外文翻譯--集成太陽能加熱系統(tǒng)從最初的分級系統(tǒng)到動(dòng)態(tài)仿真（英文）

1、Integrated solar heating systems: From initial sizing procedure to dynamic simulationYoann Raffenel a,b,*, Enrico Fabrizio b,c, Joseph Virgone d,e, Eric Blanco a, Marco Filippi ca Laboratoire AMPERE, UMR 5005, E ´ c

2、ole Centrale de Lyon, Ba ?t. H9, 36 Avenue Guy de Collongue, 69134 Ecully, France b Centre de Thermique de Lyon (CETHIL),UMR 5008, INSA de Lyon, Domaine Scientifique de la Doua, Ba ?t. Freyssinet, 40 Rue des Arts, 69621

3、Villeurbanne, France c Dipartimento di Energetica (DENER), Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy d IUT A Lyon 1, Universite ´ de Lyon, 43 Bd du 11 Novembre 1918, 69622 VILLEURBANNE

4、Cedex, France e Laboratoire sciences de l’habitat, E ´ cole nationale des travaux publics de l’E ´ tat, Rue Maurice Audin, 69518 Vaulx-en-Velin Cedex, FranceReceived 14 February 2008; received in revised form 1

5、2 September 2008; accepted 19 October 2008 Available online 26 December 2008Communicated by: Associate editor C. Estrada-GascaAbstractThe sizing of the solar installation of an individual dwelling is a problem which can

6、be solved in many ways. The approach described in this paper is a simplified procedure of considerable interest. It requires only a small quantity of data and can be computed in a short time. The performance of this proc

7、edure was evaluated by a more complex sizing method based on detailed simulation. The simplified procedure was applied to the case of an individual dwelling using a solar collector field to produce domestic hot water and

8、 space heating. The building and the solar installation have then been modelled with the software TRNSYS 16 and their behaviour was simulated during a whole year. The results obtained are particularly close to the ones e

9、xpected by the simplified sizing procedure. ? 2008 Elsevier Ltd. All rights reserved.Keywords: Solar heating systems; Solar combisystems; Initial sizing; TRNSYS1. IntroductionThe exploitation of solar energy can be made

10、by means of procedures and techniques that are quite different (for example solar collectors or PV panels as regards a direct use of solar energy, biomass combustion or wind energy as regards indirect use of solar energy

11、) and that involve dif- ferent principles (thermal conversion in case of solar collec- tors, photovoltaic conversion in case of PV panels, photosynthesis in case of biomass, mechanical conversion in case of wind energy).

12、 In all cases, the main design and operation problem concerns the mismatch between theenergy demand (the load) and the energy supply (the solar energy) and this problem is usually addressed through the integration of sto

13、rage and/or a back-up energy source. There are many configurations that can be adopted, and the study of the optimization between the energy demand, the energy supply, the converters, storage and back-up sources characte

14、ristics, that can be called an integration problem, has to be at the foremost when designing and operating a system that exploit solar energy. This integration problem can be solved by determining all the relation betwee

15、n the different quantities that affect the performance of the solar system and then find the val- ues of the design parameter by optimizing the system once an objective function has been established, or by simulating a g

16、reat number of different cases and subsequently rank them in function of one, or of a combination, of perfor- mance parameters.0038-092X/$ - see front matter ? 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.solene

17、r.2008.10.021* Corresponding author. Address: Laboratoire AMPERE, UMR 5005, E ´ cole Centrale de Lyon, Ba ?t. H9, 36 Avenue Guy de Collongue, 69134 Ecully, France. Tel.: +33 472 186111; fax: +33 478 433717. E-mail a

18、ddress: yoann.raffenel@ec-lyon.fr (Y. Raffenel).www.elsevier.com/locate/solenerAvailable online at www.sciencedirect.comSolar Energy 83 (2009) 657–663F sav ¼ fsavðAc; V Þ ¼ X 2k¼0 ðmk ln V &

