Category Archives: EuroSun2008-3

Linear concentrators with active dissipation systems which generate thermal energy

In 1981 Florschuetz [4] remarked that the use of air as an active refrigeration system is not a viable alternative because of its low thermal capacity and diffusivity. He found that water is a fluid whose properties allow for a better thermal interchange and consequentially the achievement of higher concentrations without the negative effects of the temperature over the PV cell efficiency.

After this study, a group of authors developed a series of active cooling systems using water (Edenburn, O’Leary and Clements, Chenlo and Cid, Russell). Although each system used the water cooling device to optimise conditions for electricity production, none of them analyse the possibility of taking advantage of the thermal energy produced by the warming up the water.

At present, there are two principal systems which optimise both the electricity production and the thermal energy production:

• CHAPS (Combined Heat And Power Solar), developed at the Australian National University. It consists of a parabolic concentrator with a ratio of 37X which focuses radiation onto a PVT module. The module converts the radiation into thermal and electrical energy with efficiencies of 57% and 11% respectively. The prototype was initially designed as a photovoltaic system with active cooling, the idea later evolved to use the water to capture the thermal energy. Reference data of the thermal gain achieved by the collector is not mentioned in any of the reference publications for the system [5].

• BIFRES, developed at the University of Lleida, is a system which concentrates radiation by Fresnel reflection to a concentration factor of 22X. The hybrid module operates with a nominal thermal efficiency of 59%, permitting the c-Si photovoltaic cells to operate at an optimum efficiency of 11.9% [2].

Both systems positively satisfy the requirements of actively cooling the cells whilst acting as a thermal collector with acceptable efficiencies, above 50%. However, in both cases the PVT module design is not straightforward. Both groups have opted for a tube of circular cross-section appended to an absorber on which the photovoltaic cells are placed. The two systems have significant differences: the heat sink is made of aluminium in the CHAPS system and of copper in the BIFRES system, also the tube developed at the ANU is furrowed with the goal of improving convection into the fluid.

After analyzing these two systems, some improvements may arise: It is well known that rectangular sections have higher Nusselt numbers than circular or square sections. A section with a higher aspect ratio (a), permits a greater thermal interchange into the fluid, where (a) is defined as the quotient between the long and short side of the rectangle [6]. Besides, an attractive concept such as the architectural integration is not well solved in the majority of PVT systems. As a consequence of their dimensions, PVT systems are only suitable for installation on flat roofs.

In this research is proposed, with the same concentration ratio than in the other systems explained before, to reduce the dimensions of the concentrator and the absorber to facilitate the integration in buildings.

Supervisory System

The Scada system was developed over the platform Axeda Supervisor Wizcon for Windows & Internet V8.2 [16]. The SCADA system used to implement this monitoring and control strategy permits the selective access to the application, depending on the user’s responsibility degree. In this paper we developed three user levels: Operators, Supervisors and Administrators. Several SCADA menus were built. The main characteristic of a SCADA Menu is to be simple, explicit and quick on transmitting the information to the operator or to the System administrator.

One of the developed Graphical User Interfaces (GUI) is shown in fig 9. As this SCADA platform is web enabled, all the GUI displayed data is also on-line accessible through the internet.

In fig. 9 it is shown the developed main menu for the sun-tracker system. The on-line available information, referring actual data from the tracker unit is: actual position for both axis, actual PV — power generated, max. daily PV-power generated, actual efficiency ratio.

4. Conclusion

This paper proposed the optimization of the electric energy production by photovoltaic cells through the development of an intelligent sun-tracking system. The developed solution has many advantages in relation to similar existing devices, as this system is autonomous regarding the information needed to process the optimal orientation and is intelligent in a way that it performs on-line monitoring of the photovoltaic energy production.

An experimental prototype was built and field results have proven the good performance of the developed tracking system.

The observed increase in power generation, in relation to other PV-systems, without tracking devices, is of similar magnitude (ca. 25%) as for other usual tracking solutions. However, this system has a relative advantage, as it measures exactly the controlled variable: the actual PV — power generation.

