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 contribution deals with the optimization of the frequency response of a multi-area, multi-energy HVDC-HVAC cyber-physical power system, representing a power electronic-dominated power system. The system consists of a three-area system, modified so that the areas are electromagnetically decoupled through MMC-based HVDC links, and different controllable energy sources, such as fully decoupled wind turbines type IV and proton exchange membrane electrolysers, are installed at various points of the system. The modified system exhibits three decoupled areas with different generation and demand mixes characterized by different inertia levels and increased controllability due to the converters’ capabilities. The outer controllers of the power electronic interfaced elements installed have been modified with the active power gradient control scheme to respond to frequency excursions and provide fast frequency support to the grid in case of commonly occurred active power-frequency imbalances. A problem formulation for coordinated optimization is presented, aiming at a coordinated tuning of the parameters of the frequency controllers of the synthetic inertia elements participating in the frequency regulation against critical commonly occurred active power-frequency imbalances. The formulations consider the minimization of the dynamic displacements of the areas’ speed following an active power imbalance. To effectively solve the optimization problem and enhance the frequency stability of the system, a powerful metaheuristic optimization algorithm, the mean-variance mapping optimization (MVMO) algorithm, has been utilized. The optimization results can effectively highlight the tuning strategy that achieves the best frequency response of the system under various commonly occurred active power frequency disturbances. It can also provide further insight on the proper utilization of various sources of synthetic inertia with respect to their response capabilities. Finally, the simulation results can also clarify the importance of the location of installation of converter-based elements providing fast frequency support with respect to the grid node the imbalance occurs.

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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

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

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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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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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

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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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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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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The increasing integration of distributed energy resources such as photovoltaic (PV) systems into distribution networks introduces intermittent and variable power, leading to high voltage fluctuations. High PV integration can also result in increased terminal voltage of the network during periods of high PV generation and low load consumption. These problems can be solved by optimal utilization of the reactive power capability of a smart inverter. However, solving the optimization problem using a detailed mathematical model of the distribution network may be time-consuming. Due to this, the optimization process may not be fast enough to incorporate this rapid fluctuation when implemented in real-time optimization. To address these issues, this paper proposes a co-simulation-based optimization approach for optimal reactive power control in smart inverters. By utilizing co-simulation, the need for detailed mathematical modeling of the power flow equation of the distribution network in the optimization model is eliminated, thereby enabling faster optimization. This paper compares three optimization algorithms (improved harmony search, simplicial homology global optimization, and differential evolution) using models developed in OpenDSS and DigSilent PowerFactory. The results demonstrate the suitability of the proposed co-simulation-based optimization for obtaining optimal setpoints for reactive power control, minimizing total power loss in distribution networks with high PV integration. This research paper contributes to efficient and practical solutions for modeling optimal control problems in future distribution networks.

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Distantly-located offshore energy hubs need to be connected to the shore via High Voltage Direct Current (HVDC) links to allow for an efficient bulk power exchange. A bipolar configuration of the HVDC link is suitable for a point-to-point connection, as it provides redundancy, and, therefore, a larger reliability, e.g. half of the rated transfer capacity can still be transferred via one of the poles in case of a fault occurring on the other pole. Nevertheless, a control strategy of the converters that can effectively enable a situation-dependent power routing between the two poles constitutes a research challenge. In this paper, two control strategies are proposed for the offshore Modular Multi-level Converters (MMCs) of a bipolar HVDC link connecting a 2 GW offshore hub to the shore. The strategies, based on DC current and DC voltage measurements, respectively, enable to track and adjust the amount of power flowing through each pole of the link. Real-time digital simulations show that both strategies can effectively route the power exchanges through the bipolar HVDC link, e.g. operation under balanced or unbalanced conditions. The strategy based on DC current seems more suitable to manage the dynamic performance of the HVDC link.@en

With the rise of the integration of renewable energy sources, the operating characteristics of existing electric power distribution systems are evolving and changing. As a result, the digitalisation of the distribution network is gaining attention for effective real-time monitoring and control. Cyber-Physical cosimulation is one of the options for implementing and testing novel concepts and ideas before actual implementation on the distribution network. Therefore, this paper presents some experiences on the cyber-physical testbed in the distribution network. Moreover, the methodology, possible challenges and mitigation techniques are also presented for a cyber-physical cosimulation testbed of optimal reactive power control in smarter distribution network (SDN). The cyber-physical co-simulation testbed is analysed using a Typhoon HIL 604 and OpenDSS on a CIGRE MV distribution.@en

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

Power electronic interfaced generation (PEIG) has become significantly dominant in the electrical power grid. This development is leading to a decrease in systemic inertia and damping against electrical oscillations. This causes the introduction of new and faster dynamic phenomena. One of these phenomena is sub-synchronous control interaction (SSCI), occurring as sub-synchronous oscillations (SSOs) in the system. Several real-world events reported so far have been related with large wind power plants (WPPs) and the improper tuning of the grid side converter (GSC) of (type-4) fully rated converter (FR C) wind turbines. As other PEl G have similar topologies and control systems, it is a very relevant topic. Weak grid conditions often contribute to the risks of SSO events. This paper proposes supplementary wide-area damping (WAD) to the control system of the GSC, focused on damping excursions of the phase locked loop (PLL). Signals measured by a remote phasor measurement unit (PMU) are communicated to the control system, which uses it for dynamic damping control. The effects of the WAD are tested by comparing the results of linearization-based eigenvalue analysis with and without the addition of WAD. Supplementary analysis conducted by using time-domain simulations and Prony analysis confirm the positive effect of WAD. Numerical tests are performed in DlgSILENT PowerFactory 2023 SP2 on a modified IEEE-39 bus test system.@en

Distribution grids are subject to a drastic evolution in their operating conditions due to the high integration of renewable energy resources (RES) and their ability to regulate voltage. To cope with this issue, modern solar photovoltaic (PV) systems are equipped with smart inverters enabled with communication capabilities that allow the coordinated operation to offer services such as controlling voltage by appropriately setting the reactive power production. This paper proposes a co-simulation framework for smart converter reactive power control in active distribution grids. The proposed framework is used to appropriately control smart inverters installed in PV systems to inject/withdrew reactive power ensuring voltage control at the time that minimises active power losses of the active distribution grid (ADG). The proposed approach has been tested in a modified version of the Kumamoto distribution system. The suitability of the proposed framework has been demonstrated.@en

Reaching net-zero emissions within the proposed time requires an enormous effort from the energy sector, and it is even more challenging for the electricity infrastructure. This article offers a modified version of the IEEE 39-bus system specifically created to allow zonal day-ahead market (ZDAM) simulations. The system representation is based on the original version of the IEEE 39-bus system but considers the integration of renewable energy resources (RES) in the generation mix: solar and wind. Hourly time series are used to define load profiles and wind and solar power generation. The zonal dayahead energy market information has been created by solving the optimisation problem. Numerical results of the proposed power test system are provided for the yearly ZDAM and steady-state performance, in N and N-l conditions, respectively, through Pyomo and DIgSILENT PowerFactory features.@en