Enhancing the transient stability of interconnected power systems by designing an adaptive fuzzy-based fractional order PID controller

Abstract

The reliable and efficient operation of the electrical energy transmission system heavily relies on maintaining stability as a key requirement. Interconnected power systems often experience low-frequency oscillations (LFOs), which have the potential to initiate instability and, subsequently, necessitate careful attention and investigation. To tackle this issue, researchers have focused on various controllers, including Fractional-Order Proportional-Integral-Derivative (FOPID) controllers. The FOPID controller, with its increased number of design parameters, has proven to be more successful than the traditional PID controller in various engineering applications. However, determining the optimal parameters for the controller becomes more challenging due to the increased design space. Moreover, the performance of fixed-gain FOPID controllers may be degraded when confronted with highly nonlinear and uncertain controlled objects such as power systems. This issue is primarily attributed to the static nature of fixed-gain FOPID controllers. To overcome these challenges associated with fixed-gain FOPID controllers and to instill an adaptive quality, this article introduces a novel power system control methodology. This adaptive approach combines a FOPID control strategy with a fuzzy logic system and is denoted as EOA-AFFOPID. The proposed adaptive controller dynamically tunes its coefficients through a fuzzy block, which significantly improves the overall performance of the control system. To establish a performance benchmark, we have also created an alternative controller, named EOA-FOPID, a version of the optima FOPID controller with fixed coefficients. The proposed methodology is applied to multi-machine interconnected power systems equipped with Static Synchronous Series Compensators (SSSCs), and comparative evaluations are conducted with other popular recent control strategies. The comparisons demonstrate the effectiveness of the EOA-AFFOPID control strategy in damping system fluctuations and achieving significant performance improvements in terms of different metrics including overshoot, undershoot, and settling time.