Assembly and comparison of available solar hot water system reliability databases and information.

Solar hot water (SHW) systems have been installed commercially for over 30 years, yet few quantitative details are known about their reliability. This report describes a comprehensive analysis of all of the known major previous research and data regarding the reliability of SHW systems and components. Some important conclusions emerged. First, based on a detailed inspection of ten-year-old systems in Florida, about half of active systems can be expected to fail within a ten-year period. Second, valves were identified as the probable cause of a majority of active SHW failures. Third, passive integral and thermosiphon SHW systems have much lower failure rates than active ones, probably due to their simple design that employs few mechanical parts. Fourth, it is probable that the existing data about reliability do not reveal the full extent of fielded system failures because most of the data were based on trouble calls. Often an SHW system owner is not aware of a failure because the backup system silently continues to produce hot water. Thus, a repair event may not be generated in a timely manner, if at all. This final report for the project provides all of the pertinent details about this study, including the source of the data, the techniques to assure their quality before analysis, the organization of the data into perhaps the most comprehensive reliability database in existence, a detailed statistical analysis, and a list of recommendations for additional critical work. Important recommendations include the inclusion of an alarm on SHW systems to identify a failed system, the need for a scientifically designed study to collect high-quality reliability data that will lead to design improvements and lower costs, and accelerated testing of components that are identified as highly problematic

Report on the analysis of field data relating to the reliability of solar hot water systems.

Utilities are overseeing the installations of thousand of solar hot water (SHW) systems. Utility planners have begun to ask for quantitative measures of the expected lifetimes of these systems so that they can properly forecast their loads. This report, which augments a 2009 reliability analysis effort by Sandia National Laboratories (SNL), addresses this need. Additional reliability data have been collected, added to the existing database, and analyzed. The results are presented. Additionally, formal reliability theory is described, including the bathtub curve, which is the most common model to characterize the lifetime reliability character of systems, and for predicting failures in the field. Reliability theory is used to assess the SNL reliability database. This assessment shows that the database is heavily weighted with data that describe the reliability of SHW systems early in their lives, during the warranty period. But it contains few measured data to describe the ends of SHW systems lives. End-of-life data are the most critical ones to define sufficiently the reliability of SHW systems in order to answer the questions that the utilities pose. Several ideas are presented for collecting the required data, including photometric analysis of aerial photographs of installed collectors, statistical and neural network analysis of energy bills from solar homes, and the development of simple algorithms to allow conventional SHW controllers to announce system failures and record the details of the event, similar to how aircraft black box recorders perform. Some information is also presented about public expectations for the longevity of a SHW system, information that is useful in developing reliability goals

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

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