Category Archives: EuroSun2008-11

Comparison with a producer design software

The model performance with 2 different airside correlations (Wang et al. [12] for wavy fins and Wang et al. [10] for plain fins) was compared with Type1223new and the producer design software Guntner Product Calculator (GPC) of the company Guntner GmbH. Two staggered tube lay outs available in GPC (HX 1 and HX 2, heat exchanger length of 1.25 m and height 1 m, 10 passes) with wavy fins (corrugation angle = 15°) were considered. For both geometries the heat transfer rate, calculated by the model with the correlation for wavy fins, is about 10% for HX 1 and less than 5% for HX 2 lower than that of the GPC, (Fig. 4). It has to be noted, that transverse tube pitch Pt in HX 1 is out of the validity range of the correlation for wavy fins, extrapolation of the correlation is in general not recommended. The heat transfer rate, calculated by the model for plain fins, is lower than the GPC heat transfer rate too (Fig. 4), which is plausible. However, HX 1 is also out of the validity range of the plain fin correlation, the deviation of this correlation to the GPC for HX 1 is even smaller than that of the wavy fin correlation, probably because of the less complex structure. Unlike these correlations, Type1223new with the Elmahdy and Biggs [5] correlation for plain fins gives higher heat transfer rate values than the GPC. It is, however, unfeasible that plain fins have higher heat transfer coefficient than wavy fins (compare with [20]).

Подпись: Fig. 4 Heat transfer rate calculated by the model (as plain and wavy fins), Type1223new and GPC for different air flow rates and two geometries (left for HX 1, right for HX 2).

The airside pressure drop, determined with the correlations for plain and wavy fins, is significantly lower than that, calculated by the GPC, Fig. 5. Whereas liquid-side pressure drop calculation slightly overestimate the pressure drop calculated by the GPC and is in agreement with the GPC when calculated as smooth tubes.

image274,image275
image276

Fig. 5 Airside pressure drop calculated by the model (as plain and wavy fins) and GPC for different air flow
rates and two geometries (left for HX 1, right for HX 2).

2. Conclusion

A model for fin-and-tube heat exchangers, which is based on empirical heat transfer and flow friction correlations, is presented here. The selected correlations are developed with larger data base and have complete description of the reduction method than the one used in Type1223new. In general one needs to be careful with empirical correlations, especially with complex ones, and one needs to prove simulation results. It is not recommended to extrapolate the correlations for configuration outside of the validity range. If configuration outside of the validity shall be simulated (e. g. for optimization of heat exchanger configuration) it appears to be sensible to use less complex correlations, e. g. Wang et al. [10] instead of Wang et al. [12].

Acknowledgements

The authors would like to express their gratitude to the Volkswagen Foundation, Germany for the financial support.

Nomenclature

Af

m2

minimum flow area

Q

W

heat transfer rate

Aface

m2

frontal area

Re

Reynolds number

Ai

m2

tube inside surface area

T

°C

temperature

Ao

m2

total airside surface area

U

W/m2K

heat transfer coefficient

C

W/K

heat capacity rate

Sf

m

fin thickness

Dc

m

collar diameter

є

heat exchanger effectiveness

Di

m

tube inner diameter

n

fin efficiency

Do

m

tube outer diameter

0

0

fin corrugation angle

f

friction factor

P

kg/m3

density

G

kg/m2s

air mass flux based on

z

ratio of minimum flow area

minimum flow area

to face area

j

=Nu/(RePr1/3)

Subscripts

Colburn factor

k

W/mK

thermal conductivity

1

airside inlet

N

number of tube rows

2

airside outlet

Pi

m

longitudinal tube pitch

i

tube inner side

Pt

m

transverse tube pitch

m

mean

Pr

Prandtl number

min

minimum value

References

[1] E. Frank, K. Vajen, A. Obozov, V. Borodin (2006): Preheating for a District Heating Net with a Multicomponent Solar Thermal System, Proc. EuroSun 2006, Glasgow

[2] Guntner GmbH (2007), personal communications.

