The concept of direct adaptive control for improving voltage and frequency regulation loops in several power system applications

This article presents the idea of direct adaptive control for several power system applications such as the Egyptian power system (EPS), a three-zone interconnected microgrid (MG), and a single machine connected to the grid (SMIB). The main concept of the proposed adaptive method is built on the tuning of the controller gains using Harris hawks optimizer (HHO). In order to maintain the frequency and voltage at their nominal values, a modified virtual rotor (virtual inertia + virtual damping) is investigated as a tertiary control loop within the proposed EPS and the 3-area MG system. For SMIB application, a secondary automatic voltage regulator (AVR) has been added to the primary AVR within the excitation system to offer more adequate damping characteristics for the synchronous generator of the studied system. Where the proportional-integral-derivative power system stabilizer (PID-PSS) is connected to the excitation system for a single machine tied to the grid to significantly mitigate low-frequency oscillations due to various expected faults and undesirable operating conditions. The proposed direct adaptive control strategy has been used to tune the integral controller of the secondary AVR and PID for SMIB application, and also to adjust the virtual rotor in the EPS and the 3-area MG applications. The operative performance of the introduced adaptive secondary AVR is assessed against the conventional system (no PSS), Lead-Lag PSS, and PSS type 2 based PSO and WECC standard under the effect of a 3-φ short-circuit fault subjected at the grid bus considering solar photovoltaic (PV) farm-based grid. Moreover, the EPS system and 3-area MG are evaluated under the effect of load change conditions and partial injection of PV and random loads. The final findings prove that the direct adaptive concept can provide robust performance and effectively maintain the dynamic stability of the main grid against fluctuations.