The inevitable transition of the power system toward a sustainable and renewable-energy centered power system is accompanied by huge versatility and significant challenges. A corresponding shift in operation strategies, embracing more intelligence and digitization, e.g., a Cyber-Physical System (CPS), is needed to achieve an optimal, reliable and secure operation across all system levels (components, units, plants, grids) and by the use of big data. Digital twins (DTs) are a promising approach to realize CPS. In this paper, their applications in power systems are reviewed comprehensively. The review reveals that there exists a gap between available DT definitions and the requirements for DTs utilized in future power systems. Therefore, by adapting the current definitions to these requirements, a generic definition of a “Digital Twin System (DTS)” is introduced which finally allows proposing a multi-level and arbitrarily extendable “System of Digital Twin Systems (SDTSs)” idea. The SDTSs can be realized with an open-source framework that serves as a central data and communication interface between different DTSs which can interact by “Reporting Modules” and are regulated by “Control Modules” (CMs). Exemplary application scenarios involving multiple system levels are discussed to illustrate the capabilities of the proposed SDTS concept.

Renewable inverter-based resources (IBRs), such as wind energy conversion systems (WSs), replace directly grid-connected synchronous machines (SMs). Standard grid-following (GFL) control of IBRs decreases the power system inertia. This paper proposes virtual synchronous machine (VSM) based grid-forming (GFM) control for doubly-fed induction machine (DFIM) based wind energy conversion systems (WSs) with the following extensions: (i) feedforward torque control (FTC) for maximum power point tracking (MPPT), (ii) MPPT compensation for accurate inertia emulation, (iii) reference power point tracking (RPPT) to provide energy reserves, (iv) dynamic droop saturation control to mitigate power overloading, and (v) grid voltage control utilizing DFIM stator and rotor-side back-to-back inverter reactive power. The WSs are integrated into the IEEE 9-bus test system. Comprehensive simulation results give insights into (V)SM-based power system dynamics. Compared to existing VSM control without FTC, the proposed FTC increases the wind energy yield, i.e. typical MPPT performance is achieved, similar to GFL control. For high power penetration of IBRs, the proposed VSM control enables stable operation due to its GFM capability, whereas GFL control tends to instability. The VSM provides higher power system damping than a real SM due to (i) adaptable internal damping and due to (ii) faster droop control (if reserves available) which adapts the virtual turbine power without the dominant delays of real turbine dynamics.

Historically, grid-connected synchronous machines have formed the grid voltage and frequency. Today, the high penetration of inverter-based resources poses challenges to grid stability, as conventional grid-following control methods do not provide grid-forming capabilities. New grid-forming control methods need to stabilize the grid. Therefore, electromagnetic transient modeling is essential for control design and stability analysis in future power systems. This paper proposes a novel reduced-order modeling and identification approach for doubly-fed induction machines (DFIMs) with a grid-connected stator and inverter-connected rotor. The proposed generic modeling remains valid under varying grid or stator conditions. Consequently, the modeling approach is also applicable to induction machines (IMs) with an inverter-connected stator. In this paper, DFIM measurements identify a holistic current-to-flux mapping to model nonlinear magnetic saturation effects. A virtual current injection method is introduced to identify all differential inductances without additional measurements. Various simplified and holistic nonlinear modeling approaches are compared, and measurements validate the proposed holistic flux dynamics (HFD) model under varying grid conditions.

Historically, grid-connected synchronous machines have formed the grid voltage and frequency. Today, the high penetration of inverter-based resources poses challenges to grid stability, as conventional grid-following control methods do not provide grid-forming capabilities. New grid-forming control methods need to stabilize the grid. Therefore, electromagnetic transient modeling is essential for control design and stability analysis in future power systems. This paper proposes a novel reduced-order modeling and identification approach for doubly-fed induction machines (DFIMs) with a grid-connected stator and inverter-connected rotor. The proposed generic modeling remains valid under varying grid or stator conditions. Consequently, the modeling approach is also applicable to induction machines (IMs) with an inverter-connected stator. In this paper, DFIM measurements identify a holistic currentto-flux mapping to model nonlinear magnetic saturation effects. A virtual current injection method is introduced to identify all differential inductances without additional measurements. Various simplified and holistic nonlinear modeling approaches are compared, and measurements validate the proposed holistic flux dynamics (HFD) model under varying grid conditions.

This paper proposes grid-forming control for doubly-fed induction machines (DFIMs) based on a virtual synchronous machine (VSM), which synchronizes with the grid while providing the desired power response to grid phase jumps. A rotor current control (RCC) based on input-output (I/O) linearization protects the rotor-side inverter (RSI). In addition, a novel transient stator current control (TSCC) reduces current and torque oscillations. The results demonstrate the improved performance of the proposed control compared with (i) no TSCC or (ii) grid-following control using a phase-locked loop (PLL) instead of a VSM for grid synchronization.