• Energy Research

Abstract The low frequency electromechanical oscillations (LFEOs) in electric power system are because of weaker inter-ties, uncertainties, various faults and disturbances. These LFEOs (0.2-3 Hz.) are less in magnitude and are responsible for lower power transfer, increased losses and also threaten the stability of power system. An adaptive interval type-2 fuzzy sliding mode controlled power system stabilizer (AIT2FSMC-PSS) is presented to neutralize the LFEOs and enhance stability under uncertainties and external disturbances. The AIT2FSMC is a hybridization of type-2 fuzzy logic system (T2FLS) with conventional SMC to lower the chattering effect, enhance the robustness of reaching phase and improve system’s performance. Here, T2FLS is used for estimating the unknown functions of SMC. A robust sliding surface is presented to keep the system in the desired plane and remain stable under disturbance conditions. A modified control law is proposed for selecting the control parameters and Lyapunov synthesis is used to make the error asymptotically converging to zero. The effectiveness of the AIT2FSMC-PSS is accessed in single and multimachine power systems subjected to various uncertainties and disturbances. Again, comparison of performance indices (PIs), Eigen values, damping ratios, oscillating frequencies, integral time absolute error (ITAE), figure of demerit (FD) and frequency domain plots like Bode, root locus and Nyquist plots are also analyzed to access the efficacy of the proposed stabilizer. The simulated responses, comparative study and frequency plots conform the supremacy of the proposed AIT2FSMC-PSS in suppressing the LFEOs with lesser settling characteristics, offer stable performance and assures transient stability of power system as compared to other stabilizers.

<abstract> <p>The rising proportion of inverter-based renewable energy sources in current power systems has reduced the rotational inertia of overall microgrid systems. This may cause high-frequency fluctuations in the system leading to system instability. Several initiatives have been suggested concerning inertia emulation based on other integrated external energy sources, such as energy storage systems, to combat the ever-declining issue of inertia. Hence, to deal with the aforementioned issue, we suggest the development of an optimal fractional sliding mode control (FSMC)-based frequency stabilization strategy for an industrial hybrid microgrid. An explicit state-space industrial microgrids model comprised of several coordinated energy sources along with loads, storage systems, photovoltaic and wind farms, is considered. In addition to this, the impact of electric vehicles and batteries with adequate control of the state of charge was investigated due to their short regulation times and this helps to balance the power supply and demand that in turn brings the minimization of the frequency deviations. The performance of the FSMC controller is enhanced by setting optimal parameters by employing the tuning strategy based on an iterative teaching-learning-based optimizer (ITLBO). To justify the efficacy of the proposed controller, the simulated results were obtained under several system conditions by using a vehicle simulator in a MATLAB/Simulink environment. The results reveal the enhanced performance of the ITLBO optimized fractional sliding mode control to effectively damp the frequency oscillations and retain the frequency stability with robustness, quick damping, and reliability under different system conditions.</p> </abstract>