The increasing deployment of offshore wind farms necessitates robust and stable high-voltage direct current networks. Achieving optimal stability, especially in damping oscillations on the DC side, remains a significant challenge. This study focuses on mitigating post-fault converter de-blocking oscillations, a critical issue exacerbated by complex interactions between AC and DC systems, converter dynamics, and system faults. These behavior are governed by nonlinear system dynamics, making traditional control methods less effective in ensuring stability. A comprehensive analysis of DC side oscillations and their interaction with converter dynamics is developed to understand the key factors influencing system stability. The research investigates a DC voltage regulation damping approach, identified as the most effective solution in the literature. Comprehensive parametric sensitivity analysis evaluates system behavior under diverse operational conditions. Addressing current damping method limitations during converter de-blocking, this work proposes an innovative control approach integrating fuzzy logic control and proportional–integral controllers. This approach enhances DC voltage regulation and incorporates a modified circulating current suppression control in the inner loop. The coordinated fuzzy logic control and proportional–integral controller dynamically adjusts to nonlinear system dynamics in real-time, providing a robust framework for improved post-fault recovery. It aims to achieve faster recovery times and reduced overshoot compared to conventional methods. The proposed controller's efficacy is validated through comparative analysis with existing approaches. Electromagnetic transient) simulations using the real-time digital simulator platform demonstrate the controller's performance under realistic operating conditions.

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The continuous operation and planning of electric power systems undergoes several technical and economic changes associated with environmental and societal goals toward clean, affordable, and resilient sustainable energy supply and deployment. This entails diverse upgrades, which include, for instance, integration with other energy sectors and massive addition of renewable power generation, responsive demand, and different types of storage. The dynamic properties and strength of power systems are evolving toward unprecedented levels with lowered sources for the effective management of active and reactive power balancing in different time scales. Thus, the overall security and reliability performance can be seriously compromised as unexpected disturbances may eventually cause violations to the security limits that are established for the electric power system; this may lead to the outage of important system elements and even partial or total blackouts.@en

The urgent need for a significant reduction of greenhouse emissions (around 50% by 2030 and net zero by 2050) is driving an acceleration of major technological upgrades in electrical power systems. This is gradually translating into new architectures of transmission and distribution networks. Ideally, the upgraded networks enable the technoeconomic, reliable, and environmentally friendly deployment of a high share of emerging technologies, primarily based on power electronic converters. Such major upgrades occur in renewable power generation, responsive demand (including data centers and electrolysis plants), electrical and nonelectrical energy conversion and storage, and flexible compensation devices.@en

This work seeks to reduce the severity of congestion in the medium voltage (MV) cyber-physical systems (CPES) by optimising the network topology in line with seasonal variations in the supply and demand of electricity. To this aim a two-stage reconfiguration algorithm is proposed. In the first stage, the positions of the normally open switches within the network are optimised in to adjust the power flow therein. These optimised positions are subsequently used in the second stage to calculate the network variables. The first stage is implemented as a mixed-integer linear program (MILP) optimisation in Python, whereas the second stage consists of a Newton-Raphson calculation in DIgSILENT PowerFactory software package. The benefit of network reconfiguration is that it is a short-term and low-cost solution which can be implemented by a distribution system operator (DSO) without relying on other external parties. The presented case study addresses the need of seasonal reconfigurations to accommodate for the manual operation of the switches present within a synthetic model of MV CPES, which is implemented inspired from CPES in the Netherlands. The application of the algorithm significantly reduces the frequency by which reconfiguration actions can be performed. Furthermore, the algorithm is able to consistently reduce congestion within the analysed synthetic CPES, completely removing it or reducing its severity. It also outperforms two alternative optimisation options implemented in PowerFactory with regard to the objective function value. Those being an iterative exploration of meshes and a genetic algorithm.

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The Nordic Power System is undergoing significant transformation and development in the coming years. A driving factor for this is the increased dependency on renewable energy sources and high voltage direct current transmission (HVDC). Various stability challenges due to the dynamics of reactive power - voltage (Q-V) balancing and active power - frequency (P-f) balancing seep into the system with such rise of non-synchronous generation (NSG). This paper investigates the projected impact of NSGs on the P-f dynamic performance of Nordic power system in 2030. As NSGs are systems with low inertia, power discrepancies lead to larger oscillations, higher Rate of Change of Frequency (RoCoF) and bigger maximum frequency deviation (MFD) values. To address these issues, Emulated Inertia (EI) control for wind turbines and Synthetic Inertia (SI) control for VSC-HVDC links are proposed in this paper. The simulation is carried out using DIgSILENT PowerFactory 2022 SP1 simulation software. The results obtained confirm the Effectiveness of the proposed EI and SI methods to enhance frequency response and mitigate deviations.@en

