Accuracy of key performance indicators in solar-assisted heating systems due to measurement uncertainties

In this paper, the influence of measurement uncertainties on the key performance indicators fsav and FSC in solar-assisted heating systems is investigated. The impact of temperature, volumetric flow rate, and irradiance sensors with different measurement accuracies is analysed with a combination of Gaussian error propagation and Monte Carlo Analysis. To identify the sensor equipment with best cost-benefit-ratio (BCBR), different sensor combinations are investigated. If fsav and FSC are to be measured, additional sensors must be installed. The resulting costs range from 250 euro for an inexpensive equipment to 330 euro for recommended BCBR equipment and up to 780euro for the maximum accuracy equipment. For smaller economically dimensioned systems the use of inexpensive sensors results in large uncertainties, e.g. fsav= (15.2 & PLUSMN;13.7)%. The uncertainties for larger systems are significantly lower, e.g. fsav= (56.7 & PLUSMN; 6.3)%. This is true as well if better sensors are used. Regardless of the system's size, with the BCBR sensor equipment the resulting expanded uncertainties can be reduced by 60 % (relative) compared to the results with the inexpensive sensor equipment. With maximum accuracy sensor equipment the resulting expanded uncertainties can even be reduced by 77 % (relative). The results show the importance of a carefully selected sensor equipment and the influence of the system's size. Inexpensive sensors can lead to large uncertainty ranges for the important key performance indicators fsav and FSC. Thus, these key figures effectively cannot be used for assessing the performance of a solar-assisted heating system.