19、#254; nkÞ ? Ak c ð1ÞThe values of the m and n coefficients determined mini- mizing the quadratic difference between data and equation outputs through a reduced gradient optimization algorithm are the follo

20、wings:m0 ¼ ?2:17 ? 10?2; n0 ¼ 3:02 ? 10?2m1 ¼ 1:19 ? 10?2; n1 ¼ 2:18 ? 10?2m2 ¼ ?2:26 ? 10?4; n2 ¼ ?4:34 ? 10?4A good correlation coefficient R2, equal to 0.990, was obtained between values

21、simulated and calculated by Eq. (1). In Fig. 1 some Fsav curves are plotted for different stor- age volumes over the simulated values. Alone, the perfor- mance curve of Eq. (1) cannot, however, be useful to the initial s

22、izing since the fractional energy savings always increase for an increase in the collector area and storage volume. Thus, a second performance curve was determined to relate the mean annual efficiency of the solar combis

23、ystem in function of the variables Ac and V. The mean efficiency g was calculated as a ratio between the solar gains GS and the solar energy I for the same period of time. It takes into account:? the mean performance of

24、the solar collector during oper- ating conditions (the collector efficiency is greatly influ- enced by the fluid temperature, the solar radiation and the air temperature); ? the variability of the energy demand for heati

25、ng (profiles of the space heating and of the DHW heating); ? the dynamic of the storage (charge and discharge, water temperature in the tank).In this case a cubic function of the collector area Ac where the coefficients

26、of each term are a logarithmic func-tion of the storage volume V well suits the simulated data. This curve can be expressed asg ¼ fgðAc; V Þ ¼ X 3k¼0 ðmk ln V þ nkÞ ? Ak c ð2&

27、#222;where the values of the m and n coefficients determined minimizing the quadratic difference between data and equation outputs through a reduced gradient optimization algorithm are:m0 ¼ ?1:25 ? 10?2; n0 ¼ 0

28、:372m1 ¼ 1:80 ? 10?2; n1 ¼ 2:07 ? 10?2m2 ¼ ?9:84 ? 10?4; n2 ¼ 8:29 ? 10?4m3 ¼ 1:51 ? 10?5; n3 ¼ ?1:51 ? 10?5Also in this case, a good correlation coefficient R2, equal to 0.960, was obtained

29、. In Fig. 2 some g curves are plotted for different storage volumes over the simulated values: the efficiency decrease when increasing the collector area (even though, in this case, as predicted by Eq. (1) reported in Fi

30、g. 1, the fractional savings greatly increase with the col- lector area). The trade-off between the two Fsav and g curves can clearly be analyzed plotting the two quantities together: as reported in Fig. 3, it can be see

31、n that all the intersections between the two curves (points A0.2, A0.5, A1, . . ... in Fig. 3) occur for the same value of collector area. For the defini- tions of Fsav (the ratio GS/D between the solar gain and the heat

32、ing energy demand) and g (the ratio GS/I between the solar gains and the solar energy incident on the collec- tor), this value represents the collector area for which the solar energy I equals the heating energy demand D

33、. For this value of collector area (points A in Fig. 3) it is possible to obtain the couple of greater values of both Fsav and g. If the collector area is designed following this criterion, then the fractional energy sav

34、ings equal the system efficiency. Selecting a collector area smaller than the one of point A is not relevant since the efficiency is maximised in spite of a decrease in the solar gains. The point A, however, does00.20.40

35、.60.81Ac [m 2]Fsav [-]ValuesCurvesV = 4 m3V = 2 m3V = 1 m3V = 0.2 m30 5 10 15 20 25 30Fig. 1. Fractional energy savings in function of solar collector area: comparison between simulated values and performance curves

36、for different storage volumes.0 0 5 10 15 20 25 300.20.40.60.81Ac [m 2]η [-]ValuesCurvesV = 4 m3V = 2 m3V = 1 m3 V = 0.2 m3Fig. 2. Mean annual efficiency of the solar combisystem in function of solar collector area: