts until the temperature falls below 22 °C. A user (or an advanced sophisti­cated system) might be able to perform much better cooling strategies (e. g. night cooling

Hours Hours

Fig. 5: Number of hours with mean indoor air temperature above certain limits, for ob­ject 1 (left) and object 4 (right). The mean indoor temperatures are averages weighted by the volumes of the living spaces inside the buildings.

and cooling in anticipation of hot days), however this is not always possible. In figure 5, the number of hours during one complete year with mean indoor temperature within certain temperature bands are presented for the objects 1 and 4. The object 4 exhibits signifi­cantly more overheating hours between 22 °C and 24 °C than object 1, even if its type of construction is changed from lightweight to massive.

Besides from the building mass, the major constructional differences between the 4 ob­jects are total heat loss and window distribution. Whereas objects 2 and 4 are predomi­nantly oriented towards south, the windows of the objects 1 and 3 are distributed equally to all directions. The influence of window size and distribution can be determined with varia­tions of the simulation model. Exemplary results are presented in Table 5 for variations of object 3, which has originally the lowest amount of utilized solar gains compared with the other objects. In variation 1, the windows are more concentrated to the south. Variation 2 includes windows whose size is increased up to a still reasonable maximum. In variation 3, the window area is reduced to the smallest size, which is required according to the legal regulations in Germany. The results show, that the utilized solar gains for this building could be increased by about 15% (variation 2). However, due to the losses through the larger window area, the heating demand for this variation is higher than in the original case. The distribution of windows towards south (variation 1) leads to a slightly lower heat­ing demand compared to the original construction, but this may entail drawbacks for the outside view and lighting in some zones of the building.

To emphasize the relationship between the total heat loss of the building and its utilisation of solar gains, variations of object 1 with different heat loss were simulated. The total heat loss is influenced by the thickness of the insulation layer and by the efficiency of the venti­lation system to recover heat. Variations of these parameters lead to a yearly heating de­mand for object 1 between 124 kWh/m2 to 18 kWh/m2 for the period September to May and for the weather of Trier. This band of results for the heating demand is represented by 7 individual simulations, and the corresponding solar gains are shown in Fig. 6. The total solar gain is, of course, equal for these simulations, because the windows and the bound­ary conditions are not changed. However, the utilized solar gains decrease for decreasing heat loss, or heating demand, respectively. An additional simulation was performed for a case with heating demand as low as 9 kWh/mPa. For this case, high performance windows had to be used. These windows exhibit a lower g-value, which leads to lower total solar gains. Fig. 6 shows clearly, that the utilised solar gains depend strongly on the heating demand. Whereas the building with poor energy performance has used solar gains of

20.0 kWh/m2 this value drops for the high performance case down to 7.5 kWh/m2. The reason for this is the reduced length of the heating period for high performance buildings. In such buildings, the solar gains in the transition period between winter and summer are not utilised for heating, because the heating demand tends to zero.

25

<4

;§ 20

JZ

§

15

V)

c

’ro

10

s—

03

0

Fig. 6: Solar gains for variations of the insulation level of object 1. For each variation, the heating energy demand is given. For the case with heating demand of 9 kWh/(m2 a), high performance glazing (U = 0.7 W/m2K, g = 0.54) have been used. The lower g-value leads to reduced total solar gains compared to the other 7 considered cases (U = 1.4 W/m2K, g = 0.62). The simulations are performed with weather data for Trier.

For passive houses, the overall variation of the utilized solar gains is rather small. In Table 6, the heating demand and the utilised solar gains of some analysed variations of the four objects are shown. These variations represent passive houses, with a heating demand of roughly 15 kWh/(m2a) for German weather conditions. The values for the utilised solar gains Su shown in Table 6 can be summarised as Su = (10 ± 2) kWh/(m2 a). This range is valid for passive houses with a reasonable window fraction of about 20%. For buildings with extremely small windows or a window distribution oriented towards north, the total and usable solar gains could, of course, be smaller (e. g. variation 3 in Table 5). On the other side, in very cold climates, the utilized solar gains are larger, because of the extended heating period. In the climate of Stockholm, the utilised solar gains (and the heating de­mand) are up to 50% larger than for the weather of Trier. However, the dependence on construction type and window distribution is equally small for all considered climates.