As modern trends demand efficient methods to massively and promptly exploit clean energy, there is an urgent need of solutions that can help the ambition of accelerating the development and integration of larger scale energy systems with the capacity to extract, store, and utilize huge amounts of renewable energy sources. In view of this, the rated power output of the wind generation technology is expected to significantly increase in the near future to enable multi-gigawatt roll outs, e.g. the European plans for Offshore infrastructure development in the North-Sea. Besides, gigantic energy systems shall transmit the power to onshore interconnected systems via HVDC transmission. This paper introduces an EMT model of a 20 MW wind generation system with the conventional back-to-back converter replaced by a combination of an AC to DC converter and a DC to DC converter. While the need of such systems is acknowledged in the literature, the design and performance analysis of high power implementation of such systems have not been addressed yet. The proposed system operates at a voltage level of 100 kV, which can directly transfer power through HVDC interconnection. The designed control aspects are outlined and the resulting dynamic response obtained from realtime digital simulation (RTDS) are discussed. The presented wind generator concept can help in reducing the size of a planned energy system by requiring lesser system components. Also, the system efficiency can be enhanced by decreasing the number of power conversion stages.@en

One crucial aspect of Modular Multi-level Converter (MMC)- Bipolar Point-to-Point (BPP) configuration systems is the occurrence and damping of oscillations on the DC side of HVDC networks. These oscillations can arise due to various factors, including the interaction between the AC and DC systems, de-blocking of converters after a fault, and the dynamic behaviour of connected power sources. Various investigations consider damping methods that delve to mitigate oscillatory tendencies and establish stability during Post-Fault (PF) recovery. However, the current research on damping predominantly focus on the impact of AC fault or unbalanced conditions on the DC side. This paper presents an investigation that addresses the gap concerning with sub-synchronous oscillations occurring during the de-blocking of a MMC-BPP within the post-DC fault recovery. The investigation also considers active damping and enhanced current control loop as a combined mitigation measure. A meticulous real-time digital simulation supported parametric sensitivity analysis is conducted on a four-terminal MMC-BPP synthetic power system. Numerical results provide insight into the level of effectiveness that can be achieved by the considered concept of active damping.

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Cascading failures in power systems are extremely rare occurrences caused by a combination of multiple, low probability events. The looming threat of cyberattacks on power grids, however, may result in unprecedented large-scale cascading failures, leading to a blackout. Therefore, new analysis methods are needed to study such cyber induced phenomena. In this article, we propose a data-driven method for dynamical analysis of power system cascading failures caused by cyberattacks. We provide experimental proof on how attacks may accelerate the cascading failure mechanism, in comparison to historically observed blackouts. Using a dynamic power grid model, consisting of multiple, coordinated protection schemes, we define and analyze the point of no return in a cascading failure sequence by applying the Hilbert-Huang transform for time-frequency analysis. Numerical results indicate, cyberattacks may accelerate cascading failures at least by a factor of 3x. This is due to the excitation and non-damping of multiple frequency modes greater than 1 Hz in a short time span. The proposed method is tested using time domain simulations conducted through a modified IEEE 39-bus test system, which can simulate cascading outages using coordinated protection schemes.

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Power system operators require advanced applications in the control centers to tackle increasingly variable power transfers effectively. One urgently needed application concerns estimating the feasible available aggregated flexibility from a power system network, which can be effectively deployed to mitigate issues in interconnected networks. This paper proposes the TensorConvolution+ algorithm to address the above application. Unlike related literature approaches, TensorConvolution+ estimates the density of feasible flexibility combinations to reach a new operating point within the p-q flexibility area. This density can improve the decision-making of system operators for efficient and safe flexibility deployment. The proposed algorithm applies to radial and meshed networks, is adaptable to new operational conditions, and can consider scenarios with disconnected flexibility areas. Using convolutions and tensors, the algorithm efficiently aggregates the combinations of flexibility providers' adjustable power output that can occur for each flexibility area set point. Simulations on the meshed Oberrhein and radial CIGRE test networks illustrate the effectiveness of TensorConvolution+ for flexibility estimation with high numerical confidence and a minor computing effort. Additional simulations highlight how system operators can interpret the estimated density of feasible flexibility combinations for decision-making purposes, the algorithm's capability to estimate disconnected flexibility areas, and adapt to new operating conditions.

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Electrical power systems are witnessing a paradigm shift from traditional synchronous generators towards an in-creased integration of power electronic interfaced (PEl) generation. As the global community leans towards renewables, ensuring grid stability during this transformation becomes paramount. This paper presents a fundamental study of oscillatory stability dynamics for three emerging grid-forming converter controller topologies: Virtual Synchronous Machine (VSM), droop control, and the Synchroverter, in comparison to conventional syn-chronous generation. Utilizing the two area 4 generator (2A4G) system for analysis, the research underscores the significance of converter integration, proximity-based enhancements in damping capabilities, and the delicate equilibrium in parameter tuning for optimal stability. The results pave the way for informed decision-making in grid development and renewable energy com-prehension, highlighting the potential of grid-forming converter controllers in steering a sustainable energy future.