[3] Brandemuehl, M. J., HVAC 2 Toolkit: A Toolkit for Secondary HVAC System Energy Calculations, ASHRAE 629-RP, Joint Center for Energy Management, University of Colorado, 1993

[4] Chillar, R. J, Liesen, R. J., Improvement of the ASHRAE secondary HVAC toolkit simple cooling coil model for simulation, Proceedings of the 1st SimBuild Conference, International Building Performance Simulation Association, 2004

[5] Elmahdy, A. H and Biggs, R. C., Finned tube heat exchanger: correlation of dry surface heat transfer, ASHRAE Transactions Vol. 85, Part 2, 1979

[6] Haaf, S., Warmeubergang in Luftkuhlern, pp. 435-491, in Plank, R., Handbuch der Kaltetechnik,

Springer Verlag, Berlin, 1988

[7] Wang, C. C., Chang, C. T. (1998), Heat and Mass Transfer for Plate Fin-and-Tube Heat Exchangers, with and without Hydrophilic Coating, Int. J. of Heat and Mass Transfer 41, 3109-3120

[8] Wang, C. C., Hsich, Y. C., Chang, C. T and Lin, Y. T. (1997), Performance of Finned Tube Heat Exchangers under Dehumidifying Conditions, J. Heat Transfer 119, 109-117

[9] Wang, C. C., Chi, K.-Y. (2000), Heat transfer and friction characteristics of plain fin-and-tube heat exchangers, Part I: new experimantal data, Int. J. of Heat and Mass Transfer 43 (2000), 2681-2691

[10] Wang, C. C., Chi, K.-Y., Chang, C.-J. (2000), Heat transfer and friction characteristics of plain fin-and — tube heat exchangers, Part II: Correlations, Int. J. of Heat and Mass Transfer 43 (2000), 2693-2700

[11] Wang, C. C., Lin, Y.-T., Lee, C. J. (2000), An airside correlation for plain fin-and-tube heat exchangers in wet conditions, Int. J. of Heat and Mass Transfer 43 (2000), 1869-1872

[12] Wang, C. C., Hwang, Y.-M., Lin, Y.-T. (2002), Empirical correlations for heat transfer and flow friction characteristics of herringbone wavy fin-and-tube heat exchangers, Int. J. of Refrigeration 25, 673-680

[13] Pirompugd, W., Wongwises, S., Wang, C. C. (2006), Simultaneous heat and mass transfer characteristics for wavy fin-and-tube heat exchangers under dehumidifying conditions, Int. J. of Heat and Mass Transfer 49, 132-143

[14] Jacobi, A. M., Park, Y., Tafti, D., Zhang, X. (2001), As assessment of the state of the art and potential design improvements for flat-tube heat exchangers in air conditioning and refrigeration applications — Phase I, Final Report. ARTI 21-CR Program Contract No. 605-20020

[15] Schmidt, Th. E. (1949), Heat transfer calculations for extended surfaces, Refrigerating Engineering, April 1949, 351-357

[16] Perrotin, T. and Clodic, D. (2003), Fin efficiency calculation in enhanced fin-and-tube heat exchangers in dry conditions, Proc. Int. Congress of Refrigeration 2003, Washington, D. C.

[17] Engineering Science Data Unit 86018 with Amendment A, ESDU International plc, London, 1991, pp. 92-107

[18] Shah, R. K. and Seculic’, D. P. (2003), Fundamentals of heat exchanger design, John Wiley & Sons Inc.

[19] Wagner, W. (2001), Stromung und Druckverlust, 5. Auflage, Vogel Buchverlag

[20] Gomini, G, Nonino, C. and Savino, S. (2003), Effect of space ratio and corrugation angle on convection enhancement in wavy channels, Int. J. of Num. Methods for Heat&Fluid Flow Vol. 13, No. 4, 500-519

Simulations

The simulation tool allows the user to choose different parameters related with the simulation process: time-step, accuracy, etc. The smaller the time-step, the longer the simulation time but the more precise are the results concerning the PCM interaction. This statement has to be taken into account when a PCM simulation is carried out. It was checked in previous simulations that bigger time-steps (to perform faster simulations) hid the operation of the PCM.