Conclusions

The analysed buildings with a heating demand of about 15 kWh/(m2 a) for standard Ger­man weather conditions ("passive houses") in un-shaded locations exhibit utilized solar gains of Su = (10 ± 2) kWh/(m2 a) in this climate. These solar gains do not depend strongly on type of construction (heavy or light) or windows, as long as the windows are reasonably in size and orientation. However, the overheating hours can increase with the window size and also depend on window orientation, especially for light-weight constructions.

Particularly for passive houses, the glazed area is extremely expensive. In conclusion, the results indicate, that for such buildings the window area towards south should not be maxi­mised. Windows can be distributed over all directions and should be limited in size to provide appropriate day lighting, outside view, summer comfort and to provoke lowest costs.

Acknowledgements

The authors thank the Ministry for Science and Research of North-Rhine Westphalia (NRW), Germany, for funding this study within the project of the AG Solar NRW "Bewer — tung der Energieeffizienz verschiedener MaRnahmen fur Gebaude mit sehr geringem En- ergiebedarf" under No. 262 104 99.

References

Gieseler, U. D.J., Heidt, F. D. and Bier, W., 2003: Combined thermal measurement and simulation for the detailed analysis of four occupied low-energy buildings, Proceedings of the 8th Intern. IBPSA Conf., Building Simulation, Eindhoven (2003), vol. 1, pp. 391-398.

Klein, S. A., Duffie, J. A. and Beckman, W. A., 1976: TRNSYS — A Transient Simulation Pro­gram. ASHRAE Trans 82, p. 623, Version 14.2 (1998), http://sel. me. wisc. edu/trnsys/.

Meteotest, 2000: METEONORM, Edition 2000, Global Meteorological Database for Solar Energy and Applied Meteorology, Version 4.0, Bern, http://www. meteotest. ch.

B. Porcar, M. J. Jimenez, M. R. Heras

Bioclimatic Architecture Research Program, Department of Renewable Energies, CIEMAT, Madrid, E-28040, Spain; Tel: +34 91 3466344, e-mail: beatriz. porcar@ciemat. es.

An energy efficient monozone building has been constructed in South Spain. The aims of this project are to assess the energy behaviour of the building, to evaluate the performance of the techniques implemented and to propose further improvements to reduce conventional energy needs providing a comfortable space. This paper presents a preliminary analysis of the building thermal performance by means of experimental measurements and simulation. The building has been monitored during 25 days of Spring 2003. The experimental device, the obtained measurements and their analysis are presented. The system has been modeled by means of a transient simulation program using the recorded weather data. Model predictions have been compared with the measured data. Then the simulation model has been used to estimate the performance of the real building compared to a reference building closer to the regional construction practice. The theoretical results presented focus on the indoor air temperature during the monitored period.

These preliminary results will support further experimental and theoretical studies on the system thermal performance.

Introduction

Energy consumption in buildings has been increasing during the last decades in Spain. This is an issue of concern as buildings consume as much as 31% of the total energy consumption in this country. Therefore there is a general consciousness to enhance buildings energy efficiency. This has been supported by many studies which report the performance of different passive and active techniques to reduce conventional energy requirements providing a comfortable living space in different climates.

This work studies a building that was recently constructed in an sub arid Mediterranean region in Almeria, South Spain. Several solar passive and active techniques have been implemented for indoor conditioning in both cold and hot seasons. The used techniques are of special interest as they are easy to implement regarding common regional material and construction techniques.

Indoor and outdoor variables have been recorded during 25 days of Spring 2003. Theoretical studies on the thermal behavior of the building were carried out by using the transient simulation code TRNSYS and the measured whether data. The model results have been compared to the experimental data by means of residual analysis techniques. Then the model has been used to compare the thermal behavior of the real building with that of a reference building, under identical operational and environmental conditions. The reference building is identical to the real building except for several solar passive features.

In this paper, first the building is described. Then monitoring design matters are presented as well as spectral analysis of recorded data. Afterward adopted modeling hypothesis are presented and the performed model results are compared to the experimental data. Comparisons between the theoretical results on the thermal behaviour of the reference and the real building are presented next. To finish with the conclusions to the study.

