Cascading failure in electric power systems is a complicated problem for which a variety of models, software tools, and analytical tools have been proposed but are difficult to verify. Benchmarking and validation are necessary to understand how closely a particular modeling method corresponds to reality, what engineering conclusions may be drawn from a particular tool, and what improvements need to be made to the tool in order to reach valid conclusions. The community needs to develop the test cases tailored to cascading that are central to practical benchmarking and validation. In this paper, the IEEE PES working group on cascading failure reviews and synthesizes how benchmarking and validation can be done for cascading failure analysis, summarizes and reviews the cascading test cases that are available to the international community, and makes recommendations for improving the state of the art.

In-depth security analyses of power systems (PSs) require to consider the vulnerabilities to natural and human-related threats, which may cause multiple dependent contingencies. On the other hand, such events often lead to high impact on the system, so that decision-making aimed to enhance security may become difficult. Introducing the uncertainty, the risk associated to each contingency can be evaluated, thus allowing to perform effective contingency ranking. This paper describes an in-depth security assessment methodology, based on an “extended” definition of risk (including threats, vulnerability, contingency, and impact) aimed to perform the risk assessment of the integrated power and Information and Communication Technology (ICT) systems. The results of the application to test cases and realistic PSs show the added value of the proposed approach with respect to conventional security analyses in dealing with uncertainty of threats, vulnerabilities, and system response.

We address the problem of increasing the impact of formal methods in the practice of industrial computer applications. We summarize the reasons why formal methods so far did not gain widespead use within the industrial environment despite several promising experiences. We suggest an evolutionary rather than revolutionary attitude in the introduction of formal methods in the practice of industrial applications, and we report on our long-standing experience which involves an academic institution. Politecnico di Milano, two main industrial partners, ENEL and CISE, and occasionally a few other industries. Our approach aims at augmenting an existing and fairly deeply rooted informal industrial methodology with our original formalism, the logic specification language TRIO. On the basis of the experiences we gained we argue that our incremental attitude toward the introduction of formal methods within the industry could be effective largely independently from the chosen formalism.

Various methodologies exist for assessing the risk of cascading outage in power systems, differing in the cascading mechanisms considered and in the way they are modeled. These methodologies can be classified in three groups: static computation (QSS methodologies), dynamic computation (dynamic methodologies), or a combination of both (hybrid methodologies). The objective of this paper is to benchmark the performance of several widely used QSS cascading outage methodologies. For that purpose, they are applied on a unique system, the RTS-96, and the results are compared. Several metrics and indicators are used for that comparison: expected demand loss, distribution of demand loss, distribution of lines outaged and critical lines. Results show common trends but also discrepancies between methodologies. It implies that there is not yet a standardized way to analyze the risk of cascading outage in power systems, and that the specific tool used by a power system engineer can impact the recommendations.

Assessment of dynamic stability in a modern power system (PS) is becoming a stringent requirement both in operational planning and in on-line operation, due to the increasingly complex dynamics of a PS. Further, growing uncertainties in forecast state and in the response to disturbances suggests the adoption of risk-based approaches in Dynamic Security Assessment (DSA). The present paper describes a probabilistic risk-based DSA, which provides instability risk indicators by combining an innovative probabilistic hazard/vulnerability analysis with the assessment of contingency impacts via time domain simulation. The tool implementing the method can be applied to both current and forecast PS states, the latter characterized in terms of renewable and load forecast uncertainties, providing valuable results for operation and operational planning contexts. Some results from a real PS model are discussed.