Technical Challenges and Further Research in Virtual Inertia Control

In modern power systems, there is a greater penetration of renewable sources, resulting in the expansion of microgrid. By implementing RES instead of conventional synchronous machines, the system’s overall inertia is significantly reduced. Modern and future power systems must reduce system inertia and keep the frequency at its nominal value since frequency oscillation impacts on the functionality, stability, and resilience of the system. Therefore, creating a stable, scalable, and reliable virtual inertia control system is crucial to effectively minimize the deviations during significant contingencies. Consequently, taking into account the probable issues, the foremost objective of this research work is to improve the dynamic security of an island microgrid through the implementation of a frequency control concept based on virtual inertia control. In the research study, the proposed microgrid system comprises of photovoltaics, wind-generating units, thermal power units, storage units, electric vehicles (EVs), and loads. A cascaded PIDFN controller is optimally designed using a novel metaheuristic modified differential evolution (MDE) algorithm that regulates the frequency based on virtual inertia control. In the MATLAB®/SIMULINK environment, various operating situations such as load variations, RES, and EVs disconnection are investigated, and the performance of the VIC-based MDE controller was compared to that of other controllers based on evolutionary optimization algorithms such as DE and TLBO. The results validate that the recommended virtual inertia control strategy enhances the reliability of the system.

To integrate renewable energy into microgrids with a favorable inertia property, a virtual inertia control application is needed. Considering the inertia emulation capabilities, insufficient emulation of inertia power due to the lower and short-term power of storage systems could significantly cause system instability and failure. To enhance such capability, this paper applies a virtual inertia control topology to the superconducting magnetic energy storage (SMES) technology. The SMES-based virtual inertia control system is implemented in a microgrid with renewables to emulate sufficient inertia power and maintain good system frequency stability. The efficacy and control performance of the proposed control method are compared with those of the traditional virtual inertia control system. Simulation results show that the shortage of system inertia due to renewable penetration is properly compensated by the proposed control method, improving system frequency stability and maintaining the robustness of system operations.

The growing penetration of wind power has led to a continuous decline in system rotational inertia, posing serious challenges to the stability of next-generation power systems. Moreover, the strong dependence of wind generation on weather conditions, particularly the increasing frequency of extreme wind events, further exacerbates system vulnerability, making stability enhancement under adverse conditions an urgent research priority. To address this issue, this study proposes a virtual inertia-based control strategy for hybrid wind–storage systems, formulated through transfer function modeling of wind turbines, thermal generators, and energy storage units. By appropriately simplifying the dynamic characteristics of individual components, a comprehensive system-level transfer function model is developed to characterize the frequency response of the hybrid system. Virtual inertia support is provided by controlling the outputs of wind and storage units. A conventional wind–energy storage hybrid system without a virtual inertia control strategy was developed for comparison to evaluate the frequency regulation performance against the proposed system. Simulation studies under large load disturbance scenarios demonstrate that the hybrid wind–storage system achieves a smaller frequency nadir and faster steady-state recovery compared with standalone wind power system and a conventional wind–energy storage hybrid system without a virtual inertia control strategy. Notably, even under extreme wind conditions requiring complete curtailment of wind turbines, the energy storage unit continues to deliver virtual inertia, thereby maintaining system stability, superior to the conventional wind–energy storage hybrid system without virtual inertia control. These findings highlight the enhanced reliability and dynamic performance of wind–storage hybrid systems in mitigating frequency deviations within high-renewable environments, while also demonstrating the proposed control strategy’s robust adaptability to extreme weather conditions. The proposed approach offers valuable insights into strengthening the operational resilience of future low-carbon power systems.

The continuous increasing share of power-converter-based renewable energies weakens the power system inertia. The lack of inertia becomes a main challenge to small-scale modern power systems in terms of control and stability. To alleviate adverse effects from inertia reductions, e.g., undesirable load shedding and cascading failures, three-phase grid-connected power converters should provide virtual inertia upon system demands. This can be achieved by directly linking the grid frequency and voltage references of dc-link capacitors/ultracapacitors. This paper reveals that the virtual inertia control may possibly induce instabilities to the power converters under weak grid conditions, which is caused by the coupling between the d- and q-axes as well as the inherent differential operator introduced by the virtual inertia control. To tackle this instability issue, this paper proposes a modified virtual inertia control to mitigate the differential effect, and thus, alleviating the coupling effect to a great extent. Experimental verifications are provided, which demonstrate the effectiveness of the proposed control in stabilizing three-phase grid-connected power converters for inertia emulation even when connected to the weak grid.

