The present work proposes a teaching–learning-based optimization (TLBO)-tuned fuzzy proportional-integral-derivative (PID) controller of two-area hydro-thermal generating units for automatic generation control (AGC). The proposed system takes into account the physical constraints such as transport delay (TD), generation rate constraint (GRC), and governor dead band (GDB) nonlinearities. Firstly, fuzzy PID controllers were designed for both the areas and their gains were optimized using various minimization objective function criteria. Furthermore, applications of flexible alternating current transmission system (FACTS) devices such as static synchronous series compensator (SSSC), thyristor-controlled series capacitor (TCSC), thyristor-controlled phase shifter (TCPS), and unified power flow controller (UPFC) were investigated by integrating FACTS devices in appropriate locations of the system. The simulation results revealed that the minimum objective values were attained when the UPFC was placed in the system. Lastly, robustness analysis was done to observe the capability of the proposed controller with UPFC by changing system parameters and considering random load disturbances.

Many issues have arisen for the electricity sector because of the widespread use of gadgets that rely on electrical power. India's energy demands are rising rapidly due to the country's rapid economic development. These days, almost every industry makes extensive use of electrical machinery and equipment. Electronic gadgets add a non-linear demand to the power grid, which can cause power quality (PQ) problems such as voltage fluctuations that can damage electrical equipment and even knock the grid down. As the use of DG units becomes more commonplace, complications related to power conversion interfaces, load switching, and other factors emerge as potential bottlenecks in service. Power filters were first created several decades ago to address problems with PQ and to dampen harmonics caused by nonlinear loads. This document summarises previous studies that have investigated the effectiveness of power filters and other techniques for enhancing power quality. There are also descriptions of research that is still going on and where it stands, as well as a look ahead to what its possible future benefits might be.

In this article, a bacterial foraging optimisation algorithm (BFOA)-based proportional integral derivative controller with derivative filter (PIDF) is proposed for frequency regulation of multi source hybrid power system. Initially, a two area, unequal area power system with PIDF controllers, are considered. The area 1 comprises of reheat thermal power system incorporated with distributed generation (DG) system comprising of wind turbine generators (WTGs), diesel engine generators (DEGs), fuel cells (FCs), aqua-electrolyser (AE), ultra capacitor (UC) and battery energy storage system (BESS). The area 2 comprises of hydrothermal power system. The gains of the PID controller with derivative filter are optimised by using integral time multiply absolute error (ITAE) criterion. The superiority of PIDF controller is demonstrated by comparing the dynamic responses with integral derivative (ID) and proportional integral (PI) controllers. The simulation results show that the performance of dynamic responses with PIDF controller is superior to others. Further, robustness analysis is performed by varying the system parameters and wind power variations. It is observed from the simulation results that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters.