Quality assurance of solar thermal systems with the ISFH- Input/Output-Procedure

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1 Quality assurance o solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch * and Klaus Vanoli Institut uer Solarenergieorschung Hameln (ISFH), Am Ohrberg 1, Emmerthal, Germany * Tel. +49 (0) , Fax: +49 (0) , Abstract Input/Output-Controllers or in situ and automatic unction control o solar thermal systems that were developed within the research project have been installed in 1 systems. Ater ive years seven solar thermal systems beneited rom the installation o I/O-Controllers by detecting ailures several times. In three systems the I/O-Controllers were even helping to optimize the system perormance. The accuracy o the simulation model has been validated against data rom measurement. The average deviation is less than 10 %, which is acceptable because the uncertainty o the procedure is about 7 %. The uncertainty was determined in a sensitivity analysis concerning the uncertainties o parameters and measurement. The simulation model is solvable analytically and enables low costs or I/O-Controllers, because it can be integrated into standard control units. Thereby the I/O-Procedure is even attractive or medium solar systems beginning with a collector area o 0 m². I/O-Controllers rom RESOL will be available in 006. Keywords: Input/Output-Procedure, quality assurance, uncertainty, modelling 1. Introduction The demand or solar thermal collectors is increasing because o the actual trend o the uel prices. In order to assure the operator that the solar system is still working properly ater a couple o years a procedure or unction control is necessary, because ailures can t be recognised easily. In our research project we were developing Input/Output-Controllers that are assuring the quality o solar thermal systems by an in situ and automatic comparison o measured and expected collector yields on a daily basis. They help to remove the reluctance o investors by increasing the conidence in solar thermal energy. We developed a mathematical simulation model that can be integrated into standard control units. Prototypes o I/O-Controllers with an implemented algorithm were installed in 1 dierent solar systems. The simulation model was validated with measured data. The deviation between measured and expected outputs is less than 10 %. In a sensitivity analysis that takes the uncertainties o parameters and measurement into account we determined the uncertainty o the procedure. The uncertainty results to about 7 %.. The ISFH-Input/Output-Procedure.1 General speciications For the daily comparison o measured and expected collector yields, the I/O-Controller has to measure the heat output as well as the input quantities o the simulation model or the calculation o the expected output. The ollowing schematic (Fig. 1) shows the required sensors or the Input/Output-Procedure. Optional sensors may be installed or more inormation or in order to acilitate trouble-shooting in case o a ailure. Supplementary sensors may be necessary or some special solar systems (e. g. solar systems with several storages). This is not discussed here. For the measurement o the yield o the collector Q meas, the volume low rate V and the temperature dierence between inlet and outlet o the heat exchanger (ϑ HX,in -ϑ HX,out ) are required.

2 The expected yield Q exp, is simulated with measured data o irradiance G g, ambient air temperature ϑ a, typical solar load temperature ϑ TSL and the ϑ Tmax temperature at the buer relevant position or storage the high limit cutout ϑ Tmax. Further- ϑ tank discharge collector HX,in more the I/O- ϑ Controller has to V TSL ϑ know about 40 parameters o the so- ϑ a charge lar system (e. g. G HX,out g V collector eiciency Q Load meas, coeicients like zero loss coeicient I/Oand heat loss coeicients, tilt, collec- Q exp, Controller tor area). Fig. 1. Schematic diagram o metrological integration o an Input/ Output- Controller into a solar system with buer storage tank and direct discharging The ϑ TSL describes the temperature o the heat sink o the collector. In dierent solar systems evaluated in the project the heat sink has been a (buer) storage tank, a swimming pool or a return pipe o a district heating system. An advantage o using the ϑ TSL is that the same mathematical model can be taken or the collector o all kinds o systems (q. v. chapter.). The measured and expected daily outputs o the collector can be plotted in an Input/Output- Diagram (q. v. Fig. ) over the daily irradiation (input). Solar domestic hot water systems show a well-known linear relationship, as published in the IEA SHC Tasks VI (1980) and XIV (1996). But also solar systems or space heating that do not show such a linear population can be controlled with an Input/Output-Controller, because o the dynamic simulation o an expected output. Failures in the collector can be seen easily in an Input/Output-Diagram, because the measured values strongly deviate rom the expected values. Daily Heat Q [kwh/(m² d)] Measured Value Expected Value Failure Daily Total Irradiation H Day [kwh/(m² d)] Fig.. Input/ Output-Diagram o an attended solar system o a hospital in Solingen (19 m²) rom 003. The ailure occurred in the collector. The measured yields o the collector strongly deviate rom the expected yields (encircled in red).