In a previous work (Cucumo M. et al., 2001), the authors applied the first method of Perez to calculate the hourly incident solar radiation on the vertical south-, west-, north — and east-facing surfaces, obtaining mean deviations for all surfaces ranging from 0% to 6,5% and mean square deviations from 18% to 23%. The Perez method for the calculation of global solar radiation is similar to that for the calculation of global illuminance, the structure of the equation used being similar to that of eq. 1.

In this paper the authors attempt to modify the first Perez model to obtain better predictions of illuminance on vertical surfaces. The subject of a future paper will be the analysis and attempted improvement of the second Perez model.

The high mean deviations and mean square deviations for west, north and east-facing surfaces could be justified by the fact that, for calculation of illuminance on vertical surfaces, as many as 5 correlations are used: the Erbs resolution correlation, the correlation of the effective illuminance of direct radiation, the correlation of the effective illuminance of diffuse radiation and the two correlations linking parameters F1 and F2 to the independent variables of the Perez model; whereas only 3 correlations are used for the calculation of global radiation.

Initially an attempt was made to find new correlations for the parameters F1 and F2, still following the Perez methodology, in such a way as to minimise the deviations between the calculated and experimental values. The results of these calculations are shown in table 3:

Table 3 compared with table 1, indicates an improvement of predictions on all the surfaces. The deviations are however still too great.

A closer analysis of calculated and experimental values revealed that the percentage errors are more contained during the hours when the surface is exposed to the sun, that is when direct light falls on it, whereas they are greater when the surface is only lit by diffuse light. This is clear in the graphs of Fig. 1, in which the calculated and experimental illuminance trend values for the four vertical surfaces during one day are shown.

North Wall

Fig. 1 — Experimental and calculated hourly illuminance E for the four vertical surfaces on 30 June 2001.

The same observation can be deduced, indirectly, from table 1, observing that the errors relative to the south-facing surface, which is lit by the sun for the most hours, are lower compared to those of the other surfaces.

To point out this characteristic of the Perez model more quantitatively, the error calculations were repeated, separating the hours in which the surfaces are lit by the sun (Rb>0) from the hours in which the surfaces are not lit by the sun (Rb<0). The results of the calculation are shown in tables 4 and 5.

Given the lack of ability of the first Perez method, both in the original and in the modified version with the refit of parameters F1 and F2, to predict well the experimental data of Arcavacata, the authors have developed the following simplified calculation method: the diffuse illuminance from the horizon is neglected, since its weight is always negligible, and, the following equation for the calculation of illuminance on a surface orientated in any direction:

E = Eb0Rb + Ed0(1 — F1) f+ E^FR + (Eb0 + Ed0)pf4)

Parameter Fi, which takes circumsolar radiation into account, was obtained, retaining it to be dependent on the same independent variables used in the Perez model (sky clearness index є, Д sky illuminance, zenith angle z), using the hourly experimental illuminance data of the single south-facing surface, during the hours in which that surface is lit by direct light (Rb>0). In fact, the south-facing surface is almost always lit by direct light, at the latitude of Arcavacata.

For the hours when the surfaces are not lit by the sun (Rb<0), their illuminance is calculated with the relation:

The parameter F1′ was obtained, as a function of the variables used in the Perez model, considering the hourly experimental illuminance of all the vertical surfaces. The quantity (1-F1) is the diffuse illuminance reduction factor on the horizontal surface with the aim of evaluating the diffuse light striking the inclined surface in the absence of direct light. This reduction is due to the lower value of the mean sky luminance affecting the non-south­facing walls.

The coefficients f11, f12, f13, f’11, f’12 and f’13, on which the parameters F1 and F1 depend, were obtained with the squared minima method and are shown in the appendix.

Table 6 shows the mean deviations and the correlations of variations between the experimental and calculated data using this latter method.

An examination of table 6 indicates that the deviations are notably improved compared to the values obtained using the first Perez method, see table 1. The mean deviations are contained between -2,4% and -11,7%, the correlations of variations between 20% and 33%.

