Review of long-term fault detection approaches in solar thermal systems

Abstract

Abstract This paper presents an overview, assessment and comparison of automated fault detection methods that check if solar heating systems are functioning correctly. Fault detection in solar thermal systems is important to minimize the time when the system is not functioning well, thereby ensuring an optimal energy (and economic) yield. During the past decades many systems have been monitored, mainly for scientific or demonstration projects by logging measurement data which was subsequently analysed by an expert. Automation of fault detection is necessary to reduce costs and minimize experts’ time needed for analysis of a system. An overview of existing fault detection approaches is given; these are evaluated and compared with a multi-criteria analysis. The only commercially available automated method, the Input–Output Controller, detects faults causing more than 20% energy loss in the solar loop. The function control approach is cheap without a heat meter, and only relies on few sensors to check how several components in the solar loop are functioning with algorithms. The approach developed at Kassel University checks how well a solar plant is functioning both with plausibility checks and with energy balances based on simulations. This method includes a larger part of the solar heating system and therefore requires more measurement equipment. Further research and application of several fault detection methods should improve the effectiveness and costs of these methods.