article · Fractal and Fractional
Modern power systems experience undesirable frequency swings due to unpredictable fluctuations in renewable energy sources and electrical loads. High penetration of renewables also lowers system inertia, complicating traditional load frequency control. To resolve this, an intelligent fractional-order integral controller was developed alongside virtual inertia control for a two-area interconnected power system. The controller parameters were tuned using the grey wolf optimisation algorithm to minimise both frequency deviations and tie-line power deviations. When evaluated through computer simulations in MATLAB against conventional integral and standard fractional-order integral controllers under varying conditions, the proposed control scheme demonstrated superior resilience and performance. The findings confirm that combining the optimised fractional-order controller with virtual inertia control effectively regulates grid frequency across interconnected networks facing volatile renewable generation and shifting demand.
Integrating large amounts of solar and wind energy reduces natural grid inertia, making power networks prone to unstable frequency fluctuations. Maintaining a steady frequency is essential to prevent equipment damage and blackouts. By providing more effective frequency regulation through advanced control methods and virtual inertia, this approach helps support the transition towards cleaner, renewable-dominated electrical grids without risking system stability.
This work could benefit transmission system operators, microgrid developers, and grid automation software providers managing networks with high shares of renewable energy. Because the controller was validated solely through numerical simulations in MATLAB, it represents early-stage research. Transitioning towards practical use will require validation on real-time digital simulators or hardware-in-the-loop testbeds, followed by integration testing within utility-grade energy management systems.
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Since modern power systems are susceptible to undesirable frequency oscillations caused by uncertainties in renewable energy sources (RESs) and loads, load frequency control (LFC) has a crucial role to get these systems’ frequency stability back. However, existing LFC techniques may not be sufficient to confront the key challenge arising from the low-inertia issue, which is due to the integration of high-penetration RESs. Therefore, to address this issue, this study proposes an optimized intelligent fractional-order integral (iFOI) controller for the LFC of a two-area interconnected modern power system with the implementation of virtual inertia control (VIC). Here, the proposed iFOI controller is optimally designed using an efficient metaheuristic optimization technique, called the gray wolf optimization (GWO) algorithm, which provides minimum values for system frequency deviations and tie-line power deviation. Moreover, the effectiveness of the proposed optimal iFOI controller is confirmed by contrasting its performance with other control techniques utilized in the literature, such as the integral controller and FOI controller, which are also designed in this study, under load/RES fluctuations. Compared to these control techniques from the literature for several scenarios, the simulation results produced by the MATLAB software have demonstrated the efficacy and resilience of the proposed optimal iFOI controller based on the GWO. Additionally, the effectiveness of the proposed controller design in regulating the frequency of interconnected modern power systems with the application of VIC is confirmed.
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DOI: 10.3390/fractalfract7010062
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