The length of the simulation can be chosen by the user going from daily simulations to two years simulation. Four different climates can be selected representing the four most common climates in Europe: Stockholm (Sweden) for a moderate northern climate, Zurich (Switzerland) for a moderate central climate, Barcelona (Spain) for a coast Mediterranean climate with high humidity and temperature in summer but a mild winter, and Madrid (Spain) with a continental Mediterranean climate with high temperature but low humidity in summer. The climate chosen for the simulations carried out was Madrid.

The building simulated is a two 70 m2 storey single family house facing south. Four different buildings can be selected and their differences depend on the energy demand of the building, existing an energy demand of 15, 30, 60 o 100 kWh/m2. Even a 100 kWh/m2 without shading can be chosen in order to simulate cooling demand. The 60 kWh/m2 was the selected house for the simulations performed.

The auxiliary system had a nominal power of 10 kW and the water introduced into the store was heated up to 63 °C (set point). The collectors field is 10 m2 of flat plate collectors facing south with a slope of 45 °C. The storage tank volume is 800 L following the recommendations of W. Weiss [6].

Two different types of simulations were carried out. In the first one, the aim was to observe the influence of some parameters in the result of the simulations. The parameters changed were the different inlets and outlets of the store and the position of the temperature sensors that operates the auxiliary system. Annual simulations were carried out and the results were evaluated for every month
and every week. Temperatures into the store and in every inlet and outlet of the tank as well as mass flow rates were the values checked to observe the influence of the PCM in the system behaviour. Fig. 2 shows the relative position of each sensor into the store.

image010 image011 image012 Подпись: Variable Description Tfluid4 Fluid temperature at sensor 4 Tfluid3 Fluid temperature at sensor 3 Tfluid2 Fluid temperature at sensor 2 Tfluid1 Fluid temperature at sensor 1 Tpcm PCM temperature Tpcm PCM temperature TSA Water temperature from store to auxiliaiy TAS Water temperature from auxiliary to store TSB Water temperature from store to space heating TBS Water temperature from space heating to store TSD Water temperature from store to DHW TXdS Water temperature from DHW heat exchanger to store TSC Water temperature from store to solar collectors TXsS Water temperature from solar collectors heat exchanger to store Tssa1 First on/off auxiliary temperature sensor Tssa Second on/off auxiliary temperature sensor

The second set of simulations was mainly focused on the influence of the PCM. Three different values of the Parea ratio were simulated: 0.25, 0.5 and 0.75. Also the geometry of the module was changed, different lengths of the PCM modules and different diameters were simulated. For a given PCM mass, the thinner the module was, the higher the number of modules into the storage. Also two different kind of PCM were simulated into the store focused in the two different demands. The sodium acetate — graphite compound for the DHW demand and placed at the top of the tank and the RT48 paraffin for the space heating demand and placed in the middle of the tank.

TSC

Подпись: TXdS

Fig. 2. Position of the monitored sensors inside the storage tank

More results about case 2

Cases 2A and 2B deal with photovoltaic panels, table 4 shows field production on the whole year. PV field feeds grid network, so electricity generation can be done when vapour compression chiller is not operating. Conservative shading assumptions is taken for all other results. For case 2A, PV field produces more than the whole vapour compression chiller electricity consumption, thus the auxiliaries consumption will be decreased respectively by 2.04, 3.68 and 6.31 kWh/(m2 year) for Paris, Stockholm and Lisbon.

energy

(linear shading)

energy

(conservative

shading)

Paris

81.43

71.76

Stockholm

74.18

60.72

Lisbon

151.70

128.93

Table 4. PV energy production [kWh/(net_panel_area year)]

2.3. More results about case 3.

Simulations run for case 3 have been optimised to minimise boiler gas consumption. For each location it results a panel slope, a storage tank volume. A summary of results dedicated to case 3 is presented in table 5. Figures given are only about heating and cooling production consumption.

