• Energy Research

The project ADVENTURE (ADVancEd iNtegraTed evalUation of Railway systEms) aims to provide novel solutions for the evaluation of RAMS requirements as well as to present trade-offs between dependability attributes and energy consumption in complex railway systems, leveraging both qualitative and quantitative evaluation methods. To this end, case studies concerning distributed interlocking systems, standard interfaces, and railroad switch heaters are considered, comprising different challenging scenarios, notably representative of the complexity of railway systems. In this paper, we illustrate the objectives of the project and the activities planned to address them, devising future steps to integrate the envisaged contributions within a unified framework.

Rail road switches enable trains to be guided from one track to another, and rail road switches heaters are used to avoid the formation of snow and ice during the cold season in order to guarantee their correct functioning. Managing the energy consumption of these devices is important in order to reduce the costs and minimise the environmental impact. While doing so, it is important to guarantee the reliability of the system. In this work we analyse reliability and energy consumption indicators for a system of (remotely controlled) rail road switch heaters by devel­oping and solving stochastic models based on the Stochastic Activity Networks (SAN) formalism. An on-off policy is considered for heating the switches, with parametric thresholds representing the temperatures activating/deactivating the heating. Initial investigations are carried on to understand the impact of different thresholds on the indicators under analysis (probability of failure and energy consumption).

Nowadays, economy, security and quality of life heavily depend on the resiliency of a number of critical infrastructures, including the Electric Power System (EPS), through which vital services are provided. In existing EPS two cooperating infrastructures are involved: the Electric Infrastructure (EI) for the electricity generation and transportation to final users, and its Information-Technology based Control System (ITCS) devoted to controlling and regulating the EI physical parameters and triggering reconfigurations in emergency situations. This paper proposes a modeling framework to capture EI and ITCS aspects, focusing on their interdependencies that contributed to the occurrence of several cascading failures in the past 40 years. A quite detailed analysis of the EI and ITCS structure and behavior is Performed; in particular the ITCS and EI behaviors are described by discrete and hybrid-state processes, respectively To substantiate the approach, the implementation of a few basic modeling mechanisms inside an existing multiformalism/multi-solution toot is also discussed.

Electric power systems are prominent representatives of the critical infrastructure. Existing electric power systems are composed by two cooperating infrastructures: the electric infrastructure, which is responsible for electricity generation and electricity transmission to customers; and information technology based control systems that monitor and control the physical parameters of the electric infrastructure and trigger appropriate reconfigurations in emergency situations. The interactions between these two cooperating infrastructures must be carefully analyzed to understand and characterize their (inter)dependencies, i.e., how the state of one infrastructure influences or is correlated to the state of the other. This paper proposes a model-based framework for quantitatively analyzing the propagation and impact of malfunctions in electric power systems. The framework is implemented using the stochastic activity network (SAN) formalism and is applied to concrete case studies that support the understanding and assessment of the impact of interdependencies. The results assist in developing countermeasures that can help reduce electric power system vulnerabilities.

Awareness and efforts to moderate energy consumption, desirable from both economical and environmental perspectives, are nowadays increasingly pursued. However, when critical sectors are addressed, energy saving should be cautiously tackled, so to not impair stringent dependability properties such contexts typically require. This is the case of the railway transportation system, which is the critical infrastructure this paper focuses on. For this system category, the attitude has been typically to neglect efficient usage of energy sources, motivated by avoiding to put dependability in danger. The new directives, both at national and international level, are going to change this way of thinking. Our study intends to be a useful support to careful energy consumption. In particular, a refined stochastic modeling framework is offered, tailored to the railroad switch heating system, through which analyses can be performed to understand the sophisticated dynamics between the system (both the cyber and physical components) and the surrounding weather conditions.

Analysis of interdependencies in Electric Power Systems (EPS) has been recognized as a crucial and challenging issue to improve their trustworthiness. The recent liberalization process in energy markets has promoted the entry of a variety of operators in the electricity industry. The resulting new organization contributed to increase in complexity, heterogeneity and interconnection. This paper proposes a framework for analyzing EPS organized as a set of interconnected regions, both from the point of view of the electric power grid and of the cyber control infrastructure. The emphasis is on interdependencies and in assessing their impact on indicators representative of the QoS perceived by users. Taking a reference power grid as test case, the effects of failures on selected measures are shown, both in case the grid is partitioned in a number of regions and in case of a single region, to illustrate the behavior of different grid and control configurations.

The evolution of electrical grids, both in terms of enhanced ICT functionalities to improve efficiency, reliability and economics, as well as the increasing penetration of renewable redistributed energy resources, results in a more sophisticated electrical infrastructure which poses new challenges from several perspectives, including resilience and quality of service analysis. In addition, the presence of interdependencies, which more and more characterize critical infrastructures (including the power sector), exacerbates the need for advanced analysis approaches, to be possibly employed since the early phases of the system design, to identify vulnerabilities and appropriate countermeasures. In this paper, we outline an approach to model and analyze smart grids and discuss the major challenges to be addressed in stochastic model-based analysis to account for the peculiarities of the involved system elements. Representation of dynamic and flexible behavior of generators and loads, as well as representation of the complex ICT control functions required to preserve and/or re-establish electrical equilibrium in presence of changes need to be faced to assess suitable indicators of the resilience and quality of service of the smart grid. © 2014 IEEE.