3 The volume low rate o the load V Load (warm water consumption) and the storage temperature at the relevant position or the high limit cut-out ϑ Tmax are important inormation or the algorithm to distinguish a ailure in the discharge rom the eects o lacking heat demand, so that discharging ailures can be detected. A detected blockage o a discharge heat exchanger by build up o scale was already published in [3]. In case o low heat demand, e. g. in holidays or in summer periods or solar combi-systems, no signiicant dierence between measured and expected values results. This is important to avoid alse signals that conuse the operator, because this is a normal state o solar systems.. Mathematical model The developed mathematical model or simulating the yield o the collector needs to be able to be integrated into standard control units. For that reason the heat demand V Load is not a necessary input or the model dierent rom common simulation programs. Instead the input quantity or the model is the typical solar load temperature ϑ TSL describing the temperature o the heat sink o the collector. By using the ϑ TSL we achieved the ollowing advantages: Applicability or various solar system-types without adaptation o the algorithm Dierential equation is solvable analytically, accurate enough and can be integrated into standard control units Possibility or implementation into small inexpensive I/O-Controllers! The disadvantage o using the ϑ TSL is that a ailure in the discharging also decreases the expected yields a little bit. In order to get a suicient dierence o measured and expected output (>0 %) or an alarm signal, a high limit cut-out has to occur on a sunny day. This means that the detection o this kind o ailure is less quick. The simple mathematical model or simulating the working collector results rom the heat balance o the whole collector. Figure 3 gives a schematical drawing or a collector irradiation optical losses thermal losses with an external heat exchanger. Treatment o pipe heat losses inside and outside o the building occurs within the algorithm but is neglected here. The pump energy η 0, a 1, a, C C, K θ,e that leads to an increase in temperature o the luid can be neglected or big solar systems. It is energy ϑ C P Pump P el k P, heat losses o pipes not discussed urther. (k A) HX Fig. 3. Schematic diagram o the heat balance o a collector in operation An ordinary quadratic dierential equation describes the mean temperature o the collector : C dϑ dt = η0 Kθ, e Gg 1 ( a + a ( ϑ ϑ ) + k ) ( ϑ ϑ ) k ( ϑ ϑ ) a ϑ TSL P solar heat a HX TSL Eq. 1

4 ϑ is the mean temperature o the collector. G g is the total irradiance on the tilted surace. Parameters are the collector properties η 0, K θ,e, C C, a 1, a, the properties o the pipes k P and C P and the heat transer coeicient o the heat exchanger (k A) HX. C is the total heat capacity o the collector (=C C +C P ). ϑ a is the ambient air temperature and ϑ TSL is the typical solar load temperature. k HX is derived rom the heat transer property o the heat exchanger (k A) WT. It describes the heat transer rate relative to the temperature dierence (ϑ -ϑ TSL ). This conversion is done in the algorithm with equation (without derivation). The primary and secondary heat capacity low rates m& (Indices: = collector, BL = Buer charge ) are to be entered as parameters. c The heat exchanger eectiveness ε is also calculated in the algorithm. k HX = ε ( m& c ) ( m& BL ( m& c ) ε ( m& c ) ε ( m& ε BL ( m& > ( m& ( m& ( m& The Input/Output-ormula [] or calculating the daily expected yield Q ollows ater integrating equation 1 (without derivation). Q = 0 Kθ, e H insu + η0 Kθ, e Day th Cap BL BL Eq. η H Q Q Eq. 3 Eq. 3 describes the typical population in an Input/Output-Diagram. It implicitly depends on the typical solar load temperature. The insuicient irradiation H insu increases with ϑ TSL. This irradiation part is not utilisable because the temperature level o the collector is not yet high enough to load the storage tank. Thermal losses during operation increase with the mean temperature level o the collector which is depending on ϑ TSL. The dierent heat loss mechanisms o a thermal solar system are shown in an Input/Output- Diagram in Fig. 4 with measured data. Herein the capacity eects are not plotted. I Optical losses II Thermal losses while temperature level not high enough III Thermal losses during operation o collector Daily heat Q [kwh/(m² d)] absorbed irradiation absorbed utilisable irradiation collector output Fig. 4. Dierent heat loss mechanisms shown in 1 0 an Input/Output- Diagram or a H solar system in insu Daily total irradiation H Day [kwh/(m² d)] Munich (110 m²), having a low solar raction and accordingly a small insuicient irradiation higher ϑ TSL I II III