The illuminance predictions could be further improved by obtaining the fit of parameter F{ for each vertical surface; that is in agreement with the fact that each surface is exposed to a portion of the sky having its own mean luminance.

The authors propose to continue this work examining the incidence on the deviations of the use of the Erbs resolution correlation (using the experimental values of direct and diffuse radiation resolution is avoided), experimentally testing, for the Arcavacata area, the effective illuminance correlations proposed by Perez for calculating direct and diffuse illuminance, and in the future also testing the sky illuminance correlation proposed by Perez for the use of the second model.

3. CONCLUSIONS

Some correlations and calculation methods of natural incident illuminance on variously orientated surfaces have been tested, using experimental hourly global illuminance data of a horizontal surface and four vertical surfaces facing south, west, north and east, recorded at Arcavacata di Rende for a period of 22 months. More than 23,000 data were considered overall.

Illuminance on the horizontal surface proved to be well-predicted by the correlation of effective illuminance proposed by Perez, whereas, for the variously orientated vertical surfaces, notable differences were observed between the values calculated using the Perez methods and the experimental data.

In particular the Perez method was analysed, based on the composition of the illuminance as the sum of the direct illuminance, diffuse circumsolar illuminance, diffuse isotropic illuminance, and diffuse illuminance from the horizon. This method appears to be inadequate for predicting the experimental data of Arcavacata.

The authors have proposed a simplified method, in which illuminance due to the illuminance from the horizon is eliminated and two correlations are used, the first to be used in those hours when the surfaces are lit by the sun and the second to be applied when those surfaces are lit only by diffuse light. This method, which will be further perfected, is able to reduce notably the deviations with respect to the original Perez method.

This argument is particularly complex and requires further examination and development.

APPENDIX Erbs Correlation

Erbs resolution Correlation (Erbs et al., 1982) of the global radiation on the horizontal plane Hh in the diffuse Dh and direct Bh components:

where k is the hourly clearness index, defined as the ratio of the hourly global energy Hh incident to the ground on the horizontal plane and hourly energy Hh, ex incident on the horizontal plane outside the atmosphere.

Perez Correlations

Illuminance on the horizontal plane

The effective illuminance of the global radiation on the horizontal plane is calculable with the equation:

— = a; + b;w + q cosz + djn Д G0

where w is the precipitation water content in the atmosphere; z is the zenith angle of the sun, Д sky illuminance; ai, b, c; and di are the coefficients (Perez et al., 1986) calculable as a function of the sky clearness index e.

Sky illuminance is defined in this way

Д = m-^ Iq

where m is the relative air mass, Ido diffuse radiation on the horizontal plane and Io normal extra-atmospheric radiation.

The clearness index e is defined in this way

I + bo

— sen^ + 5,535.1Q-6z3

e = !d0_____________________

1 + 5,535 ■ 10_6z3

where Ib0 is direct radiation on the horizontal plane, a is the solar height, the quantity Ib0/sena is direct normal radiation to the ground, and the zenith angle z is expressed in sexagesimal degrees.

Precipitation water w is calculable with the relation

w = e(0-07Td -0,075)

Where, Td is the dew temperature in °C, calculable with correlations in literature, as a function of the temperature and of the relative humidity of the outdoor air (ASHRAE HANDBOOK, 2001).

Illuminance on inclined surfaces

The effective illuminance of the diffuse radiation is calculable with the equation

= a; + b;w + q cosz + djn Д

‘dO

where Ed0 and I d0 are respectively the diffuse illuminance and the diffuse radiation on the horizontal plane; while the effective illuminance of the direct radiation can be calculated using the equation

Eb0 = a| + b|w + c|e(5,73z 5) + d|A

‘bO

the coefficients ai, Ь;, c; and di, different for the calculation of global, diffuse and direct illuminance, are a function of the sky clearness index e (Perez et al., 1986).

The instantaneous incident illuminance on an inclined surface however orientated can be calculated using the equation:

E = EboRb + Edo(1 — Fi) (+ e^F, і + E^senp + (Ebo + Edo) p (

where Rb is the inclination factor of the direct radiation, p is the inclination of the surface on the horizontal plane, p is the coefficient of reflection from the ground, F1 and F2 are coefficients respectively linked to circumsolar illuminance and to that of the horizon; a and b are quantities defined as:

a = max [o, cosi] b = max [cos 85°, cos z]

being the incidence angle of the solar rays on the inclined surface and z the zenith angle. The quantities F1 and F2 are calculated by means of the equations:

F2 = max o, ff2i + f22^ + f23z V!

