Final report : testing and evaluation for solar hot water reliability.

Abstract

Solar hot water (SHW) systems are being installed by the thousands. Tax credits and utility rebate programs are spurring this burgeoning market. However, the reliability of these systems is virtually unknown. Recent work by Sandia National Laboratories (SNL) has shown that few data exist to quantify the mean time to failure of these systems. However, there is keen interest in developing new techniques to measure SHW reliability, particularly among utilities that use ratepayer money to pay the rebates. This document reports on an effort to develop and test new, simplified techniques to directly measure the state of health of fielded SHW systems. One approach was developed by the National Renewable Energy Laboratory (NREL) and is based on the idea that the performance of the solar storage tank can reliably indicate the operational status of the SHW systems. Another approach, developed by the University of New Mexico (UNM), uses adaptive resonance theory, a type of neural network, to detect and predict failures. This method uses the same sensors that are normally used to control the SHW system. The NREL method uses two additional temperature sensors on the solar tank. The theories, development, application, and testing of both methods are described in the report. Testing was performed on the SHW Reliability Testbed at UNM, a highly instrumented SHW system developed jointly by SNL and UNM. The two methods were tested against a number of simulated failures. The results show that both methods show promise for inclusion in conventional SHW controllers, giving them advanced capability in detecting and predicting component failures.