Gas cons

Electricity

cons

Solar

fraction

Solar

Energy

Solar energy

Electrical

COP

m2 coll by kWcold

Pannel

slope

storage

tank

case 3A

kWh/(m2

year)

kWh/(m2

year)

%

kWh/(m2

year)

kWh/(coll_net_area

year)

coll_net_area/ kWc nominal

degree

m3

Paris

60.67

2.92

45

43.25

380.73

13.35

1.35

15.00

7.00

Stockholm

99.79

2.11

31

38.70

340.64

13.99

1.35

15.00

8.00

Lisbon

9.08

4.85

93

82.21

723.72

10.94

0.95

25.00

11.00

case 3B

Paris

92.08

2.23

13

12.48

439.29

15.89

0.34

15.00

3.00

Stockholm

126.15

1.53

10

12.14

427.44

16.08

0.34

15.00

3.00

Lisbon

63.41

3.58

32

27.19

957.34

14.53

0.24

25.00

3.00

Table 5. Case 3 summary

Some details should be given on this table: solar energy is the heat collected by the solar field and feeding storage tank; solar fraction is computed following equation 1. Table 6 proposes primary energy savings by net collector area for case 3A. It can be put in relation with table 4 given for case 2 (table 4 values must be multiplied by 2.5 to have primary energy).

Подпись: (equ. 1)Solar energy

Solar fraction =

(Heating load + Chiller hot water consumption)

Location

CASE 3A

Primary energy savings by area of collector

Paris

51.67

Stockholm

107.60

[kWh/(net_coll_area year)]

Lisbon

225.02

Table 6. Primary energy savings by collector area

3. Conclusion

In this work, design and energy performance of different kinds of air conditioning system were analysed. A complete building simulation model was developed with parameters found in IEA ECBCS Annex 48 research project. Heating and cooling emission and distribution systems were also defined as well as heat/cold production devices. This simulation has been run in three different locations. The comparison between three cases gives the potential energy savings of two solar technologies in relation to classical air-conditioning. A first analysis of auxiliaries showed that they have a huge weight in the primary energy balance. For case 1, it varies from 60% in Stockholm to 80% in Lisbon. Therefore it shows an important energy savings potential. When using classical vapour compression chiller and no solar energy, cooling cost less primary energy than heating due to COP higher than 2.5 (converting net energy to primary energy for Belgium). If solar energy conversion technology is implemented, a key point is available area for installing panels. In each case (A or B), primary energy savings are higher using PV panels instead of thermally driven chiller (assisted by solar thermal panels). It is another important result of this study. PV panels are directly connected to grid, then solar energy is use even if the building has low needs (e. g. during the weekend). For case 3.B (12 floors), solar fraction is very low, operating this system consumes more energy than classical air-conditioning. A better control can reduce this trend but a much higher solar fraction is required to save primary energy.

Systems costs have not been approached in this study. If this analysis is performed, the comparison should be done between solar and classical air-conditioning. An important point for PV is that, nowadays, electrical energy can be sold by the producer at a very interesting price. Moreover in some countries, such Belgium, kWh photovoltaic are paid directly at the production, so money can be saved even if electricity is not used in the building. Solar thermal energy has no such high financial incentive.