The large-scale deployment of sustainable energy sources has become a mandatory goal to reduce pollution from electricity production. As photovoltaic (PV) plants replace conventional synchronous generators (SGs), their significant inherent rotational inertia characteristics are reduced. The high penetration of PV results in reduced system inertia, leading to system frequency instability. Virtual inertial control (VIC) technology has attracted increasing interest because of its ability to mimic inertia. Adoption of the energy storage system (ESS) is hindered by the high cost, although it can be used to provide virtual inertia. The determined forecast gives PVs the ability to reserve power before shading and compensate the power when a system power drop occurs, which can increase system inertia. Nevertheless, it has forecast errors and energy waste in a stable state. To improve the stability of the microgrid and improve the ESS efficiency, this study proposes an adaptive forecasting-based (AFB) VIC method using probabilistic forecasts. The adaptive power reserve and virtual inertia control are proposed to reduce energy waste and increase system inertia. The simulation results reveal that the proposed method has adaptive system inertia to reduce the reserved power, required ESS power capacity, and battery aging.

Power hardware-in-the-loop testing for multiple inverters with virtual inertia controls

This paper investigates virtual inertia control of doubly fed induction generator (DFIG)-based wind turbines to provide dynamic frequency support in the event of abrupt power change. The model and control scheme of the DFIG is analysed. The relationships among the virtual inertia, the rotor speed and the network frequency variation are then investigated. The hidden kinetic energy that can be released to contribute to the grid inertia by means of shifting the operating point from the maximum power tracking curve to a virtual inertia control curve is investigated. The virtual inertia control strategy based on shifting power tracking curves of the DFIG is proposed and the calculation method for determining these virtual inertia control curves is presented. A three-machine system with 20 percent of wind penetration is used to validate the proposed control strategy. Simulation results show that by the proposed control strategy, DFIG based wind farms have the capability of providing dynamic frequency support to frequency deviation, and thus improving the dynamic frequency performance of the grid with high wind power penetration. (6 pages)

In this paper, an adaptive virtual inertia-damping system based on model predictive control (MPC) is proposed to enhance the frequency dynamic performance of islanded microgrids (MGs) considering a high penetration level of renewable energy sources (RESs). Recently, a large amount of RESs is replacing traditional generating units, causing an undesirable effect on the MG frequency stability and system inertia, and thus weakening the MG. Therefore, the proposed control system handles this challenge to enhance the robust performance and stability of the MG with high RESs penetration during contingencies. The proposed online MPC strategy estimates the gains of the virtual inertia control (VIC) system (i.e., inertia and damping coefficients) in high RESs MG. The performance of the proposed adaptive VIC system is compared with the conventional VIC system (i.e., constant values of inertia and damping coefficients) using MATLAB/Simulink under numerous disturbances and system uncertainties. Moreover, the effectiveness of the proposed adaptive VIC system based on the online MPC strategy is verified by comparing its performance with the adaptive VIC system based on fuzzy logic control, which is designed to estimate only the inertial gain. The results highlight that the frequency stability is upgraded, and the adaptive virtual inertia system based on MPC successfully supports low-inertia islanded MGs with RESs and load fluctuations.

An incremental tide in IoT devices prompts a centralized control system where physical controls such as buttons and knobs can become virtual and centralized via augmented reality: especially headset AR. I conduct a literature mapping to identify gaps and create a front-end based virtual control panel API tool to allow programmers and end-users to rapidly create headset augmented reality-based virtual control systems for physical devices. I probe on how an artificial intelligence back-end aids in such a system in terms of panel creation and automation as well as panel usage and control scenarios. I delve into use cases of the virtual control panel API including mass usage and specialized scenarios. Furthermore, I specify the guidelines for a requirements elicitation study for such a system along with potential points of derivation. Next, I probe into implications and limitations of such a system in terms of artificial intelligence, usage, and precision. My work has implications for programmers and users of a virtual control system backed by artificial intelligence for the purpose of controlling physical IoT devices in mass usage as well as in specialized scenarios.