2 [ і21 22 23 18o jj

being the illuminance coefficients fn, f12, f13, f21, f22, f23 obtainable from table A1 as a function of parameter e.

Table A2 — Illuminance coefficients for the calculation of coefficient F1 in eq. (4)

Christel Russ, Fraunhofer Institute for Solar Energy Systems, Freiburg, Germany Robert Hastings, Architektur, Energie & Umwelt GmbH, Wallisellen, Switzerland

Single-family and apartment housing with a very low energy demand are state of the art in Europe, especially in Germany, Switzerland and Austria. Such dwellings have a high construction quality and very efficient heat production and supply for space heating, domestic hot water. Well engineered ventilation assures exceptional comfort in the rooms. The planning and engineering to such standards requires must lead to an integrated building concept. Active and passive solar energy can then make a significant contribution to meet the small remaining energy demands. The IEA SHC1 Task 28 and ECBCS2 Annex 38 „Sustainable Solar Housing — Marketable housing for a better environment[27] uses the results from previous projects to collect the experiences of high efficient buildings in 19 countries. The goal is to provide a sound basis for planning buildings with very low energy demand, exceptional comfort level and marketable costs.

A building requires a large quantity of water for the purposes of drinking, cooking, washing and cleaning, flushing toilets, irrigating plants, etc. All of this water requires treatment and delivery, which consumes energy. The water that exits the building, as sewage must also be treated. At this project the idea was to reduce both input and output of resources. A reduction in use also produces a reduction in waste.

Reuse of water onsite: Gray water was recycled within the building to irrigate plants and flush toilets. Rainwater tank collection: the roof became a rainwater-collecting device, in combination with the rainwater collection tank. This water could also be used for irrigation and toilet flushing.

Bio composting toilets: was used to treat sewage on site eliminating the need for energy intensive local treatment.

Indigenous landscaping: vegetation was used being adapted to the local rainfall levels eliminating the need for additional watering.

Materials conservation

The production and consumption of building materials has diverse implications on the local and global environments. Extraction, processing, manufacturing and transporting building materials all cause ecological damage to some extent. There are input and output reduction methods for materials conservation. As with water, some of these methods overlap.

Use of materials that can be recycled and has low embodied energy: the project has search to use plantation timber for all floors, stairs and structural system. For traditional way of construction and availability, brick was used for walls. White tiles for some parts of the roof and recycled corrugated iron roof were used.

Non-toxic materials: as people spend more than three quarters of their lifetime indoors, non-toxic materials are vital to the health of the building’s occupants. Adhesives, which release volatile organic compounds into the air, were avoided.

1. Conclusions

The design strategies and methodology used for the BR ecoproject have been presented. The use of a mixed strategy (dual mode concept) has been introduced. An active approach for some periods along with extended passive operation can be used. A block of four main sustainable design strategies were set and analysed. The use of water and materials were treated on a sustainable basis. Low energy design features combined with the production of energy thorugh a PV grid connected system installed on top of the roof had demonstrated the important integration of energy efficiency and renewable energy features. Simulations were carried out to assess the feasibility of the design features proposed and optimize its performance according to the specific conditions presented. A development of this project is being undertaken, in which the intention is to test this methodology for other locations and compare the results, considering the dual mode concept and its feasibility and applications. A proposed set of locations is currently being analysed, as part of possible developmental areas for further research/implementation of projects.

2. References

[1] OEA. The world in 2020, www. iea. shc. org, 2001

[2] Tenorio, R. Pedrini, A. 2001. Guarajuba Ecohouse, Proceedings of ISES — International Solar Energy Society Conference, Adelaide — AUS, 2001

[3] Tenorio, R. Dual mode cooling house in the warm-humid tropics: PhD Thesis, University of Queensland, UQ — AUS, Department of Architecture, 2002.