Подпись: Fig. 8. Control Algorithm for the Tracking system Box0: After reset is activated, the system stores the PV — power generated in the actual position, Pactual, in the variable Pin. The system searchs its reference — null position. It moves until it finds the hardhome position (both external proximity sensors on). In this position the system assumes the absolute orientation angles for both axis equal zero (a1 = a2 = 0). The maximal Power, Pmax is set to zero. Both counters, C1, C2, are loaded;

Box1: After start is activated, the system iniciates the search for the maximal power generated in axis 1, with an angle increment a10. The system stores the power generated in variable P1.

Box2: If P1 < Pmax, the system goes to Box 4, and follows for a new position;

Box3: If P1 > Pmax, this position is stored in the variables: a 1max, a2max. The max. Power value, Pmax is actualized with the new Power value P1;

Box4: Counter for axis 1 is updated;

Box5: After all orientations for axis 1 are evaluated, regarding a fixed orientation for axis 2, axis 2 is positioned in a new position, with an angle increment a20, and axis 1 returns to its initial position a1=0. The system re-initiates the search for the optimal orientation of axis 1, regarding the new position of axis 2. The information flux returns to box 1.

Box6: After all orientations for axis 1 are evaluated, regarding all different positions of axis 2, the system compares the maximal power found (Pmax) with the initial Power generated, before the search process had begun (Pin). If the new Power value is greater than a pre-defined gain, this new correspondent orientation (a1max, a2max) is sent to all park panels. If the power gain is not enough, the new found position is not to follow by the other PV-panels.

Подпись: Fig. 9. Sun Tracker System: SCADA main Menu

Box7: After a pre-defined time interval (K) the tracker system initiates a new complete search process in both axis. The information flux returns to box 0.


This work was partially funded by the FCT through program POCTI-SFA-10-46-IDMEC, subsidized by FEDER and by the Project PETER — PIC Interreg IIIA SP6.E53/03.


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[2] German Advisory Council on Global Change, 2003 (http://www. wbgu. de)

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[4] Atlas I, Sharaf A.; “A Novel on-line MPP search algorithm for PV arrays”; IEEE Trans. Energy Convers., 1996; 11 (4); pp. 748-754

[5] Hua, C., Lin, J.; “An on-line MPPT algorithm for rapidly changing illuminations of Solar arrays”; Renew Energy 2003; 28; pp. 1129-1142.

[6] Benlarbi K., Mokrani L., Nait-Said M., “A Fuzzy Global Efficiency Optimization of a Photovoltaic Water Pumping System”; Sol Energy 2004; 77; pp. 203-216.

[7] Hua C., Lin J.; “A modified tracking algorithm for maximum power tracking of solar array”; Energy Conversion and Management 2004, Vol. 45, pp. 911-925.

[8] Chen Y., Liu Y., Wu F.; “Multi-Input Converter with Power Factor Correction, Maximum Power Point Tracking, and Ripple-free Input Currents”; IEEE Trans. Power Electron. 2004, 19 (3), pp. 631-639

[9] http://solardat. uoregon. edu/ SolarPositionCalculatorhtml

[10] Hoppe D.; “Solar-Tracking Mirror with Radiation Sensor”; Publ. Nr. DE4425125; European Patent Office, esp@cenet database.

[11] F. R. Rubio, M. G. Ortega, F. Gordillo and M. Lopez-Martinez; “Application of new control strategy for sun tracking”; Energy Conversion and Management, Vol. 48, Issue 7, July 2007, Pages 2174­2184.

[12] Simatic Net — NCM S7 for Profibus/ FMS. SIEMENS 12/2001.

[13] System Software for S7-300 and S7-400 — Reference Manual, SIEMENS 08/2000; A5E00069892- 02

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Measurement of the slope errors of a linear PV/T Fresnel reflector

B. Abdel Mesih 1* , J. I. Rosell 1 , J. Illa 2, D. Chemisana 1

1 Department of environmental and soil sciences, University of Lleida, Spain
2 Department of computer science and industrial engineering, University of Lleida, Spain
* Corresponding Author, bahy@macs. udl. cat


The objective of this work is to measure the surface slope errors of the mirrors of the 22-
suns photovoltaic-thermal concentrator that is installed in the University of Lleida in Spain.

