Modified Differential Evolution Algorithm for Governing Virtual Inertia of an Isolated Microgrid Integrating Electric Vehicles

The integration of the significant number of virtual inertia control systems could create new challenges in the implementation of virtual inertia control systems in today and future power systems. Since the large amounts of RESs/DGs have been integrated by the electrical industry into power systems, considerable effort is required to effectively manage the installed virtual inertia control units. This chapter presents the technical challenges and further research needs regarding the virtual inertia control system. The key aspects of the challenges are how to manage changes in system topology created by various virtual inertia control systems as new control units in the network along with the resulted change in system dynamics and how to make the robust power grid by taking the advantage of the potential flexibility of the decentralized/distributed virtual inertia control units. The challenges such as the optimization of the virtual inertia control system and real-time inertia estimation are emphasized for supporting the reliable operation of virtual inertia control units for their application in low inertia power systems with high penetration of RESs. Finally, some important challenges related to the market for inertia service and the regulation of the virtual inertia control system are discussed for further research.

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 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.

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.

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.

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)

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

The modern power system is experiencing transformation from the rotational-generation-equipment-dominated system to a power-electronics-converter-dominated system, with the increasing penetration of renewable energy resources such as wind and photovoltaic. The power-electronics-based renewable generation, as well as energy storage system, can lead to the reduction of system inertia. As dc systems such as dc microgrids are attracting more attention, the low-inertia issues will challenge their stability. In this paper, a comprehensive review of inertia-enhancement methods in dc power systems is presented. The concept and significance of the inertia in dc systems is firstly introduced, and then the types of inertia-providing sources in dc systems are discussed. After that, the different virtual inertia control strategies applied in power electronics converters are classified and investigated. These virtual inertia control methods are proven to have a great ability to enhance the inertia of a dc system. The challenges and future research direction are discussed at the end of the article. In this paper, the previous research work on the inertia of dc power systems is summarized in detail, the inertia-enhancement methods of DC systems are comprehensively introduced, and the future research directions are prospected.

To mitigate voltage transients caused by power fluctuations in microgrid systems, this study investigates model predictive control and virtual inertia control for the voltage regulation strategy of energy storage unit converters. By drawing an analogy with the virtual synchronous machine equation in AC systems, the virtual capacitor inertia equation is derived for DC systems. Subsequently, model predictive control (MPC) is integrated with virtual inertia (VI) control, leading to the development of an MPC-VI cooperative control method. The reference value for the inner control loop is computed in real time using model prediction, enabling the injection of a counteracting signal opposite to the direction of DC bus voltage fluctuation during disturbances. This approach effectively suppresses rapid voltage variations and enhances system inertia. Furthermore, by incorporating a threshold-based mechanism, the issue of prolonged dynamic response time is mitigated. Simulation and experimental results demonstrate that, compared to conventional control strategies, the proposed MPC-VI method significantly attenuates instantaneous and severe voltage fluctuations, allowing for a more gradual voltage transition during transient events. Additionally, with the implementation of the threshold equation, the system returns to steady state without notable delay, preserving the droop characteristics of the control scheme.

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.

With the conventional power supply being replaced by a large number of wind power and the investment of ultra‐high‐voltage transmission channels, the operating characteristics of the power system have undergone profound changes, and the characteristics of power electronics have become increasingly evident. The dynamic characteristics of DFIG (double‐fed induction generator) with virtual inertia control are in a coupling relationship with the dynamic characteristics of the power system, which leads to significant changes in the frequency oscillation characteristics of the wind turbine. The intrinsic mechanism and external performance of the sub and super‐synchronous oscillating systems are essentially different from those of conventional wind turbines. Based on the analysis of oscillation mechanism and stability of traditional wind turbines, this study reviews the literature and summarises the existing key technical problems. Secondly, the eigenvalue analysis and simulation are used to demonstrate the influence of virtual inertia on the sub and super‐synchronous oscillations of wind turbines.

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.

Cybersecurity is crucial for modern power systems due to their high digitization. The open information and communication technology, that is (ICT) being used for the operation of such systems, is highly vulnerable to cyber threats. The adopted smart grid concept around the globe enables the utilization of demand-side for providing ancillary services based on well-known demand response (DR) programs. These programs aggregate smart appliances in homes and electric vehicles (EVs) for providing vital services such as frequency regulation and voltage support. Since the aggregation is based on cyber layer, any cyber threat could affect the ancillary services that are being delivered from the aggregators, which might lead to stability and security issues resulting in brownout or massive blackouts. This chapter discusses the cybersecurity in DR program and shows its importance for modern and future smart power systems due to their stability and security margins. Furthermore, the cyberattack case study is implemented in a power system with demand side program responsible for providing primary frequency support ancillary service, where the results confirm the high vulnerability of modern power systems to cyber threats on DR-active power reserve providers. Moreover, technical suggestions are provided for enhancing the cybersecurity in DR programs in power systems with high power share from renewable energy sources.

Ensuring frequency stability in low-inertia microgrids with high penetration of renewable energy sources (RESs) is a critical challenge, as these sources lack physical inertia and generate variable, unpredictable power. This leads to amplified frequency deviations, further aggravated by nonlinearities and stochastic behavior. Virtual inertia control, which emulates the inertial response of synchronous generators using energy storage, has emerged as a promising solution. However, conventional approaches often lack the responsiveness and robustness required to manage RES uncertainties and system nonlinearities, thereby limiting their effectiveness in dynamic environments. Moreover, the application of variable structure fuzzy logic controllers for load frequency control in renewable-dominated, low-inertia microgrids remains largely underexplored. To address these limitations, this paper proposes a variable structure fuzzy proportional-integral-derivative (VSC-FPID) controller designed for virtual inertia support in low-inertia microgrids. The proposed controller is tested under diverse loading scenarios and nonlinear conditions to ensure comprehensive evaluation. Its parameters are optimally tuned using the particle swarm optimization algorithm to guarantee efficient and robust dynamic performance. Comparative analysis with conventional PID and fuzzy-PID controllers demonstrates the superior capability of the VSC-FPID controller. Simulation results conducted in MATLAB confirm its robustness in regulating frequency under load fluctuations, RES uncertainties, and nonlinear system dynamics, including severe low-inertia and worst-case operating conditions involving simultaneous load and renewable disturbances. The proposed controller consistently outperforms benchmark methods, significantly improving transient and steady-state performance. Specifically, it achieves notable reductions in overshoot, undershoot, and settling time, with up to 60% improvement compared to the nearest competing technique. These results highlight the potential of the VSC-FPID-based virtual inertia control strategy as an effective solution for enhancing frequency stability in renewable-rich, low-inertia microgrids.

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.