The power output from the wind turbine in distributed generation (DG) resources is intermittent in nature, which adversely affects the system frequency in an interconnected system. Hence, it is important to study the system dynamic performance when DG resources are connected to the existing power system. This study presents the load frequency control of the three‐area thermal–thermal–hydro system with DG resources in area 1. Proportional integral fractional derivative (PID ^μ ) controller is proposed as a secondary controller. System dynamics are compared among integral, proportional integral (PI), PI derivative (PID), fractional order PID (PI ^λ D ^µ ) and PID ^μ controllers whose parameters are optimised simultaneously using nature inspired ant lion optimiser (ALO) technique. The analysis shows the competitive performance of PI ^λ D ^µ and PID ^μ controllers. Furthermore, the PID ^μ controller parameters are optimised using hybrid ALO‐pattern search technique, which outperforms the ALO optimised PID ^μ controller. A flexible AC transmission system device called gate controlled series capacitor performs better than an interline power flow controller. The studies show that the gate controlled series capacitor placed in all lines is its optimal location. The system dynamics are improved considerably with the incorporation of high voltage direct current link, the transient droop of the hydro governor. The PID ^µ controller effectively handles the parametric variations, random load and wind power profiles.

An interconnected power system requires specific restrictions to be maintained for frequency, tie-line power, and the terminal voltage of synchronized generators to avoid instability. Therefore, frequency stability and voltage regulation issues are covered individually and jointly in the current research work. Initially in test system 1, automatic generation control (AGC) investigations are done on two interconnected systems with thermal plants and electric vehicles in one area and distributed generation and electric vehicles in other area. The automatic voltage regulator (AVR) problem alone is chosen for investigation in test system 2. The third test system addresses the combined AGC and AVR issues. The performance of the fractional-order tilt-integral-derivative (TID) controller is compared with that of a widely used proportional integral derivative (PID) controller in all three test systems studies. The findings demonstrate better performance of the TID controller than PID in terms of providing superior dynamic metrics, such as low peak overshoots, undershoots, and settling time, as well as decreased oscillations amplitudes. Additionally, TID performs better than PID despite randomized load disturbance, system non-linearities, and time delays in AGC and the combined AGC and AVR problem. The PSO-tuned TID controller is insensitive to variation in load damping factor and time constants of the AVR system. Finally, the results are validated by an OPAL-RT 4510 real-time digital simulator.

The frequency and terminal voltages in power systems are the two critical operating points that balance active and reactive powers, which must be maintained within predefined limits through automatic generation control (AGC) and automatic voltage regulator (AVR) control loops. To address this issue, in this manuscript, the problem of a combined AGC and AVR is solved using a non-integer order PID controller. Its parameters are adjusted using the recently proposed equilibrium optimizer (EO) technique. Along with the conventional sources, renewable energy sources such as geothermal power plants, and electric vehicles are considered. The EO tuned non-integer order PID controller outperformed the traditional integer order PI and PID controllers in view of peak overshoots, undershoots, and settling times. The performance of EO is evaluated and found superior against widely used particle swarm optimization and firefly algorithms in presence of non-integer order PID controller. Different case studies such as random load disturbance, the effect of nonlinearities, the impact of communication time delay and sensitivity analysis have been performed, which also test the heftiness of the non-integer order PID controller. The obtained results are verified using the real-time digital simulator OPAL-RT (OP4510) for nominal conditions.

In micro-grids (MGs), renewable energy resources (RESs) supply a major portion of the consumer demand. The intermittent nature of these RESs and the stochastic characteristics of the loads cause a frequency stabilization issue in MGs. Owing to this, in the present manuscript, the authors try to uncover the frequency stabilization/regulation issue (FRI) in a two-area MG system comprising wind turbines (WTs), an aqua-electrolyzer, a fuel cell, a bio-gas plant, a bio-diesel plant, diesel generation (DG), ship DG, electric vehicles and their energy storage devices, flywheels, and batteries in each control area. With these sources, the assessment of the FRI is carried out using different classical controllers, namely, the integral (I), proportional plus I (PI), and PI plus derivative (PID) controllers. The gain values of these I, PI, and PID controllers are tuned using the recently proposed smell agent optimization (SAO) algorithm. The simulation studies reveal the outstanding performance of the later controller compared with the former ones in view of the minimum settling period and peak amplitude deviations (overshoots and undershoots). The SAO algorithm shows superior convergence behavior when tested against particle swarm optimization and the firefly algorithm. The SAO-PID controller effectively performs in continuously changing and increased demand situations. The SAO-PID controller designed in nominal conditions was found to be insensitive to wide deviations in load demands and WT time constants.

Frequency, tie-line power, and the terminal voltages of synchronized generators must all be kept within prescribed limits to ensure the stability of an interconnected power grid through combined automatic generation control (AGC) and automatic voltage regulator (AVR) loops. Thermal power plants, electric vehicles, and renewable energy sources—including solar and wind, geothermal, and solar thermal power plants—form the two-area integrated power system in present research. A new cascade controller named the cascaded proportional integral derivative (PID) and fractional-order PID (CPID-FOPID) controller is proposed for the first time, whose performance is compared with the PID and FOPID controller. The results show that the proposed cascade controller outperforms PID and FOPID in delivering superior dynamic characteristics, including short settling times and low oscillation amplitudes. A new metaheuristic algorithm named the coot algorithm was applied to optimize the parameters of these controllers. The suggested controller outperforms FOPID in the combined AGC and AVR problem under uncertain conditions (random load disturbance, variable input of solar irradiation, and wind power). Robustness of the controller is tested with significant variation in the turbine time constant of the thermal and geothermal power plant. In this study, authors also investigated the best possible coordination between the superconducting magnetic energy storage (SMES) and gate-controlled series capacitor (GCSC) devices to control both voltage and frequency simultaneously. The effect of communication time to the power system is analyzed in this study. Additionally, the obtained results are satisfactorily validated using OPAL-RT real-time digital simulator.