References

[1] W. Pridasawas (2006). Solar-Driven Refrigeration Systems with Focus on the Ejector Cycle, Doctoral

Thesis, Royal Institute of Technology, KTH, Sweden

[2] TRNSYS simulation studio, Version 16.00.0038 Licensed to Universite of Liege

[3] Stabat P. (2007). IEA48 — Description of Type 1c air-conditioned office buildings for simulation test,.IEA — ECBCS Annex 48 working document

[4] ALESSANDRINI J. M. et al. (2006) Impact de la gestion de l’eclairage et des protections solaires sur la consommation d’energie de batiments de bureaux climatises, Climamed, Lyon, France, 2006

[5] Project PVGIS : PV Estimation Utility tool : http://re. jrc. ec. europa. eu/pvgis/index. htm PVGIS © European Communities, 2001-2008

[6] Water Fired Chiller/Chiller-Heater WFC-S Series: 10, 20 and 30 RT Cooling, http://www. yazakienergy. com/waterfiredperformance. htm

[7] Henning, H.-M. (2008). Solar Cooling Components and Systems — an Overview, proceedings Solar Air­Conditioning international seminar, 11th June 2008, Munich, Germany

[8] U. Speicher (2008). Demand and market development, proceedings Solar Air-Conditioning international seminar, 11th June 2008, Munich, Germany

[9] Henning, H.-M. (2007). Solar-Assisted Air-Conditioning in Buildings, A Handbook for

Planners (Second Revised Edition), Springer-Verlag/Wien.

Simulation of Thermosiphon Solar Hot Water Systems. UsingMatlab/Simulink and Carnot

S. Brandmayr1*, M. Konrad1, W. Zorner1 and V. Hanby[2]

1 Ingolstadt University of Applied Sciences — KompetenzzentrumSolartechnik, Esplanade 10,

85049 Ingolstadt, Germany

2 De Monfort University, Institute of Energy and Sustainable Development, The Gateway,
Leicester LE1 9BH, United Kingdom
* Corresponding Author, sebastian. brandmayr@fh-ingolstadt. de

Abstract

This paper describes with the R&D activities at Ingolstadt University of Applied Sciences in terms of thermosiphon solar hot water systems. The simulation tool Matlab/Simulink and CARNOT was enhanced by a double mantle heat exchanger storage in order to be able to investigate the behaviour of all kinds of thermosiphon systems in theory. Taking data measured at the university’s thermosiphon testing rig into the simulation models, provides the possibility to improve systems by all relevant parameters without performing additional outdoor tests.

Keywords: simulation, Matlab/Simulink, thermosiphon system, storage, development

1. Introduction

Thermosiphon solar hot water systems have been a subject to R&D activities of the Kompetenzzentrum Solartechnik (Centre of Excellence for Solar Engineering) at Ingolstadt University of Applied Sciences since 2004. After building up a test rig, several thermosiphon systems were tested according to the specifications given in ISO 9459-2 [1]. In addition to that, tests according to methods and procedures developed at Ingolstadt University have been carried out in order to learn about the system’s behaviour under special conditions, e. g. its stagnation behaviour.

In the end of 2007, a R&D project was started which aims at the development of an optimised thermosiphon system based on scientific results. A market analysis carried out beforehand showed that most thermosiphon systems are still developed through trial and error [2]. This project, however, aims at demonstrating a closed development cycle. This cycle includes the analysis of thermosiphon systems in theory, the transfer of the mathematical model into simulation, the design of a prototype based on the simulation results and, eventually, the testing of the prototype in order to maximize the system performance and to achieve validation of the computer model. This validated system model is going to offer the project partner, a manufacturer of solar thermal applications, the possibility of adapting their thermosiphon systems to the customers’ and climatic conditions.

blockset (Conventional And Renewable eNergy systems Optimization Toolbox [4]), which is a tool for the calculation and simulation of the thermal components of heating systems with regard to conventional and regenerative elements, was used. It provides models for heat sources, storage systems, hydraulics and fundamental material calculation as well as the possibility of integrating further models. The models used, except the developed double mantle heat exchanger storage, were validated by Hafner et al [4].

Existing district heating grid

The existing district heating grid with a total grid length of approx. 34 km is powered by a gas-fired power plant (Fig.1) and has an annual heat demand of 156 GWh, the peak heat load is in the amount of 72 MW. The power plant is joined with a water-based thermal storage tank with a total storage volume of 5000 m3 and can store a heat quantity of 250 MWh in the operable temperature range.