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Power grid digitalization introduces new vulnerabilities and cyber security threats. The impact of cyber attacks on power system stability is a topic of growing concern, which is yet to be comprehensively analyzed. Traditional power system stability analysis is based on the impact of non-malicious small, and large physical disturbances. However, cyber attacks introduce a new dimension to power system stability, in which malicious cyber actors can selectively target critical systems and applications and cause severe stability issues. Hence, in this work, the traditional disturbances considered in power system stability classification are expanded from physical to cyber-physical disturbances caused by cyber attacks. Based on a thorough state-of-the-art, an analysis of how cyber attacks can translate into physical disturbances affecting the traditional power system stability categories is performed. The system stability analysis is expanded by mapping the power system stability categories with the defined cyber-physical attack types. The findings of this work showcase the importance of cyber security for power system stability.@en

Low-inertia power systems require more innovative operation, control, and protection strategies to maintain the operation secure and reliable. One of the challenges related to these systems is the need for knowledge of the inertia level (kinetic energy stored in the rotating masses) in real time. This paper proposes a framework for training and deploying machine learning methods for real-time power systems’ kinetic energy forecasting. Linear Regression and Long Short-Term Memory methods are implemented in the Python interpreter of the Typhoon HIL 404 real-time simulator for forecasting the kinetic energy of the Nordic Power System in real-time. This paper provides implementation details together with possible future expansions of the framework. Simulation results show that the trained models can predict the kinetic energy in a forecasting horizon of four hours with a Mean Absolute Error lower than other methods currently available in the literature.@en

Modernization of power systems leads to more power electronic interfaced units in the generation, demand, and transmission. Examples are remotely installed renewable energy sources, loads with constant power, or high voltage direct current (HVDC) corridors. These changes significantly affect the frequency stability margins of the system and thus special control techniques should be applied in the converters of the new installed units so as to shoulder the frequency regulation in case of commonly occurred active power imbalances. The response of such units has to be cooperative in order to avoid problems such as insufficient reactions or overshoots. In this chapter, a coordinative tuning approach of the active power gradient control scheme applied to the controllers of modular multilevel converter (MMC)-based HVDC links and proton exchange membrane electrolyzers with the provision of fast frequency support in a multiarea hybrid HVDC-HVAC power system with responsive demand units is proposed. This tuning uses an optimization approach based on mean variance mapping optimization and is able to minimize the frequency excursions in all interconnected areas participating in the frequency regulation even without communication between the system nodes. This technique has shown great results in terms of quality and convergence rate within a short number of fitness evaluations achieving a set of frequency responses within acceptable limits set by operators even in case of the loss of the largest generating unit in the weakest system area. It has also revealed the applicability of such a method in more complex systems and the necessity for sophisticated tuning methods according to the application needs and the system characteristics.

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Power electronic interfaced devices progressively enable the increasing provision of flexible operational actions in distribution networks. The feasible flexibility these devices can effectively provide requires estimation and quantification so the network operators can plan operations close to real- time. Existing approaches estimating the distribution network flexibility require the full observability of the system, meaning topological and state knowledge. However, the assumption of full observability is unrealistic and represents a barrier to system operators' adaptation. This paper proposes a definition of the distribution network flexibility problem that considers the limited observability in real-time operation. A critical review and assessment of the most prominent approaches are done, based on the proposed definition. This assessment showcases the limitations and benefits of existing approaches for estimating flexibility with low observability. A case study on the CIGRE MV distribution system highlights the drawbacks brought by low observability.@en

The increasing penetration of Internet of Things (IoT) devices at the consumer level of power systems also increases the surface of attack for the so-called Manipulation of Demand through IoT (MaDIoT) attacks. This paper provides a comparison of the impact that MaDIoT attacks could have on power systems with different characteristics, such as the IEEE 39-Bus (New England) and the PST-16 system (simplified European model), by assuming that the attacker does not have advanced knowledge of the grid. The results for the IEEE 39-Bus system expand and complement the results obtained by previous work. The simulation results show that these systems present significant differences between them with respect to the success probability of an attack, being in general much higher for the IEEE 39-Bus system. In the PST-16 system, the required number of bots to obtain a certain success probability varies depending on the area attacked. However, a high probability of success does not necessarily mean a high impact on the system. This paper shows that the response to the high-impact MaDIoT attacks of the two models considered is very different as the initial impact of the attack on the system also differs, mainly affecting rotor angles in the PST-16 system, and the frequency in the IEEE 39-Bus.@en