[4] J. Kim, B. Rigdon, Principles of sustainable design, national Pollution prevention Center for Higher Education, USA, pp 9-15, 1998.

[5] www. labeee. ufsc. br

[в] R. De Dear, G. Brager, D. Cooper. Developing an adaptive model of thermal comfort and preference. Final Report. ASHRaE RP-884-1997

[7] D. S. Parker, J. P. Dunlop, Solar Photovoltaic Air Conditioning or residential buildings, Proceedings of the 1994 Summer Study on Energy Efficiency, FSEC, USA, Vol 3 188-198­1994

The Angular Variation Model gives smaller relative errors than the othertwo approximations. That is seen when figure 4 below is compared to figures 5 and 6.

Figure 4 Relative errors in absorbed power versus angle of incidence for all 62 studied panes for the Angular Variation Model.

Figure 5 Relative errors in absorbed power versus angle of incidence for all 62 studied panes for the Clear Pane Model.

Figure 6 Relative errors in absorbed power versus angle of incidence for all 62 studied panes for the Constant Value Model.

Future work will put emphasis on the following fields:

• Continuation of the system monitoring (first and second generation prototype) in order to implement and test the developed control algorithms.

• Technical redesign of the storage modules.

• Production of a second generation prototype module.

• Development of stable modified sorption materials.

The newly developed second generation prototype needs to be extensively tested, analysed and evaluated under laboratory and practical conditions as input for the finalisation of the product development and identification of the most attractive market.

Acknowledgements

We are grateful to our project partners from Fraunhofer Institute for Solar Energy Systems (Freiburg/Breisgau, Germany) and Sortech AG (Freiburg/Breisgau, Germany) for their valuable work which contributed to the success of the project. We thank the European Commission and the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) for financial support of the projects HYDES and MODESTORE.

References

• W. Mittelbach: Final Report HYDES Project. Final Report of a Joule III Project, European Comission 2001

• Tomas Nunez, Hans-Martin Henning, Walter Mittelbach: High Energy Density Heat Storage System — Achievements and Future Work, ISES Solar World Congress 2003, Goteborg, Sweden

measurements

M. J. Jimenez; B. Porcar; M. R. Heras

Department of Renewable Energies, "Bioclimatic Architecture Research Programme”, CIEMAT, Madrid, E-28040, Spain; Tel:+34 91 3466305,fax: +34 91 3466037, e-mail:

miose. iimenez@psa. es

Introduction

The use of passive design strategies to benefit from the solar energy in order to reduce heating and cooling loads in buildings but maintaining indoors comfort is a very important concern regarding environmental aspects.

The application of these design strategies requires an accurate knowledge on the parameters that characterise the thermal behaviour of each building component used, such as the heat transmission coefficient, U, and the total solar energy transmittance, g, values and time constants. These parameters are required to apply the mandatory national standards and regulations that impose the minimum requirements regarding energy consumption in buildings (eg. The Spanish NBE-CT- 79). The availability of these parameters for each component included in the building envelop is also important because they are required as input for most of the simulation programs which estimate heating and cooling loads and evaluate the thermal behaviour of buildings that include these components in its envelop.

In both cases, the accuracy in the final results depends on the accuracy on the estimation of the parameters of each individual component. It is possible to estimate these parameters, according to national standards, from tabulated values of the integrating parts of the component, but in this case their accuracy depends on the degree of knowledge of the composition of the enclosure. Outdoors testing (Vandaele, 1994) and in-situ measurements (ISO 9869:1994) are very useful and reliable alternative to provide more accurate estimations of these parameters.

This paper presents the experimental determination of the U value of each wall of a quite simple mono-zone building, located at the Plataforma Solar de Almerfa (Tabernas, Almerfa, Spain), by in-situ measurements and dynamical analysis. These values have been compared with those obtained from tabulated values according to national standards. Comparisons have been considered in order to obtain information on the predictable degree of agreement between both approaches.

The studied building is considered especially suitable for analysis as far as its simplicity and the high degree of knowledge about its construction and components allow undertaking relatively good estimations from tabulated values according to national standards in comparison to the usual quality of these calculations from tabulated values. Its performance is also interesting because it includes some passive strategies to reduce heating and cooling loads and to improve thermal comfort.