Muhammad Ragab

Current power networks face considerable issues due to a continuous decrease in inertia and increased sensitivity to load/generation fluctuations. The main cause of these problems is the enhanced penetration capabilities of renewable energy sources. An unbalanced load with high power output greatly affects the frequency behavior of electrical grids. Several load-frequency control mechanisms are commonly employed to tackle these problems. Accordingly, the purpose of this work is to present a novel optimal load frequency control methodology for dual-area-linked power systems that contain a variety of conventional (i.e. thermal generator) and renewable (i.e. solar photovoltaic plant) power sources. A revolutionary hybrid regulator, the one plus proportional integral double-integral derivative with a proportional fractional derivative with fractional filter (1 + PIID-PD ^μ F ^λ ), has been designed. Its goal is to lessen frequency drifts brought on by any known load disturbance. The optimal gains of the 1 + PIID-PD ^μ F ^λ controller are finely adjusted using the mother optimization algorithm, an up-to-date population-based metaheuristic optimization technique that simulates the procedure of birthing and growth. The mother optimization algorithm has demonstrated its superior performance compared to other brand-new optimization methods, including tuna swarm optimization and sea horse optimization. The effectiveness of the proposed mother optimization algorithm-based 1 + PIID-PD ^μ F ^λ regulator is assessed by comparing its performance with other cascaded regulators in existing literature, such as TIDF-PID ^μ D, FOPI-PIDA, and PID-TID, which stand for tilt integral derivative with filter-proportional integral derivative fractional derivative with filter, proportional integral-proportional integral derivative acceleration, and proportional integral derivative-tilted integral derivative, respectively. Various scenarios involving fluctuations in load (step, multi-step, and random), solar radiation changes, and system parameter modifications are used to demonstrate the controller's effectiveness in handling disturbances. The simulation results, presented using MATLAB/SIMULINK, show that the proposed controller outperforms other existing controllers in terms of its dynamic response to system disturbances, namely it achieved a substantial reduction in frequency overshoot (94.66%, 48.49%, 68.75%), undershoot (94.66%, 26.75%, 67.25%), and settling time (78.57%, 90.81%, 75.0%) as measured by the frequency deviation in Area 1, respectively. Similar improvements were observed in frequency deviation in Area 2 and deviation in power exchange between system areas.

This work addresses the important issue of frequency stability in shipboard microgrids (SMGs), which are confronted with difficulties because of the alternating power insertion from green sources and low system inertia. In order to sustain a consistent frequency (despite system uncertainties), a study and precisely calibrated regulator is necessary. Therefore, this article proposed a new combined three degree of freedom proportional integral derivative (3DOF-PID) and tilted-integral (TI) regulators for achieving enhanced system performance, robustness, and enhance the frequency performance of a power grid. The superior performance of the suggested 3DOF-PID-TI has been assured by comparing it with three distinct controller architectures (FOPID, PDPID2 and 2DOF-PID) for the multi-energy SMG system. The investigation also took into account the temporal delays brought on by the communication links between the sensor and the regulator. The triangulation topology aggregation optimizer (TTAO), a relatively new meta-heuristic technique that hasn’t been employed to load frequency control (LFC) issues until recently, was employed to adjust the controllers’ parameters. The TTAO’s frequency performance outcomes were thoroughly contrasted to those of other optimization algorithms (i.e., Chimp, Whale, and Gradient-Based Optimization Algorithms) so as to evaluate the optimization efficacy of the suggested optimizer. The findings showed that the proposed 3DOF-PID-TI controller, whose parameters has been tuned by TTAO, outperformed its competitors in terms of overshoot (15.87mHz), undershoot (-29.04mHz), settling time (2.49sec) and performance index (i.e., ITAE(0.0171)). Additionally, the suggested controller’s robustness was assessed in a range of SMG operating situations as ex. (Random Multi-Step Variation in Load, Real Data on Stochastic Power Fluctuations, Energy Storage System Impact on the system and sensitivity analysis). The acquired data amply proved that when crucial system parameters experience a substantial variation, the controller’s gains set under normal circumstances do not need to be re-tuned.

