Modern large-scale electrical power systems face serious stability threats in the form of low-frequency oscillations. Based on the recently proposed Lyapunov modal analysis framework, this study proposes a method for estimating the location and structure of inter-area oscillations as well as their interactions on the graph of an electrical power system. This method combines the known approaches of modal analysis and spectral decomposition of Lyapunov functions. In contrast to conventional modal analysis, modal indicators that consider the energy of voltage disturbances accumulated over time are proposed rather than the instantaneous dynamics of an individual perturbation. These indicators help analyze not only the location and structure of individual inter-area oscillations but also the geometry and structure of their pair-wise interactions in terms of the mutual action of modes, which is produced in the nodes over time. Motivational examples that illustrate the benefits of the proposed energy-based indicators are discussed. In test experiments using the New England IEEE 68 bus system, the proposed method is compared with the network modeshapes method to assess the locations of the nodes and ties that are critical for the selected inter-area oscillations. In a scenario experiment, the locations of the most sensitive nodes at the resonant modal interaction are examined. The proposed method can be used to analyze the resonance phenomena that arise in modern EPSs, especially in connection with the growth of renewable energy sources and the active use of thyristor converters. Novel approach can improve various control methods used for damping inter-area oscillations, optimal placement of sensors and stabilizers, and the analysis of voltage stability.

This paper presents an analysis of a temporal network that describes the social connections of a large-scale (∼30,000) sample of online social network users, inhabitants of a fixed city. We tested how the main network formation determinants—transitivity, preferential attachment, and social selection—contribute to network evolution. We obtained that tie appearing and tie removing events are governed by different combinations of mechanisms: whereas the structure of the network is responsible for the formation of new ties, nodal nonstructural characteristics “decide” whether a tie will continue to exist. Next, our findings show that only one network formation mechanism, gender selectivity, has a significant impact on both tie appearing and tie removing processes. What is interesting, the effect of gender selectivity is most notable for low-degree vertices. Besides this, our analysis revealed that opinion selectivity appears to be a noticeable (but not very important) factor only in the case of tie removing, whereas its contribution to tie appearing is elusive. Our findings suggest that nodes’ activity is a crucial factor of network evolution—the majority of tie removing events can be explained by the age-based activity mechanism. Finally, we report that transitivity and preferential attachment do govern network evolution. However, there are two important details: (i) their zone of influence is restricted primarily by tie appearing and (ii) the preferential attachment mechanism is replaced by the anti-preferential attachment rule if the number of common peers is greater than zero.

Witnessing a present-day radical shift from carbonized power towards renewables and smart energy systems, one should recognize nuclear power to be an equal partner, not opponent, to the sustainable types of energy. However, in contrast to systems based on renewable resources, nuclear energy production is highly risky, and NPP industrial control systems (ICS) impose the growing demands on safety and security. In order to meet pressing security challenges and perform an effective risk management, one of the fundamental steps to be taken is to conduct a comprehensive risk assessment, which in the context of today's transition from conventional control to digital, aka digitalization, should more accurately refer to cybersecurity. To carry out a cybersecurity risk assessment, a standard assets-based CIA risk assessment approach operating with confidentiality, integrity, and availability attributes is commonly utilized. Nevertheless, for NPP ICS, the approach happens to be slightly different because, firstly, industrial control is normally established with the primary aim of performing functions, e.g., control and monitoring ones, but not dealing with and managing assets, and, secondly, the availability property of control takes the major priority over other CIA attributes. The article investigates the cybersecurity risk assessment in the NPP ICS perspective. Clarifying the priority of control systems performance, it presents an approach adapted to NPP ICS and a modified equation for the first iteration of the potential cybersecurity risk calculation where the assets are replaced by functions. For the assignment of values for the availability property of NPP ICS functions, a metric based on delay is recommended. The ICS availability reference model, in particular, the system domain and so the dependency between system components is utilized for the accurate metric calculation.

The design of systems important to the safety of nuclear power plants (NPPs) is based on compliance with regulatory documents’ requirements and ensuring the object’s reliable operation throughout its entire life cycle. One of the aspects of increased requirements for the reliable and safe operation of NPP process control systems is perfecting human-operator information decision support systems. In the paper, an approach is considered in which the operator support information system kernel is a flexible modeling program complex, which, depending on the tasks being solved, can be used as a digital twin or a digital shadow. The digital twin furnishes the past state of the product, the current state, and probable future states, which is especially significant for its use. The paper also discusses methods for assessing the proximity of a physical object and its digital twin based on a consistent and normalized measure of dependence of random vectors.

Calculation of technical and economic indicators (TEI) is part of the information tasks of the upper-level control system of the NPP instrumentation and control system (I&C system). The TEI characterize the efficiency, reliability, and durability of the power unit equipment during its operation. Based on the automation of the TEI determination, objective information can be obtained about the efficiency of technological processes, the actual state of power equipment, as well as the risk potential of the ongoing processes.