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High voltage direct current (HVDC) transmission lines are being constructed throughout the world, aided by advancements in power electronics and the potential value to transfer power between distant areas and off-shore locations. Multiple HVDC lines within and across large AC interconnections could bring about economic benefits such as interregional capacity exchange and transfer of low-cost, distant electric energy directly to load centers. In addition, network configuration of HVDC lines could result in additional benefits that have not been deeply studied. This paper describes the modeling process for continentallevel power system interconnections with the addition of multiple HVDC lines configured as a macrogrid. The models used for study are based on industry-accepted power-flow and dynamic system models for the North American Eastern and Western Interconnections. The model provides insight on feasibility and initial steady-state and stability tests of the HVDC macrogrid and its interactions with the existing electricity infrastructure, opening the door to analysis of the technical value of such a macrogrid.

Traditional power systems have been gradually shifting to power-electronic-based ones, with more power electronic devices (including converters) incorporated recently. Faced with much more complicated dynamics, it is a great challenge to uncover its physical mechanisms for system stability and/or instability (oscillation). In this paper, we first establish a nonlinear model of a multi-converter power system within the DC-link voltage timescale, from the first principle. Then, we obtain a linearized model with the associated characteristic matrix, whose eigenvalues determine the system stability, and finally get independent subsystems by using symmetry approximation conditions under the assumptions that all converters’ parameters and their susceptance to the infinite bus (Bg) are identical. Based on these mathematical analyses, we find that the whole system can be decomposed into several equivalent single-converter systems and its small-signal stability is solely determined by a simple converter system connected to an infinite bus under the same susceptance Bg. These results of large-scale multi-converter analysis help to understand the power-electronic-based power system dynamics, such as renewable energy integration. As well, they are expected to stimulate broad interests among researchers in the fields of network dynamics theory and applications.

The generation of the mix-based expansion of modern power grids has urged the utilization of digital infrastructures. The introduction of Substation Automation Systems (SAS), advanced networks and communication technologies have drastically increased the complexity of the power system, which could prone the entire power network to hackers. The exploitation of the cyber security vulnerabilities by an attacker may result in devastating consequences and can leave millions of people in severe power outage. To resolve this issue, this paper presents a network model developed in OPNET that has been subjected to various Denial of Service (DoS) attacks to demonstrate cyber security aspect of an international electrotechnical commission (IEC) 61850 based digital substations. The attack scenarios have exhibited significant increases in the system delay and the prevention of messages, i.e., Generic Object-Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV), from being transmitted within an acceptable time frame. In addition to that, it may cause malfunction of the devices such as unresponsiveness of Intelligent Electronic Devices (IEDs), which could eventually lead to catastrophic scenarios, especially under different fault conditions. The simulation results of this work focus on the DoS attack made on SAS. A detailed set of rigorous case studies have been conducted to demonstrate the effects of these attacks.

The increasing deployment of renewable energy sources (RESs) reduces the inertia levels of modern power systems, raising frequency stability issues. Therefore, it becomes crucial, for power-system operators, to monitor system inertia, in order to activate proper preventive remedial actions in a timely way, ensuring, this way, the reliable and secure operation of the power system. This paper presents a brief review of available techniques for inertia estimation of synchronous devices. Additionally, a comparative assessment of conventional measurement-based inertia-estimation techniques is performed. In particular, five conventional inertia-estimation techniques are considered and examined. The distinct features of each method are presented and discussed. The effect of several parameters on the accuracy of the examined methods is evaluated via Monte Carlo analysis. The performance of the examined methods is evaluated using dynamic responses, obtained via RMS simulations, conducted on the IEEE 9 bus test system. Based on the conducted analysis, recommendations to enhance the accuracy of the examined techniques are proposed.

As modern power systems grow increasingly complex, there is a pressing need for stability analysis methods capable of handling nonlinear dynamics while providing physically meaningful and reliable stability indices. Port-Hamiltonian (PH) frameworks have emerged as strong candidates in this regard, offering inherently stable formulations, energy-consistent representations, and modular plug-and-play scalability. However, the practical deployment of PH-based stability analysis remains hindered by the absence of reliable, high-fidelity parameter identification methods that rely on sensor measurements to capture system dynamics while remaining compatible with PH model structures. This paper addresses that gap by proposing a comprehensive three-stage data-driven identification framework for PH modeling of synchronous generators—the central dynamic component of any power system. While the IEEE Standard 115 provides established procedures for transient parameter identification, it exhibits fundamental limitations when applied to PH modeling, including single-scenario identifiability constraints, noise-sensitive derivative-based formulations that amplify sensor measurement errors, and the inability to decouple generator-internal damping from grid contributions. The proposed framework resolves these limitations through multi-scenario excitation using sensor-acquired voltage and current signals, derivative-free state consistency optimization, and physics-based regularization that enforces PH structure preservation. Complete identification of eight key parameters (H, D, Xd, Xq, Xd′, Xq′, Tdo′, Tqo′) is achieved with errors ranging from 1.26% to 9.10%, and validation confirms RMS rotor angle errors below 1.2° and speed errors below 0.15%, demonstrating suitability for transient stability analysis, passivity-based control design, and oscillation damping assessment.