A set of photos are taken with a digital camera placed at a distance perpendicular to the mirrors plane which is oriented towards the camera. The analysis of the reflected pattern of the edges of a target on the mirrors shows the irregularities of the mirrors surface. The deformation of the observed pattern could be due to installation errors, misalignments, or bending of mirrors under to their own weight. A geometrical algorithm based on the principles of projective geometry is used with the aid of numerical software to analyze and detect the edges of the absorber. The aim is to find the distribution of actual normal vectors of each mirror strip and to calculate the root mean square error (RMSE). This work gives insight into the loss of optical quality due to reflector errors which affects both the electrical and thermal output of the concentrator severely.

Keywords: Solar concentrators, linear PV/T Fresnel reflector, surface slope errors

1. Introduction

The optical quality of reflectors in photovoltaic thermal concentrator systems affects both the electrical and thermal production drastically. Misalignments of the mirrors during the installation phase, problems with the holding structure, or surface dents, all contribute to both non-uniform illumination and temperature on the PV modules. The current produced by the PV cells, which are usually connected in series, is directly proportional to the incident radiation. Consequently, the cell that receives the least illumination is then the one that determines the power output of the whole PV module. The negative effect of non-uniform illumination on the performance of a whole concentrator system has been well shown by Franklin and Coventry [3].

There are several methods to quantify the slope errors of the reflector components of solar concentrators. Scanning Hartman Optical Tester (SHOT) and video-SHOT (VSHOT) have been used since the 1970’s with great success. There are a number of publications that focus on the principles of VSHOT and applications [4, 11-13]. Photogrammetry is another reliable method that is popular in the field of assessing the slope errors of solar concentrators [7-9]. The curvature of specular reflecting surfaces has been also addressed in a number of publications concerning deflectometry and deflectometric measurements [5, 6]. In this paper, a new approach presented by Ulmer et. al [10] is used to measure the surface slope errors of the PV/T generator installed in Lleida, Spain. The method is called the absorber reflection method (ARM). The method relies on the fact that an observer can easily detect the deformation in the reflecting surface when observing the irregularities in the reflection pattern of a target which has defined and known uniform
contours. The results obtained by the ARM shows big resemblance to the results obtained by photogrammetric methods in assessing the surface errors of parabolic troughs.

Load Prognosis

For an optimal operation of grids and cogeneration plants good prognoses of the expected loads (electric and thermal) and feed-in of fluctuating generation are essential. For this we suggest a statistic method with empiric formulas to fit the load. In several projects we tested an algorithm based on the method of multiple linear regression [4],[7]. The scheme of this algorithm is shown in Fig. 4.

Basis for this method is a database with a time horizon of at least one year, which contains the profile of the value y[t] to be predicted together with other data {z1[t], .., Zn[t]} that might correlate with y. These are calendar data (e. g. day of year) and weather data (e. g. temperature, global radiation). To keep the database as up-to-date as possible it is continuously actualised with the newest measurements

before the actual prognosis calculation. The method of multiple linear regression [8] estimates the given depended variable y[t] by a linear function y[t] = co + ci Xi[t] + c2 X2[t] + … + cn Xn[t] + e[t]

Подпись: Fig. 4. Scheme of the prognosis algorithm.

of the given independent variables {x1 [t], .., xn[t]}, where the factors {c0, .,cn} are unknown and e[t] gives the error for each time step.

