Circuit breaker prognostics using SF6 data

Control decisions within future energy networks may take account of the health and condition of network assets, pushing condition monitoring within the smart grid remit. In order to support maintenance decisions, this paper proposes a circuit breaker prognostic system, which ranks circuit breakers in order of maintenance priority. By monitoring the SF6 density within a breaker, the system not only predicts the number of days to a critical level, but also incorporates uncertainty by giving upper and lower bounds on the prediction. This prognostic model, which performs linear regression, will be described in this paper, along with case studies demonstrating ranking breakers based on maintenance priority and prognosis of a leaking breaker. Providing an asset manager with this type of information could allow improved management of his/her assets, potentially deferring maintenance to a time when an outage is already scheduled

Internal combustion engine sensor network analysis using graph modeling

In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data. In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs. The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

An automated wrapper-based approach to the design of dependable software

The design of dependable software systems invariably comprises two main activities: (i) the design of dependability mechanisms, and (ii) the location of dependability mechanisms. It has been shown that these activities are intrinsically difficult. In this paper we propose an automated wrapper-based methodology to circumvent the problems associated with the design and location of dependability mechanisms. To achieve this we replicate important variables so that they can be used as part of standard, efficient dependability mechanisms. These well-understood mechanisms are then deployed in all relevant locations. To validate the proposed methodology we apply it to three complex software systems, evaluating the dependability enhancement and execution overhead in each case. The results generated demonstrate that the system failure rate of a wrapped software system can be several orders of magnitude lower than that of an unwrapped equivalent

QoS within Business Grid Quality of Service (BGQoS)

Differences in domain QoS requirements have been an obstacle to utilising Grid Computing for main stream applications. While the resource could potentially provide potentially vital services as well as providing significant computing and storage capabilities, the lack of high level QoS specification capabilities has proven to be a hindrance. Business Grid Quality of Service (BGQoS) is a QoS model for business-oriented applications on Grid computing systems. BGQoS defines QoS at a high level facilitating an easier request model for the Grid Resource Consumer (GRC) and eliminates confusion for the Grid Resource Provider in supplying the appropriate resources to meet the GRC requirements. It offers high level QoS specification within multi-domain environments in a flexible manner. Employing component separation and dynamic QoS calculation, it provides the necessary tools and execution environment for a scalable set of requirements tailoring to specific domain demands and requirements. Moreover, through reallocation, the model provides the insurance that all QoS requirements are met throughout the execution period, including migrating tasks to different resources if necessary. This process is not random and adheres to a set of conditions which ensures that task execution and resource allocation happen when and in accordance with execution requirements. This paper focuses on BGQoS’ flexibility and QoS capability. More specifically, the concentration is on core operations within BGQoS and the methods used in order to deliver a sustained level of QoS which meets the GRC’s requirements while being versatile and flexible such that it can be tailored to specific domains. This paper also presents an experimental evaluation of BGQoS. The evaluation investigates the behaviour and performance of the separate operations and components within BGQoS, and moreover, it presents an investigation and comparison between the different operations and their effect on the full model