With the increasing penetration rate of Power Electronic Converter (PEC) based technologies, the electrical power systems are facing the problem of transient stability since the PEC based technologies do not contribute to the system inertia, and the proportion of synchronous generators (i.e., the source of inertia) is in decreasing rate. In addition, PEC based technologies’ components have poor inherent damping. It is very important to analyze the system characteristics of a power system to minimize the potential instabilities during the contingencies. This paper presents the parametric sensitivity analysis of the rotor angle stability indicators for the 39-bus New England power system. The indicators of rotor angle stability analysis such as critical fault clearing time (CCT), Eigenvalue points, damping ratio, frequency deviation, voltage deviation, and generator’s speed deviation are identified and analyzed for three case scenarios; each scenario has six sub-cases with different inertia constants. The results show that the CCTs for each component will be reduced if the inertia reduces at any section of a multi-machine power system. Although the applied three scenarios with six sub-cases are identified to be stable in this analysis, the decreasing inertia constant has significant impact on the power system dynamics.

With the active modernization of power facilities and the increasing deployment of maneuverable combined-cycle gas turbines (CCGTs), the selection of rational start-up strategies becomes increasingly important from the perspective of power quality. Excessive acceleration of power ramp-up may lead to undesirable voltage deviations, particularly in transmission networks with limited grid stiffness. This study investigates the impact of CCGT start-up ramp rate on voltage dynamics and power quality indicators at a 110/220 kV grid node. A detailed model of the Almaty power hub was developed in MATLAB/Simulink, taking into account the network structure, generating units, transformers, and aggregated loads. Three start-up scenarios were analyzed: an existing combined heat and power plant, a 504 MW combined-cycle gas turbine unit, and a 560 MW combined-cycle gas turbine unit with fuel afterburning. Voltage dynamics were evaluated using RMS-based indicators and a stabilization criterion incorporating a 5 s sliding time window and an 80% admissibility threshold. The simulation results reveal a nonlinear relationship between the start-up ramp rate and voltage quality. Increasing the ramp rate reduces the voltage stabilization time; however, beyond approximately 0.05 MW/s, further acceleration does not lead to additional improvement in power quality. The results indicate the existence of an optimal range of start-up ramp rates that provides a compromise between start-up speed and voltage quality requirements. The proposed approach can be used in the development of start-up algorithms for modern combined-cycle power plants connected to 110/220 kV transmission networks.

We perform a rare-event study on a simulated power system in which grid-scale batteries provide both regulation and emergency frequency control ancillary services. Using a model of random power disturbances at each bus, we employ the skipping sampler, a Markov Chain Monte Carlo algorithm for rare-event sampling, to build conditional distributions of the power disturbances leading to two kinds of instability: frequency excursions outside the normal operating band, and load shedding. Potential saturation in the benefits, and competition between the two services, are explored as the battery maximum power output increases. This article is part of the theme issue ‘The mathematics of energy systems’.

The development of smart grid technologies has resulted in increased interdependence between power and communication systems. Many of the operations in the existing power system rely on a stable and secured communication system. For electrically weak systems and time-critical applications, this reliance can be even greater, where a small degradation in communication performance can degrade system stability. However, despite inter-dependencies between power and communication systems, only a few studies have investigated the impacts of communication system performance on power system dynamics. This study investigates the dependencies of power system dynamics operations on a communication system performance. First, a detailed, dynamic networked microgrid model is developed in the GridLAB-D simulation environment, along with a representative multi-traffic, multi-channel, multi-protocol communication system model, developed in the network simulator (ns-3). Second, a hierarchical engine for large-scale infrastructure co-simulation framework is developed to co-simulate microgrid dynamics, its communication system, and a microgrid control system. The impact of communication system delays on the dynamic stability of networked microgrids is evaluated for the loss of generation using three use-cases. While the example use-cases examine microgrid applications and the impact to resiliency, the framework can be applied to all levels of power system operations.