Подпись: 250 MWh120’C

ізоот district heating grid

Fig. 1: Existing district heating with a combined gas and steam cogeneration plant

Effect of evaporation heat loss coefficient at the swimming pool

By running the model of the system for swimming pool operation with inputs from meteorological models, we can compare the calculated pool temperatures determined by different recommendations for the evaporation heat loss coefficient using different sources from relevant literatures.

Evaporation causes the dominating part of heat losses at swimming pools. It normally accounts for more than 60% of the total energy losses [6]. The mostly used equation for determining the evaporation heat loss power at the water surface is the following:

Подпись:Подпись: (1)Q = A. h

z—eva pool /leva

where

Подпись: Qeva A ^pool heva Pv, sat {Tpool} Pv,amb evaporation heat loss power at the swimming pool, W, swimming pool surface area, m2, evaporation heat loss coefficient, W/(m2Pa),

vapour pressure of saturated air directly at swimming pool temperature, Pa, vapour pressure of ambient air, Pa.

The evaporation heat loss coefficient can be determined as

heva = a + b • W>t, (2)

where

w is the wind speed at the swimming pool, m/s, a, b and n are constants.

For the value of a , b and n different references [10], [11], [12] and [13] contain recommendations (see in Table 1).

Table 1. Recommendations with adequate sources for the constants of evaporative heat loss coefficient.

a

b

n

Source

Height of relevant

wind speed in meters

4,523

5,088

0,84

Richter, 1969 [10]

1,0

5,058

6,690

1

ISO TC 180/ SC 4 N 140 [11]

0,3

8,5

5,08

1

Rowher, 1931 [12]

0,3

8,866

7,813

1

HVAC Handbook, 1987 [13]

0 — on ground level

According to the descriptions in this paper the model have been run using meteorological models. Specifications for the calculations are as follows:

The modelled day is a clear day [3] with number 163 (12 June).

Irradiance, ambient temperature, wind velocity is determined by the model.

Air humidity is fixed to be constant, ф=0,65.

There is no auxiliary heating.

The initial swimming pool temperature is 25°C.

image40

Fig. 6. Comparison of the swimming pool temperatures affected by the evaporation heat loss coefficient.

The biggest difference of the calculated swimming pool temperatures is in the cases of using the recommendations by Richter and by the HVAC Handbook. Namely the difference has a mean value of

0, 76°C, maximum value of 1,25°C, residual value, at the end of the modelled day, of 0,9°C.

References

[1] I. Farkas, Z. Rendik, International Journal of Ambient Energy, 14, 2 (1993) 59-68.

[2] J. A.Duffie, W. A.Beckman, (1991). Solar Engineering of Thermal Processes, John Wiley and Sons, New York.

[3] Gy. Szabo, Zs. Tarkanyi, (1969). Solar radiation data for the planning in building industry, Institute for Building Sciences, Budapest (in Hungarian).

[4] J. Buzas, I. Farkas, A. Biro, R. Nemeth, Mathematics and Computers in Simulation, 48, 1 (1998) 33-46.

[5] J. Buzas, I. Farkas, The 3rd ISES-Europe Solar Congress (EuroSun 2000), Copenhagen, Denmark, June 19­22, 2000, CD-ROM Proceedings, 9.

[6] E. Hahne, R. Kubler, Solar Energy, 53, 1 (1994) 9-19.

[7] B. Molineaux, B. Lachal, O. Guisan, Solar Energy, 53, 1 (1994) 21-26.

[8] I. Farkas, I. Vajk, Energy and the Environment, I /ed. by B. Frankovic/, Croatian Solar Energy Association, Opatija, October 23-25, 2002., 91-99.

[9] B. Bourges, (1991). European simplified methods for active solar system design. Kluwer Academic Publishers for CEC.

[10] D. Richter (1969). Ein Beitrag zur Bestimmung der Verdunstung von freien Wasserflachen dargestellt am Beispiel des Stechlinsees, Abhandlung des Meteorologischen Dienstes der DDR Nr. 88 (Band XI), Akademie- Verlag, Berlin.