The error is minimised with a least square estimation, which has got the advantage that it can be solved analytical with a linear set of equations. From experience we know, that the thermal load will not depend linear on the input variables. To integrate also nonlinear relations the variables xi[t] are introduced. They are defined as a function of the input data in the database {z1[t], .., zn[t]}:

xi[t] = f (zi[t],…,zJt]) (4)

In a pre-analysis we tested, which combination of input variables fits the load best and got for each hour a model equation. The regression analysis results in a specific formula for each hour of the day, e. g. hour = 13:

Pioad. iih = Cl + C2 • Sunday + c3 ■ doy2 + c4 ■ doy4

r, ump ■ r,,-hmp — r — limp’ <ч limp’ (5)

+C9 • sunrise + C10 • sunset


For the prognosis the multiple linear regression routine calculates the coefficients {c1, …, cn} for the chosen equation by use of the updated database. The resulting model is used together with weather forecasts from a commercial meteorological service. Fig. 5 shows the curve of a thermal load of a real district heating system and the prognosis which was predicted one day ahead.

Impact on overproduced power level

From the grid point of view, the instantaneous level of the overproduced power is critical, since it affects voltage levels locally in the grid. An analysis involving mean load cannot give any detailed insights into grid issues, but an average response in power overproduction to load matching measures can be determined. As an example, Figure 3 shows a duration graph over the overproduced power for the base case (case 0) and the two DSM cases (2a and 2b).

For the ALR 2 setup, the overproduced energy is heavily reduced, for the more extensive DSM scheme (case 2b) almost entirely. For the ALR 8 setup the effect is smaller since the amount of shiftable energy is smaller compared to the overproduction. A comparison with the panel orientation cases (not shown here) suggests that the DSM option is more effective at ALR 2 while the orientation options are more effective at ALR 8, since they shift more of the heavy overproduction from midday. A more comprehensive analysis of the impact on the overproduced power will be covered in [15].




For large system setups, corresponding to high penetration levels of PV, energy storage has the greatest potential of obtaining a better match between load and production in terms of solar fraction, although both DSM and PV array orientation options have comparable impacts. At more moderate overproduction, orientation and DSM options seem slightly better, because of energy losses in the storage medium.


[1] N. I. Carlstedt, B. Karlsson, E. Kjellsson, L. Neij, O. Samuelsson (2007), Konkurrenskraft for natansluten solel i Sverige (Competitiveness of grid-connected solar electricity in Sweden), Elforsk Report 06:57.

[2] PV-UPSCALE (2007), Publications review on the impacts of PV distributed generation and electricity networks, http://www. pvupscale. org.

[3] J. V. Paatero, P. D. Lund, Renewable Energy 32 (2007), 216-234.

[4] M. Thomson, D. G. Infield, IET Renewable Power Generation 1 (2007) 33-40.

[5] J. Widen, E. Wackelgard, K. Ellegard, Modeling household electricity load from time-use data. International Scientific Conference on “Green Energy with energy management and IT” in connection with the Swedish National Energy Convention 2008, Alvsjo fair, Stockholm, 12-13 March 2008.

[6] J. Widen, M. Lundh, I. Vassileva, E. Dahlquist, K. Ellegard, E. Wackelgard, Constructing load profiles for household electricity and hot water from time-use data — modelling approach and validation. Manuscript submitted to Energy and Buildings.

[7] A. Capasso, W. Grattieri, R. Lamedica, A. Prudenzi, IEEE Transactions on Power Systems, 9 (1994) 957-964.

[8] K. Ellegard, M. Cooper, electronic International Journal of Time Use Research, 1 (2004), 37-59.

[9] Swedish Consumer Agency, http://www. konsumentverket. se.

[10] Satel-Light, The European Database of Daylight and Solar Radiation, http://www. satel-light. com.

[11] P. Bennich, A. Persson, Methodology and first results from end-use metering in 400 Swedish households. In Proceedings of EEDAL 06 International energy efficiency in domestic appliances and lighting conference, Gloucester 21-23 June 2006.

[12] J. A. Duffie, W. A. Beckman (1991), Solar Engineering of Thermal Processes, John Wiley & Sons, Inc.

[13] D. L. King, J. A. Kratochvil, W. E. Boyson, W. I. Bower, Field experience with a new performance characterization procedure for photovoltaic arrays, 2nd World Conference and Exhibition on Photovoltaic Solar Energy Conversion, 1998.

