Proactive Fault Handling for System Availability Enhancement

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system.

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Self-healing trans-cloud applications

Computing ◽

10.1007/s00607-021-00977-z ◽

2021 ◽

Author(s):

Antonio Brogi ◽

Jose Carrasco ◽

Francisco Durán ◽

Ernesto Pimentel ◽

Jacopo Soldani

Keyword(s):

Open Source ◽

Cloud Services ◽

Self Healing ◽

Controlled Experiments ◽

Fault Handling ◽

Extensive Evaluation ◽

Cloud Providers ◽

Heterogeneous Cloud ◽

Cloud Applications ◽

Unstable States

AbstractTrans-cloud applications consist of multiple interacting components deployed across different cloud providers and at different service layers (IaaS and PaaS). In such complex deployment scenarios, fault handling and recovery need to deal with heterogeneous cloud offerings and to take into account inter-component dependencies. We propose a methodology for self-healing trans-cloud applications from failures occurring in application components or in the cloud services hosting them, both during deployment and while they are being operated. The proposed methodology enables reducing the time application components rely on faulted services, hence residing in “unstable” states where they can suddenly fail in cascade or exhibit erroneous behaviour. We also present an open-source prototype illustrating the feasibility of our proposal, which we have exploited to carry out an extensive evaluation based on controlled experiments and monkey testing.

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Fleet Resilience: Evaluating Maintenance Strategies in Critical Equipment

Applied Sciences ◽

10.3390/app11010038 ◽

2020 ◽

Vol 11 (1) ◽

pp. 38

Author(s):

Orlando Durán ◽

Javier Aguilar ◽

Andrea Capaldo ◽

Adolfo Arata

Keyword(s):

Application Study ◽

System Availability ◽

Maintenance Strategies ◽

Resilience Index ◽

Reliability Block Diagrams ◽

Maintenance Policies ◽

Definition Of ◽

The Impact ◽

Important System ◽

Intrinsic Characteristic

Resilience is an intrinsic characteristic of systems. Through it, the capacity of a system to react to the existence of disruptive events is expressed. A series of metrics to represent systems’ resilience have been proposed, however, only one indicator relates the availability of the system to this characteristic. With such a metric, it is possible to relate the topological aspects of a system and the resources available in order to be able to promptly respond to the loss of performance as a result of unexpected events. This work proposes the adaptation and application of such a resilience index to assess the influence of different maintenance strategies and topologies in fleets’ resilience. In addition, an application study considering an actual mining fleet is provided. A set of critical assets was identified and represented using reliability block diagrams. Monte Carlo simulation experiments were conducted and the system availability data were extracted. Resilience indexes were obtained in order to carry out the definition of the best maintenance policies in critical equipment and the assessment of the impact of modifying system redundancies. The main results of this work lead to the overall conclusion that redundancy is an important system attribute in order to improve resiliency along time.

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A Fault Handling Process for Faults in District Heating Customer Installations

Energies ◽

10.3390/en14113169 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3169

Author(s):

Sara Månsson ◽

Marcus Thern ◽

Per-Olof Johansson Kallioniemi ◽

Kerstin Sernhed

Keyword(s):

Data Analysis ◽

Fault Detection ◽

Negative Impact ◽

District Heating ◽

Customer Data ◽

Heating Systems ◽

Fault Handling ◽

District Heating Systems ◽

High Return ◽

Using Data

Faults in district heating (DH) customer installations cause high return temperatures, which have a negative impact on both current and future district heating systems. Thus, there is a need to detect and correct these faults soon after they occur to minimize their impact on the system. This paper, therefore, suggests a fault handling process for the detection and elimination of faults in DH customer installations. The fault handling process is based on customer data analysis since many faults manifest in customer data. The fault handling process was based on an analysis of the results from the previous fault handling studies, as well as conducting a workshop with experts from the DH industry. During the workshop, different organizational and technical challenges related to fault handling were discussed. The results include a presentation of how the utilities are currently working with fault handling. The results also present an analysis of different organizational aspects that would have to be improved to succeed in fault handling. The paper also includes a suggestion for how a fault handling process based on fault detection using data analysis may be designed. This process may be implemented by utilities in both current and future DH systems that interested in working more actively with faults in their customer installations.

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