[11] ISO/TC 180/SC 4 N 140, Solar Energy — Heating Systems for Swimming Pools — Design and Installations.

[12] Rowher, United States Department of Agriculture, Tech. Bulletin 271 (1931, December).

[13] HVAC Handbook (1987). Section 20.8.

A GIS-BASED DECISION SUPPORT TOOL FOR. RENEWABLE ENERGY MANAGEMENT AND PLANNING IN. SEMI-ARID RURAL ENVIRONMENTS OF NORTHEAST OF

BRAZIL

PART II — THE SOFTWARE AND ITS USE

C. Tfba1*, A. L. B. Candeias2, N. Fraidenraich1, E. M. de S. Barbosa1, P. B. de Carvalho

Neto3 and J. B. de Melo Filho3

1Departamento de Energia Nuclear da Universidade Federal de Pernambuco
Av. Prof. Luiz Freire, 1000 — CDU, CEP 50.740-540, Recife, Pernambuco, Brazil
2Departamento de Engenharia Cartografica da Universidade Federal de Pernambuco
Av. Academico Helio Ramos, s/n — CDU, Recife, Pernambuco, Brazil
3Companhia Hidro Eletrica do Sao Francisco — DTG — CHESF
Rua Delmiro Gouveia, 333 — Bongi, CEP 50761-901, Recife, Pernambuco, Brazil
Corresponding Author, tiba@ufpe. br or chigueru. tiba@pa. cnpq. br
Abstract

This work describes the functionalities of the SIGA SOL 1.0 — Geographic Information System Applied to Solar Energy. The prototype of the GIS tool is made up of three principal blocks: management of installed renewable systems, planning of inclusion of new renewable systems and updating of the data bank. The SIGA SOL 1.0 has a total of 80 layers of information that permit the realization of spatial analyses on management and planning of renewable sources of energy at a macro-spatial level (state) and local (municipality). The system was developed particularly for PV systems as a possible support tool for management and planning of the Program of Energy Development for the States and Municipalities (PRODEEM), a program for inclusion of photovoltaic solar energy on large scale, in the rural medium, conducted by the Ministry of Mines and Energy of Brazil.

Keywords: GIS, Planning and Management, Photovoltaic solar energy, Functionalities, PRODEEM

1. Introduction

The GIS is a valuable tool for assesment and development of the use of renewable energy resources in extensive regions because it is a tool that is especially adequate for analyzing the spatial variabilities of the resource, as also for resolving problems of management and planning of programs for installation of decentralized systems, that are characterized by a large spatial dispersion. It can be seen as a support system for decisions that integrate spatially referenced data in an ambient of answers to problems. A GIS groups, unifies and integrates information, thus making such information available in a more accessible manner, and it puts old information in a new context. In this project, the GIS is used as tool that permits the integration and processing of information coming from diverse sources. From this it is possible to use it in the elaboration of strategies for implanting and management of the rural electrification programs with renewable sources of energy.

Potential materials for polymeric collectors

Although the approach for developing polymeric collectors is rather an approach from the material side, some requirements for the use in domestic hot water heating and possibly heating support should be met regardless of the used material. It is very important, that temperatures of up to 90 — 100°C are tolerated. In addition, UV-stability is essential as well as chemical resistance to the heat transfer fluid. Other properties that are important in the end are e. g. the absorption, heat conductivity, mechanical stability and processability.

Some appropriate polymers and a selection of important properties are presented in table 1. They have been used for the different calculations and might be candidate materials for solar thermal applications. The values used are a compilation from various sources.

Most thermoplastics — including the ones mentioned in the table — are extrudable, so the advantages of this well-known, effective continuous process can be used. However, it seems to be impossible to find one polymer that fulfils all the aforementioned needs as it is. Thus, one has to look for possibilities to modify polymers in order to serve one’s purposes. Additives and fillers might be used to increase the heat conductivity, as well as the heat stability and they can be used as a protection against UV-radiation if no special UV-screen on top of the polymer is used.

