The radial topology of the Multi-terminal High Voltage Direct Current (MTDC) power system is a preferred connection for the gigawatt- renewable power due to its scalability and reliability. However, a radial topology with a metallic return bipolar converter configuration MTDC network possesses technical challenges regarding DC fault current interruption and grid expansion. Furthermore, such HVDC networks are energized in a specific manner, usually involving a separate energizing controller. This paper proposes a design of DC Hubs with direct current circuit breakers (DCCBs) along with a network energization sequence without requiring a separate controller. Additionally, a PI-based controller for post-DC fault circulating current in MTDC's metallic return is proposed. This control operates after DCCB recloses, removing any offset in the metallic cable by regulating the power setpoint in the converters. The proposed control is investigated under a pole-to-ground fault occurrence in the DC Hub. The proposed solution is validated by RSCAD/RTDS^@ simulation by applying detailed and average equivalent models of turbines, DCCBs and converters. The results of this simulation show a successful suppression of the DC circulating current, which results in a balanced operation of the MMCs in the post fault steady state conditions.

This paper presents a new formulation for intentional controlled islanding (ICI) of power transmission grids based on mixed-integer linear programming (MILP) DC optimal power flow (OPF) model. We highlight several deficiencies of the most well-known formulation for this problem and propose new enhancements for their improvement. In particular, we propose a new alternative optimization objective that may be more suitable for ICI than the minimization of load shedding, a new set of island connectivity constraints, and a new set of constraints for DC OPF with switching, and a new MILP heuristic to find initial feasible solutions for ICI. It is shown that the proposed improvements help to reduce the final optimality gaps as compared to the benchmark model on several test instances.

The increase in Power Electronic (PE) converters due to the increase in offshore wind energy deployment have given rise to technical challenges (e.g., due to unprecedented fast dynamic phenomena) related to voltage and frequency stability in the power system. In the Offshore Wind Farms (OWFs), the currently available current injection-based voltage control for PE converters are not suitable for voltage control in PE dominated systems due to the absence of continuous voltage control and ineffectiveness during islanding. Moreover, in such power systems, the conventional controllers are not suitable for frequency control due to the absence of dynamic frequency control. The paper presents the Direct Voltage Control (DVC) strategy in a real-time environment to mitigate challenges related to voltage and frequency stability during islanding of OWFs. The control strategy is implemented in the average Electro-magnetic Transient (EMT) model of Type-4 Wind Generator (WG) in RSCAD® Version 5.011.1. It is compared with the benchmark model of the control strategy in DIgSILENT PowerFactory™ 2019 SP2 (×64) in EMT platform. The comparison based on shortterm voltage stability and reactive current injection reveals that both the models provide similar results, confirming the validation of the RSCAD model. Moreover, the detailed representation of the converters in the RSCAD model provides a better depiction of the real-world operation.

In this book chapter, a benchmark test system has been studied for power system stability considering the high share of power electronic converter-based generation. Furthermore, both conventional PI controllers and grid forming control have been taken in to account in order to study the impact of the high penetration of power electronic converter on the dynamic response of the power system.

In this book chapter, innovative protection schemes have been suggested to prevent bottlenecks of the power system considering the integration of offshore and onshore wind turbines and HVDC link. Four different countermeasures are proposed and investigated. Their effect on the system overloading and stability is also taken into account. The models for the simulation have been implemented in PowerFactory.

In this chapter, a grid forming control approach called direct voltage control (DVC) for wind turbine control with restoration capability of power system with a high share of power electronic-based generation units is presented and discussed. All the detailed explanation, DSL-based control is presented for dynamic simulations in DIgSILENT software.

The grid integration of renewable energy sources interfaced through power electronic converters is undergoing a significant acceleration to meet environmental and political targets. The rapid deployment of converters brings new challenges in ensuring robustness, transient stability, among others. In order to enhance transient stability, transmission system operators established network grid code requirements for converter-based generators to support the primary control task during faults. A critical factor in terms of implementing grid codes is the control strategy of the grid-side converters. Grid-forming converters are a promising solution which could perform properly in a weak-grid condition as well as in an islanded operation. In order to ensure grid code compliance, a wide range of transient stability studies is required. Time-domain simulations are common practice for that purpose. However, performing traditional monolithic time domain simulations (single solver, single domain) on a converter-dominated power system is a very complex and computationally intensive task. In this paper, a co-simulation approach using the MOSAIK framework is applied on a power system with grid-forming converters. A validation workflow is proposed to verify the co-simulation framework. The results of comprehensive simulation studies show a proof of concept for the applicability of this co-simulation approach to evaluate the transient stability of a dominant grid-forming converter-based power system.