[14] Meteotest, http://www. meteotest. ch.

[15] J. Widen, E. Wackelgard, P. Lund, Options for improving the load matching capability of distributed photovoltaics at high latitudes, manuscript to be submitted to Solar Energy.

Static surface vs. tracking concentrating surface

Another issue to take into account is that concentrating solar systems, with concentration ratio C=10, can make use only of the beam irradiation plus 10% of the diffuse one, roughly. On the contrary, non­concentrating systems make use of the global irradiation coming from the sun. Thus, the received global irradiation by a non-concentrating static surface was compared with the beam irradiation plus 10% of the diffuse onto a tracking concentrating surface (Table 4).

Table 4. Incident irradiation on a static non-concentrating surface and on a tracking concentrated surface. Static surface inclination from horizontal is 40° in Stockholm, 30° in Lisbon and 20° in Lusaka.

Static surface vs. tracking concentrating surface







Static non-concentrating surface G (kWh/m2,yr)




North-South tracking concentrating surface Gb + 10%*Gdiff (kWh/m2,yr)




Ratio Static/Tracking concentrating surfaces output




The global irradiation incident on a static surface is higher when compared with the beam irradiation plus 10% of the diffuse towards a tracking concentrating surface. This means that a non-concentrating fixed collector receives more usable irradiation than a tracking concentrating one like Solar8. Closer to the equator, the beam irrradiation values are higher and this result becomes less accentuated.

Summary and conclusions

PV-Wind-Hybrid systems are for all locations more cost effective compared to PV-alone systems. Adding a wind turbine halves the net present costs (NPC) for the coastal locations in the south of Sweden and cuts the NPC by one third for a location as Borlange with low wind speeds. The load that has to be supplied has of course a large impact on the system size and costs. The results from the simulations show that the NPC for a hybrid system designed for an annual load of 6000 kWh will vary between $48,000 and $ 87,000. Sizing the system for a load of 1800 kWh/year will give a NPC of $17,000 for the best and $33,000 for the worst location.

However, theses values are calculated for a capacity shortage allowance of 10%. The question is of course if such a shortage is acceptable in a single family house and if not what means could be applied to supply the remaining 10% and what would this cost. These questions have not been studied but as Figure 4 shows for most location it would increase the cost significantly if the last 10% should be supplied with the PV-Wind system. The cost per kWh electricity produced by a PV-Wind-Hybrid system varies between 1.4$ for the worst location and 0.9$ for the best location.


[1] Borowy, B. S., and Salameh, Z. M. (1994). "Optimum photovoltaic array size for a hybrid wind/PV system." Energy Conversion, IEEE Transaction on, 9(3), 482-488.

[2] Celik, A. N. (2002). "Optimisation and techno-economic analysis of autonomous photovoltaic-wind hybrid energy systems in comparison to single photovoltaic and wind systems." Energy Conversion and Management, 43(18), 2453-2468.

[3] Koutroulis, E., Kolokotsa, D., Potirakis, A., and Kalaitzakis, K. (2006). "Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms." Solar Energy, 80(9), 1072-1088.

[4] McGowan, J. G., Manwell, J. F., Avelar, C., and Warner, C. L. (1996). "Hybrid wind/PV/diesel hybrid power systems modeling and South American applications." Renewable Energy, 9(1-4), 836­847.

[5] Protogeropoulos, C., Brinkworth, B. J., and Marshall, R. H. (1997). "Sizing and techno-economical optimization for hybrid solar photovoltaic/wind power systems with battery storage." International Journal of Energy Research, 21(6), 465-479.

[6] Berruezo, I., and Maison, V. (2006). "Electricity Supply with PV-Wind Systems for Houses Without Grid Connection," Master thesis, Hogskolan Dalarna, Borlange.

[7] Pazmino, V. (2007). "PV-Wind Energy Hybrid Systems Techno-Economic Feasibility Analysis for Different Swedish Locations," Master thesis, Hogskolan Dalarna, Borlange.