Table 1. Properties of contemplated polymers

Polymer

Optical

properties

UV-

stability

Heat

conductivity in W/mK

Max. operating temp. in °C

Heat deflection temp. in °C HDT/A

Youngs modulus in N/m2

PMMA

transparent

yes

0.19

75-90

95

3.20E9

PC

transparent

no

0.21-0.24

130

128

2.30E9

PE-HD

translucent

limited

0.42-0.43

80-90

49

1.00E9

PP

translucent

limited

0.22

90-100

55

1.45E9

POM-C

opaque

limited

0.31

90

105

2.43E9

PPS

opaque

limited

0.25

180-200

137

3.30E9

PPO

opaque

limited

0.19-0.22

105

115

2.25E9

Characterisation of Optical Parameters by Ray-tracing Simulations

1.1. Modelling of Materials

For an accurate simulation result it is essential to truthfully reproduce the optical properties of the different materials of the thermal collector. That means to clearly define for example the geometrical dimensions since they correlate directly with the IAM-values. For this purpose the program OptiCAD offers the opportunity to check the defined geometrical, energy-related and optical parameter by a visual 3-D presentation which is based on the entered data. This is very helpful because non-conformances and errors in entered data can be identified very quickly.

Подпись:
The absorber and the glass cover of a flat-plate collector represent the most relevant optical units for a ray-tracing simulation. Figure 1 shows the interaction of a light beam with two transparent covers and an absorber. Effects like refraction of rays and multiple reflections of them within the glass covers as well as between them and the absorber are well to be distinguished.

In OptiCAD, the optical properties of the solar glass can be calculated by declaring the absorption coefficient and the refraction index. The transmission of solar radiation incident under a specific angle is calculated in the program by applying the Fresnel equations.

The optical properties of the absorber are implemented in OptiCAD according to their measured data. In addition to the capability of absorption the fraction of reflection under different incident angles plays an important role since the portion of reflected radiation increases with increasing incidence angle.

The mode of reflection of rays (direct or diffuse) at the reflectors of concentrating collectors is as substantial as the fraction of reflection. Modelling of scattered reflection in OptiCAD has been treated in [1].

Due to polarisation of light after passing one glass cover it is important particularly in case of collectors with multiple covers to investigate the optical characteristics by utilising a polarised light source. The software OptiCAD then is able to detect the state of the light’s polarisation after passing through the transparent covers and incorporates such effects in its simulation calculations.

image311

Fig. 2. Comparison of measured and simulated transmission of polarised light of one solar glass

In Figure 2 the measured transmittance of one antireflective treated solar glass weighted with the solar spectrum AM 1.5 for s-, p — and non-polarised light is plotted over the incidence angle. The transmittances simulated with the ray-tracing program OptiCAD are also shown in the figure for comparison. It can be seen that the curves fit very well, whereby the adequate performance of the software is demonstrated.

. The Temperature Field in the Plate between Tubes

Assuming that the process is stationary, the temperature field in the OiABC section in the Descartes coordinate system O1xz with O1 as the initial point is described by the Laplace equation

[4] :

52 71 52 71 (1)

1 1 = 0, дx2 dz2

image077 image078

We will introduce dimensionless variables and parameters [5], the dimensionless temperatures will be described by the formulae:

where

2 is the heat conductivity of the collector plate, W/m-K; q is the density of the solar heat flow, W/m2; h is the plate’s thickness, m.

2b is the distance between the tubes’ axes, m; r0 is the inner radius of a tube, m.

The Laplace equation and boundary conditions in the dimensionless form will be:

д 2©1 + d 2©1 0. dt2 дд2 ;

(6)

д©дМ= Q ;

дд

(7)

д©1 (t,0) =

дд ’

(8)

д©1 (0,?) = 0.

дt ’

(9)

(10)

The solution to the problems (6)-(10) is

©1 Ы=Q fe2 V)+1-