As a typical grid-forming control method, virtual synchronous generator (VSG) control enhances system inertia but introduces frequency oscillation issues. This problem becomes particularly severe in multi-VSG parallel systems when inconsistent virtual inertia exists among power sources, significantly compromising the security and stability of power system operation. Virtual inertia control can directly regulate the rate of change of frequency (RoCoF) under constant torque difference conditions to suppress frequency oscillations, offering faster response characteristics. Therefore, this paper proposes a distributed virtual inertia control strategy for multi-VSG parallel systems. First, a small-signal model of the multi-machine parallel system is established, and its small-signal stability is demonstrated. Second, a neighbor-communication-based distributed virtual inertia coordination control method is proposed. Through neighbor information exchange and local decision-making, this method enables dynamic adjustment of each unit's virtual inertia, driving frequency synchronization among all units in the system. This effectively suppresses post-disturbance frequency oscillations and enhances the dynamic performance of low-inertia power systems. Furthermore, the stability of the proposed control strategy is rigorously proven through the construction of a Lyapunov energy function. Finally, MATLAB/Simulink simulations verify that the proposed virtual inertia control strategy can effectively mitigate frequency oscillations while reducing their settling time.

The high-level penetration of intermittent renewable power generation may limit power system inertia, resulting in system frequency instability in increasing power converter-based energy sources. To resolve this problem, virtual inertia control using distributed gray wolf optimization (DGWO) method in a synchronous generator is simulated under a distinct output fluctuation condition. First, the DGWO algorithm was established to achieve a local and global balance solution, and standard test functions were employed to verify the model convergence. Second, the key parameters that determine the effect of the virtual inertia controller in the power grid were analyzed. A DGWO-based optimization strategy to stabilize inertia was also developed. Finally, simulation results using step and random loads under a high permeability level are provided to verify the effectiveness of the proposed model. In the step load disturbance, the system can recover from the disturbance point to the stable point after 3 s under the regulation of the proposed control strategy, which is reduced by 18 s compared with the traditional control method. In the random load test, it takes only 12 s, 63 s less than the traditional one. Accordingly, the power system frequency can be stabilized more quickly from a disturbance state to a stable stage.

A dc microgrid is a low inertia system dominated by power converters. As a result, the change rate of the dc voltage is very fast under power variation. In this study, a distributed virtual inertia control is proposed to enhance the inertia of the dc microgrid and decrease the change rate of the dc voltage. The inertia of the dc microgrid can be enhanced by the kinetic energy in the rotor of the permanent magnet synchronous generators (PMSG)‐based wind turbine, the energy stored in batteries and the energy from the utility grid. By introducing a virtual inertia control coefficient, a general expression of the inertial power provided by each controllable power sources is defined. The proposed inertia control is simply a first‐order inertia loop and is implemented in the grid‐connected converter, the battery interfaced converter and the PMSG interfaced converter, respectively. The small‐signal model of the dc microgrid with the proposed inertia control is established. The range of virtual inertia control coefficient is determined through stability analysis. Finally, a typical dc microgrid is built and simulated in Matlab/Simulink, and the effectiveness of the proposed control strategy and correctness of the stability analysis are verified.

Renewable power systems dynamic security using a new coordination of frequency control strategy based on virtual synchronous generator and digital frequency protection

In the near future, an expected shortage of fossil fuel supplies for conventional generating units has become mandatory. At the same time, there is a high level of penetration of renewable energy sources for these conventional power grids, especially using wind energy turbines. Generally, renewable energy sources have the most important technical disadvantage which is low inertia constant. This results in relatively oscillations at any slight change in any of the power system states. This means a weakly stable system. Virtual inertial controllers can help solve this problem but are they efficient enough. In this paper, a question will be asked: is it possible for conventional controllers to play the same role as virtual inertial controllers. The use of strong action controllers to play the same role of virtual inertia controllers will be proposed. Required analysis and sufficient simulations are driven to answer these questions. The answer shows the effectiveness of strong action controllers to compensate the role of virtual inertia controllers.

Virtual radio space control system is the necessary tendency to spacecraft control. Spacecraft control system based on Virtual radio is different from traditional software radio in the data paralleled transmission and time synchronization. Dynamic time-division multiplexing transmission mode is presented by analyzing the data paralleled and synchronous transmission. The problem caused by traditional software radio frame that paralleled high speed data being blocked by low speed data is solved in the transmission time delay. According to uncertainty problems of data transmission and dealing time delay caused by the asynchronous work model of the virtual radio spacecraft control system, the method of time synchronization based on the data frame structure is presented, and the measure synchronization is preformed in a general way.