Future carbon-neutral power systems impose many challenges; one is the urgent need for a simulation platform that allows replicating the complex systems’ actual dynamic performance. This paper shows the results of implementing a cyber-physical testbed co-simulation in real-time to analyse the system frequency response considering primary frequency control and emergency frequency control: under-frequency load-shedding (UFLS) protection schemes. The proposed testbed uses a physical layer of two real-time simulators from different vendors in a closed loop, Opal-RT OP4510 and Typhoon HIL 604, being the first simulator for test system modelling and the remainder used to implement the UFLS protection scheme. Two connections of the real-time simulators are considered: physical connection using wires to exchange analogue signals and cybernetic digital communication using ANSI C37.118 communication protocol. The cybernetic layer of the testbed models a test system, controls the real-time simulation, and implements digital communication between the simulators. A modified version of the P.M. Anderson 9-bus systems is used for testing purposes, including phasor measurement units (PMUs). Results of the real-time simulation show the appropriate performance of the proposed testbed.

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Due to the continuous increase (decrease) in the number of inverter-based (synchronous) generators in modern electrical power systems, the theoretical foundations behind widely used system strength and voltage stability assessment methods require thorough revision. The existing evaluation methods such as the Short-Circuit Ratio (SCR) are often based on simplifications which may produce inaccuracies, particularly when studying weak systems. As a result, a misleading estimation of voltage stability can occur, exposing systems to unnecessary renewables curtailment or other inappropriate remedial actions that may cause partial disruptions or potential instability. This paper provides a rigorous analytical revision of voltage stability assessment to confidently evaluate the maximum power transfer under various operating conditions. Subsequently, the proposed approach is applied as an enhanced method of system strength evaluation. The method is extensively tested on a single-machine-infinite-bus test system. Numerical results show a notably more accurate assessment relative to the common alternative methods.@en

The amount of power electronic interfaced generation (PEIG) is significantly proliferating in modern cyber-physical energy systems (CPESs). The limited capabilities (e.g. inertia, over-current) of PEIG, together with their location and technology-specific designed control systems, alter the dynamic properties of different types of stability phenomena, e.g. sub-synchronous oscillations (SSOs). A poorly damped SSO can emerge, within a sub-second time scale, through conflicting inter-actions between the controls of PEIG and the dynamic response of the surrounding electrical network. This paper focuses on the modelling and assessment of such interactions, with emphasis on the integration of large-size full converter (a.k.a. type-4) based wind power plants (WPPs). By combining different analysis tools, the implemented model supports sensitivity assessment of the occurrence and observability of a poorly damped SSO. State-space model based eigenanalysis is iteratively used to ascertain damping variability of a dominant SSO, excited by inappropriate controller settings of the WPP. Power spectral density (PSD) analysis is used to qualitatively estimate the degree of observability of the poorly damped SSO across different buses of a CEPS. Numerical tests are performed on a modified version of the IEEE-39 bus system by using DIgSILENT PowerFactory 2022 SP1. Suggestions are provided for the deployment of data generated from phasor measurement units (PMUs) in the monitoring and wide-area damping control of critical SSOs.@en

Future distribution networks (DN) are subject to rapid load changes and high penetration of variable distributed energy resources (DER). Due to this, the DN operators face several operational challenges, especially voltage violations. Optimal power flow (OPF)-based reactive power control (RPC) from the smart converter (SC) is one of the viable solutions to address such violations. However, sufficient communication and monitoring infrastructures are not available for OPF-based RPC. With the development of the latest information communication technology in SC, cyber-physical co-simulation (CPCS) has been extensively used for real-time monitoring and control. Moreover, deploying OPF-based RPC using CPCS considering the controller design of SC for a realistic DN is still a big challenge. Hence, this paper aims to mitigate voltage violations by using OPF-based RPC in a real-time CPCS framework with multiple SCs in a realistic DN. The OPF-based RPC is achieved by performing the CPCS framework developed in this study. The CIGRE medium-voltage DN is considered as a test system. Real-time optimization and signal processing are achieved by Python-based programs using a model-based toolchain of a real-time DN solver and simulator. Real-time simulation studies showed that the proposed method is capable of handling uncertain voltage violations in real time.

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This paper concerns with the determination of a suitable level of overplanting for photovoltaic systems. For this purpose, six futuristic operational scenarios for the Dutch electrical power system are generated for year 2050. A synthetic model is developed by using DIgSILENT Power Factory 2022 SP3 to investigate the steady-state systemic performance in each operational scenario, taking into account three cases with different levels of overplanting. Power flow calculations are conducted to reflect on the resulting voltage profiles and active power losses as well as on the implications on the required network upgrades (e.g. addition of lines, transformers, and reactive power compensation devices).@en