From Interaction Overview Diagrams to Temporal Logic

In this paper, we use UML Interaction Overview Diagrams as the basis for a user-friendly, intuitive, modeling notation that is well-suited for the design of complex, heterogeneous, embedded systems developed by domain experts with little background on modeling software-based systems. To allow designers to precisely analyze models written with this notation, we provide (part of) it with a formal semantics based on temporal logic, upon which a fully automated, tool supported, verification technique is built. The modeling and verification technique is presented and discussed through the aid of an example system

An Efficient Method to Take into Account Forecast Uncertainties in Large Scale Probabilistic Power Flow

The simulation of uncertainties due to renewable and load forecasts is becoming more and more important in security assessment analyses performed on large scale networks. This paper presents an efficient method to account for forecast uncertainties in probabilistic power flow (PPF) applications, based on the combination of PCA (Principal Component Analysis) and PEM (Point Estimate Method), in the context of operational planning studies applied to large scale AC grids. The benchmark against the conventional PEM method applied to large power system models shows that the proposed method assures high speed up ratios, preserving a good accuracy of the marginal distributions of the outputs

Probabilistic assessment of Net Transfer Capacity considering forecast uncertainties

In transmission system planning, researchers propose methods to assess the effect of uncertainties of power system operating condition due to forecasting errors of intermittent generation and loads. In particular probabilistic power flow methods are used to calculate the probability distributions of the voltages and the branch currents, starting from the distributions of power injections/absorptions. These uncertainties play a key role in the operational planning of power systems, as certain configurations of load and intermittent generation can cause security problems. This paper aims to propose a probabilistic methodology to assess Net Transfer Capacity (NTC) among network areas, which quantifies forecast error uncertainties by applying the Point Estimate Method (PEM) combined with Third Order Polynomial Normal (TPN) Transformation. This approach is compared with a conventional NTC assessment technique and has been tested on an IEEE test system

A Risk-Based Methodology and Tool Combining Threat Analysis and Power System Security Assessment

A thorough investigation of power system security requires the analysis of the vulnerabilities to natural and man-related threats which potentially trigger multiple contingencies. In particular, extreme weather events are becoming more and more frequent due to climate changes and often cause large load disruptions on the system, thus the support for security enhancement gets tricky. Exploiting data coming from forecasting systems in a security assessment environment can help assess the risk of operating power systems subject to the disturbances provoked by the weather event itself. In this context, the paper proposes a security assessment methodology, based on an updated definition of risk suitable for power system risk evaluations. Big data analytics can be useful to get an accurate model for weather-related threats. The relevant software (SW) platform integrates the security assessment methodology with prediction systems which provide short term forecasts of the threats affecting the system. The application results on a real wet snow threat scenario in the Italian High Voltage grid demonstrate the effectiveness of the proposed approach with respect to conventional security approaches, by complementing the conventional "N - 1" security criterion and exploiting big data to link the security assessment phase to the analysis of incumbent threat

A timeband framework for modelling real-time systems

Complex real-time systems must integrate physical processes with digital control, human operation and organisational structures. New scientific foundations are required for specifying, designing and implementing these systems. One key challenge is to cope with the wide range of time scales and dynamics inherent in such systems. To exploit the unique properties of time, with the aim of producing more dependable computer-based systems, it is desirable to explicitly identify distinct time bands in which the system is situated. Such a framework enables the temporal properties and associated dynamic behaviour of existing systems to be described and the requirements for new or modified systems to be specified. A system model based on a finite set of distinct time bands is motivated and developed in this paper

Integrating discrete- and continuous-time metric temporal logics through sampling

Abstract. Real-time systems usually encompass parts that are best described by a continuous-time model, such as physical processes under control, together with other components that are more naturally formalized by a discrete-time model, such as digital computing modules. Describing such systems in a unified framework based on metric temporal logic requires to integrate formulas which are interpreted over discrete and continuous time. In this paper, we tackle this problem with reference to the metric temporal logic TRIO, that admits both a discrete-time and a continuous-time semantics. We identify sufficient conditions under which TRIO formulas have a consistent truth value when moving from continuous-time to discrete-time interpretations, or vice versa. These conditions basically involve the restriction to a proper subset of the TRIO language and a requirement on the finite variability over time of the basic items in the specification formulas. We demonstrate the approach with an example of specification and verification

Online security assessment with load and renewable generation uncertainty: The iTesla project approach

The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (HPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator

Benchmarking and Validation of Cascading Failure Analysis Tools

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