5 The mathematical model proved its accuracy and applicability in all 1 dierent solar systems. The mean deviation between measured and expected output is less than 10 %..3 Sensitivity analysis The uncertainty o the Input/Output-Procedure u( Q) depends on the uncertainties o parameters, measured values and simpliications o the simulation. Comparisons with TRNSYS results showed that the simpliications can be neglected, while the solar system is running properly. The uncertainties o the collector properties come rom dierent testing conditions. Their uncertainty values can be taken rom [1]. The uncertainties o the other relevant parameters were assumed conservatively. Tolerances o the sensors and systematic errors in measurement cause the uncertainties o the measured values. Only or ϑ TSL that is measured under the insulation o the storage instead o inside the storage tank a systematic error was considered. The joint inluence o the uncertainties o parameters and measurement on the uncertainty o the I/O-Procedure was analysed in a sensitivity analysis. Thereore the original values µ o the parameters and the measured data were modiied with their standard uncertainty s. The eect was calculated with data o one year o a typical solar system. The ollowing diagram shows the mean inluences on the uncertainty o the expected (simulated) value u(q exp ). 6 µ-1 s µ+1 s measured values parameters all G g ϑ TSL ϑ a η 0 a 1,a C C K θ,e k P (k A) HX s: ±,9% ±1,K ±0,35K ±,5% ±5% ±9% ±0,4% ±7,% ±5% ±5,% Uncertainty o expected value u(q exp ) in % Fig. 5. Mean uncertainty o the expected daily collector output u(q exp ) based on the uncertainties o measured values and important parameters. All the individual uncertainties have to be added as root sum o squares because they do not occur in the same direction. The mean uncertainty o the expected yield o the collector results to 5, %. It is strongly inluenced by the measurement o the irradiance with the photovoltaic sensor. By additional individual calibration on a solar tracker and consideration o the incidence angle this inluence was reduced by a actor o 3. Among the parameters the uncertainty o the zero loss coeicient η 0 has the biggest inluence. Its uncertainty as well as the uncertainties o the other collector properties a 1, a, C C and K θ,e are mainly determined by varying test conditions (e. g. diuse radiation) according to EN These uncertainties can not be corrected unless the test conditions are given in the test report or the properties have to be related to a ixed basis. The uncertainty o the measured yield o the collector u(q meas ) was also determined with the uncertainties o parameters (density and heat capacity o the luid) and measurement (volume low rate and temperature dierence). It is approx. 4 %. Taking both eects into account, the standard uncertainty o the Input/Output-Procedure u( Q) ollows to about 7 %. I the limit o tolerance between measured and simulated yield o e. g. 0 % is exceeded, which is the triple standard uncertainty o the procedure, a ault is existent with a probability o 99 %.

6 Conclusion Quality assurance o solar thermal systems is necessary because ailures cannot easily be recognised by an operator. The ISFH-Input/Output-Procedure is automatically and in situ controlling the measured yield o the collector by comparing it with a simulated value. The dynamic simulation algorithm to calculate the expected yield can be integrated into standard control units because the mathematical model is simple and analytically solvable. This enables low-cost Input/Output-Controllers. The mathematical model has been validated against measured data o 1 dierent solar systems. The average deviation is under 10 % which exceeded our expectations. The model is applicable or various solar systems without adaptation o the algorithm. The uncertainty o the I/O-Procedure concerning the uncertainties o parameters and measured data is about 7 %. I the limit o tolerance between measured and simulated yield o e. g. 0 % is exceeded a ault is existent with a probability o 99 %. RESOL will oer inexpensive I/O-Controllers in 006 or about 1000 incl. sensors. Acknowledgements The authors wish to thank the Federal Ministry or the Environment, Nature Conservation and Nuclear Saety (BMU) or unding the research project (contract no A). As well, we are thankul or the conidence and the engagement o the hardware-partners RESOL and INGA, the sotware-company DR. VALENTIN ENERGIESOFTWARE and the collector manuacturers SOLVIS, VIESSMANN, WAGNER and BUDERUS. Reerences [1] R. Sillmann, G. Rockendor: Mess- und verahrenstechnische Unsicherheiten bei Leistungsprüungen an Sonnenkollektoren. Proceedings o the 11 th symposium thermal solar energy, 001, Staelstein, Otti- Technologie-Kolleg, Regensburg, p [] F. Meyer: Funktions- und Ertragsüberwachung ür thermische Solaranlagen. BINE Inormationsdienst, Projektino 07/03, Herausgeber: Fachinormationszentrum Karlsruhe, ISSN , 003 [3] K. Vanoli, F. Pujiula, T. Conrad, A. Knoch: Anwendung der ISFH-IOC-Technologie: Erkennung und Beseitigung des Ausalls einer 76 m² Solaranlage. Proceedings o the 1 th symposium thermal solar energy, 00, Staelstein, Otti-Technologie-Kolleg, Regensburg

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