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In light of the challenges of integrating more renewable energy sources (RESs) into the utility grid, the virtual synchronous generator (VSG) will become an indispensable configuration of modern power systems. RESs are gradually replacing the conventional synchronous generators that are responsible for supplying the utility grid with the inertia damping properties, thus renewable power grids are more vulnerable to disruption than traditional power grids. Therefore, the VSG is presented to mimic the behavior of a real synchronous generator in the power grid through the virtual rotor concept (i.e., which emulates the properties of inertia and damping) and virtual primary and secondary controls (i.e., which emulate the conventional frequency control loops). However, inadequate imitation of the inertia power owing to the low and short-term power of the energy storage systems (ESSs) may cause system instability and fail dramatically. To overcome this issue, this paper proposes a VSG based on superconducting magnetic energy storage (SMES) technology to emulate the needed inertia power in a short time and thus stabilizing the system frequency at different disturbances. The proposed VSG based on SMES is applied to improve the frequency stability of a real hybrid power grid, Egyptian Power System (EPS), with high renewables penetration levels, nonlinearities, and uncertainties. The performance superiority of the proposed VSG-based SMES is validated by comparing it with the traditional VSG approach based on battery ESSs. The simulation results demonstrated that the proposed VSG based on the SMES system could significantly promote ultra-low-inertia renewable power systems for several contingencies.

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This paper describes the integration of a photovoltaic (PV) renewable energy source with a superconducting magnetic energy storage (SMES) system. The integrated system can improve the voltage stability of the utility grid and achieve power leveling. The control schemes employ model predictive control (MPC), which has gained significant attention in recent years because of its advantages such as fast response and simple implementation. The PV system provides maximum power at various irradiation levels using the incremental conductance technique (INC). The interfaced grid side converter of the SMES can control the grid voltage by regulating its injected reactive power to the grid, while the charge and discharge operation of the SMES coil can be managed by the system operator to inject/absorb active power to/from the grid to achieve the power leveling strategy. Simulation results based on MATLAB/Simulink® software prove the fast response of the system control objectives in tracking the setpoints at different loading scenarios and PV irradiance levels, while the SMES injects/absorbs active and reactive power to/from the grid during various events to improve the voltage response and achieve power leveling strategy.

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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). Where a large amount of RESs is recently replacing traditional generating units, causing an undesirable effect on the MG frequency stability and the 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. Also, the effectiveness of the proposed adaptive VIC system based on the online MPC strategy (which considers both inertia and damping coefficients) 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.INDEX TERMS Adaptive virtual inertia system, model predictive control (MPC), microgrid (MG), frequency stability, high penetration of renewable energy sources (RESs).

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