Numerical analysis

2.1. General specifications

The configuration of the PVT module consists of a row of photovoltaic cells with a rectangular surface area of 1cm x 1m, placed at the top of the aluminium heat sink. The encapsulation can be divided into various elements.

1. — In the surface at which concentrated radiation is received, an EVA film is applied to the cells, and high absorption glass with low iron content is used as an outer skin. This reduces deterioration of the cells and minimises the thermal losses through the top of the module.

2. — Between the cell and the heat sink a strip of electrical insulation is inserted using a double sided adhesion (Chomerics Thermattach T404). This method considerably-simplifies the adhesion process, as it simultaneously serves to insulate the cell and to fix it in right position.

3. — Finally, the lateral and underneath faces of the heat sink are thermally insulated-with a plate of temperature resistant polypropylene.

image083 Подпись: Fig.2. Simulation Scheme.

The figure 2 shows a scheme of the proposed cooling system. Concerning to the boundary conditions they must be fixed in the numerical study. In the outer upper face of the cooling device a, Neumann boundary condition of 1000W/ m2 is applied. This represents the heat flow per unit surface area that the cells transmit to their back contact. The remaining lateral boundaries are considered to be adiabatic surfaces, assuming that the insulation is sufficiently wide to achieve this requirement. Finally, at the surfaces that represent the entry and exit of the fluid flow, the boundary conditions are fixed flow at the entrance and free flow at the exit.

As a line of symmetry exists in the geometry (Fig.1) only half of the system will be modelled.

The tube is made of aluminium (thermal conductivity k =202W/mK). The analysed cross sections are those of the usual commercial tubes with rectangular cross section. The only requirement is a fixed section at the upper face where to accommodate the row of PV cells (1cm width). In the table 1, a summary of the analysed sections is shown. The difference among these three sections relates to the height of the section, it varies from 7 to 27 and hence the aspect ratio increases.

Table 1. Dimensions of the commercial aluminium cross sections analysed in this research































The SDS process for silicon ribbon growth

Joao M. Serra*, C. Pinto, Miguel C. Brito, Jorge Maia Alves, Killian Lobato, Antonio Vallera

DEGGE/SESUL University of Lisbon
Campo Grande ED-C8, 1749-016 Lisboa, Portugal
Corresponding Author, imserra@fc. ul. pt


A lot of research has been done to try to reduce the costs of solar cells by developing ribbon growth techniques that bypass the ingot/wafering step. The SDS-Silicon on Dust Substrate process, here described, is a technique to produce ribbons directly from the gas phase. Test solar cells were fabricated on SDS ribbons as a demonstration of concept of this new technique. Keywords: Photovoltaics; Solar Cells; Ribbons

1. Introduction

A lot of effort has gone into reducing the costs of solar cells by bypassing the ingot/wafering process, which is currently the dominant industrial process. Early on it was realised that such a wasteful process could be avoided by the direct preparation of silicon sheet by ribbon growth techniques [1][2]. The SDS-Silicon on Dust Substrate process, described here, is a new method for the growth of silicon ribbons for photovoltaic applications.

Description of the PV/T concentrator

The system developed at the University of Lleida (Figure 1) is a two-axis sun tracking system using water as a working fluid. The absorber has 72 mono-crystalline Si solar cells which are adhered on top of two circular tubes. Water runs in these tubes to cool down the cells thus enhancing their efficiency and the outlet water is guided to a storage tank where it can be further utilized for domestic hot water production or running a solar-driven chiller. The 12 m2 reflecting system (receiver) is composed of 30 white mirrors that reflect light onto the PV focus band of 0.10 m width and 3.90 m long. The mirrors are of equal length but have unequal widths and are installed at various tilt angles. The solar cells are illuminated by approximately 22 times the solar beam irradiance. The generator’s rated power is 1 KWectrcial and 4 KWthermal.


Fig. 1. 22-sun PV/T concentrator