Virtual inertia control for improving frequency stability in hybrid power systems using sparrow search algorithm with mountain gazelle optimization

The increasing need for energy, coupled with the diminishing availability of fossil fuels, has driven the widespread utilization of Renewable Energy Sources (RESs). These resources are recognized for their eco-friendliness and economic viability and are increasingly integrated into interconnected power systems for widespread use. This development has been primarily facilitated by progress in electricity networks. However, stabilizing the frequency in microgrids is challenging due to the intermittent behavior of RESs. Over-penetration of RESs can lead to challenging frequency oscillations, making system stability harder to maintain. Moreover, integrating RESs into isolated MGs requires power electronic devices, such as static converters, which lack rotational mass and reduce overall system inertia. This thesis aims to enhance the frequency response in a smart multi-microgrid power system integrated with renewable energy sources by utilizing advanced virtual inertia control techniques. At the outset, this study considers a Proportional-Integral-Derivative (PID) controller whose parameters are tuned using a hybrid sparrow search algorithm-grey wolf optimizer (SSAGWO) for a multi-area Load Frequency Control (LFC) problem. Results from the analysis of the multi-area multi-source demonstrate that the proposed SSAGWO-optimized PID controller outperforms other state-of-the-art algorithms presented in the literature, showing improvements of 53%, 60%, 20%, and 70% in terms of settling time, peak undershoot, control effort, and steady-state error values, respectively. Although the results show the proposed approach effectively manages renewable impacts on system stability, combining lower-rated RES with higher-rated conventional generators does not clearly indicate an effect on system inertia. A robust control approach of a Fractional Derivative Virtual Inertia Controller (FDVIC), integrated with a modified demand response controller, has been introduced for an islanded low inertia Multi-Microgrid (MMG) system. Fractional Order Proportional Integral Derivative (FOPID) controllers have been employed to regulate the active power output of the biodiesel generators and the Geothermal station of the proposed Microgrid (MG). Optimal parameters for the three-loop controller were determined using a new hybrid Sparrow Search and Mountain Gazelle Optimizer (SSAMGO). SSAMGO's performance was then evaluated against other optimization algorithms across various scenarios. The results demonstrate that the estimated value of the virtual inertia and virtual damping when using SSAMGO-optimized the proposed controller is less than other optimization techniques. The estimated value of the virtual inertia has a very significant impact on the size of the capacity of the Energy Storage System (ESS) that is used to support the MG power system with instant active power. In other words, the minimum value of the virtual inertia constant means reducing the size of the battery and leading to a reduction in the cost. Furthermore, the achieved outcomes exhibited substantial improvements in terms of settling time, peak undershoot, control effort, and steady-state error values compared to other optimization algorithms. Moreover, the system's stability is analyzed in the frequency domain through the utilization of Bode analysis. Finally, the validation of the power system is ultimately achieved by utilizing both the New England IEEE-39 bus test system and conducting Real-Time Digital Simulation experiments using the Opal-RT simulator.

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