The reliability and availability evaluation of repairable district heating networks under changeable external conditions

The conventional reliability evaluation of district heating networks is generally based on restrictive assumptions aiming to simplify the reliability assessment process, e.g., the hypothesis of the unrepairable system and constant outside temperature. Due to such simplifications, the reliability indices retain constant and unchangeable during the heating season, which is infeasible to reveal the changeability of reliability of heating networks. Concerning such deficiencies, this paper presents a novel study to modify these assumptions, and further analyze the influence of changeable outside temperature on the reliability of heating networks based on the state-space method. In this study, in terms of the dynamic state-determination criterion, structural and functional reliability indices are proposed to evaluate dynamic reliability of heating networks. In reality, the realistic state-determination is the critical foundation of reliability evaluation, which directly determines the accuracy of the reliability assessment. Hence, the dynamic state-determination criterion is introduced in this study, concerning both the external and internal conditions of consumers. Combined with the state probabilities, functional reliability indices consider two functional parameters, i.e., the heat power and the indoor temperature, to reflect the changeability of heat-supply ability and the resultant effects of failures on internal status of consumers under changeable external conditions. As a pilot study, the proposed reliability evaluation indices are applied to a real looped heating network in Harbin, China. The results indicate that the outside temperature significantly affects the reliability of heating networks. It is observed that the reliability and availability demonstrate a ladder growth with the increasing of outside temperature. According to the changeability of reliability, the weaknesses and the key components of the system can be figured out. Therefore, advanced preventive measures can be taken to reduce failures of components and improve the reliability of heating networks.

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