In this chapter, a generic model of fuel cells and electrolysers suitable for power system stability studies has been developed in PowerFactory. Both theoretical modelling background and software implementation of fuel cells and electrolysers are detailed. Furthermore, a case study based on a three area test system has been performed, which provides valuable insight into the benefits that the synergy between the electricity and hydrogen sectors can bring to power system stability.

This paper proposes a Electro-Magnetic Transient (EMT) model of a 2 GW offshore network with the parallel operation of two Modular Multi-level Converter (MMC)—High Voltage Direct Current (HVDC) transmission links connecting four Offshore Wind Farms (OWFs) to two onshore systems, which represent a large scale power system. Additionally, to mitigate the challenges corresponding to voltage and frequency stability issues in large scale offshore networks, a Direct Voltage Control (DVC) strategy is implemented for the Type-4 Wind Generators (WGs), which represent the OWFs in this work. The electrical power system is developed in the power system simulation software RSCAD™, that is suitable for performing EMT based simulations. The EMT model of 2 GW offshore network with DVC in Type-4 WGs is successfully designed and it is well-coordinated between the control structures in MMCs and WGs.

The main objective in this chapter is to develop and present a generic model for wind turbine (WT) which can be used for both DFIG- and FSCG-based WT for large-scale multi-machine power system dynamic studies. The presented model is developed for RMS simulation on PowerFactory, and it can be used as a replacement for both DFIG- and FSCG-based WTs without making any changes in the generic model itself. The generic RMS model is appropriate for the stability studies of large grids where the detailed dynamics, i.e., control action in the range of milliseconds, of the power electronic converter-based controllers do not play an important role.

This chapter is dedicated to present some control mechanism to cope with the challenges due to the growth of the penetration level of the power electronic interfaced generation (PEIG) in sustainable interconnected energy systems. Specifically, this chapter presents different forms of fast active power injection (FAPI) control schemes for the analysis and development of different mitigation measures to address the frequency stability problem. Among the considered FAPI control schemes are the traditional droop-based scheme, and two propositions implemented in the form of a derivative-based control and a second-order virtual synchronous power (VSP)-based control. All the detailed explanation, DSL-based control is presented for the simulations in DIgSILENT software. Simulation results show that thanks to proposed FAPI controllers, it is possible to increase the maximum share of wind power generation without violating the threshold limits for frequency stability problem in low-inertia systems.

Unlike synchronous generators, wind turbines cannot directly respond to large disturbances, which may cause transient instability, due to their power electronic-based interface and maximum power control strategy. To effectively monitor the influence of wind turbines, this paper proposes an approach that combines decision trees (DTs), and a newly developed variant of the Mean-Variance Mapping Optimization (MVMO) algorithm, to simultaneously tackle the problem of selecting the key variables that properly reflect the transient stability performance of a system dominated by wind power, and designing the DTs for reliable online assessment of transient stability. The notion of key variables refers to the set of variables that are closely related to the modified power system transient stability performance as a consequence of the replacement of conventional power plants by wind generators. The selection of key variables is formulated as a non-linear optimization problem with weight factors as decision variables and is tackled by MVMO. A weight factor is assigned to each key variable candidate, and its value is considered to reflect the degree of influence of the key variable candidate on the splitting property and estimation accuracy of the DTs. The samples of the key variable candidates and the initialized weight factors are used to build the first group of DTs. Then, MVMO iteratively evolves the weight factors according to its special mapping function with minimizing DTs' estimation error. According to the final list of optimized weight factors, system operators can select a reduced set of variables with the largest weight factors as key variables, depending on the resulting accuracy of the DTs. Meanwhile, DTs built by using key variables are considered as the optimal performance trees for transient stability estimation. In this way, the selection of key variables and the development of DTs are made jointly and automatically, without the interference of the users of the DTs. Test results on the modified IEEE 9 bus system and a synthetic model of a real power system show that the proposed method can correctly identify the set of key variables related to wind turbine dynamics, as well as its ability to provide a reliable estimation of the transient stability margin.