Large-scale energy storage systems (ESSs) that can react quickly to energy fluctuations and store excess energy are required to increase the reliability of electricity grids that rely heavily on renewable energy sources (RESs). Hybrid systems, which combine different energy storage technologies such as batteries and supercapacitors, are becoming increasingly popular because no single technology can satisfy all requirements. In this study, a supercapacitor is used to stabilize quickly shifting bursts of power, while a battery is used to stabilize gradually fluctuating power flow. This paper proposes a robust controller for managing the direct current (DC) bus voltage to optimize the performance of ESS. The proposed controller combines a fractional-order proportional integral (FOPI) with a classical PI controller for the first time in the DC microgrid area. The hybrid (FOPI-PI) controller achieves an outstanding and superior performance in all transient and dynamic response specifications compared to other traditional controllers. The parameters of the suggested controller are incorporated with the self-adaptive bonobo optimizer (SaBO) to determine the optimal values. Furthermore, various optimization techniques are applied to the model and the SaBO’s output outperforms other techniques by minimizing the best objective function. In addition, the current study has utilized a novel power management strategy that includes two closed current loops for both batteries and supercapacitors. By using this method, batteries’ lifespans may be increased while still retaining optimal system performance. The suggested controller is implemented in MATLAB/Simulink 2022b, and the outcomes are reported for several case studies. The findings demonstrate that the control technique remarkably improves the transient response, such as transient duration, overshoot/undershoot, and the settling time. The proposed controller (FOPI-PI) with the SaBO optimizer is effective in maintaining the DC bus voltage under load and solar system variation.

The most recent advancements in renewable energy resources, as well as their broad acceptance in power sectors, have created substantial operational, security, and management concerns. As a result of the continual decrease in power system inertia, it is critical to maintain the normal operating frequency and reduce tie-line power changes. The preceding issues sparked this research, which proposes the Fuzzy Tilted Fractional Order Integral Derivative with Fractional Filter (FTFOIDFF), a unique load frequency controller. The FTFOIDFF controller described here combines the benefits of tilt, fuzzy logic, FOPID, and fractional filter controllers. Furthermore, the prairie dog optimizer (PDO), a newly developed metaheuristic optimization approach, is shown to efficiently tune the suggested controller settings as well as the forms of the fuzzy logic membership functions in the two-area hybrid power grid investigated in this paper. When the PDO results are compared to those of the Seagull Optimization Algorithm, the Runge Kutta optimizer, and the Chaos Game Optimizer for the same hybrid power system, PDO prevails. The system model incorporates physical constraints such as communication time delays and generation rate constraints. In addition, a unified power flow controller (UPFC) is put in the tie-line, and SMES units have been planned in both regions. Furthermore, the contribution of electric vehicles (EVs) is considered in both sections. The proposed PDO-based FTFOIDFF controller outperformed many PDO-based traditional (such as proportional integral derivative (PID), proportional integral derivative acceleration (PIDA), and TFOIDFF) and intelligent (such as Fuzzy PID and Fuzzy PIDA) controllers from the literature. The suggested PDO-based FTFOIDFF controller has excellent performance due to the usage of various load patterns such as step load perturbation, multi-step load perturbation, random load perturbation, random sinusoidal load perturbation, and pulse load perturbation. Furthermore, a variety of scenarios have been implemented to demonstrate the advantageous effects that SMES, UPFC, and EV units have on the overall performance of the system. The sensitivity of a system is ascertained by modifying its parameters from their standard configurations. According to the simulation results, the suggested PDO-based FTFOIDFF controller can improve system stability despite the multiple difficult conditions indicated previously. According to the MATLAB/Simulink data, the proposed method decreased the total fitness function to 0.0875, representing a 97.35% improvement over PID, 95.84% improvement over PIDA, 92.45% improvement over TFOIDFF, 83.43% improvement over Fuzzy PID, and 37.9% improvement over Fuzzy PIDA.

In this article, the problem of voltage and frequency stability in a hybrid multi-area power system including renewable energy sources (RES) and electric vehicles has been investigated. Fractional order systems have been used to design innovative controllers for both load frequency control (LFC) and automatic voltage regulator (AVR) based on the combination of fractional order proportional-integral and proportional-integral-derivative plus double derivative (FOPI–PIDD²). Here, the dandelion optimizer (DO) algorithm is used to optimize the proposed FOPI–PIDD² controller to stabilize the voltage and frequency of the system. Finally, the results of simulations performed on MATLAB/Simulink show fast, stable, and robust performance based on sensitivity analysis, as well as the superiority of the proposed optimal control strategy in damping frequency fluctuations and active power, exchanged between areas when faced with step changes in load, the changes in the generation rate of units, and the uncertainties caused by the wide changes of dynamic values.

This work presents a novel controller, the Proportional Integral Derivative-Second Derivative with a Proportional Derivative (PIDD2-PD), to enhance the frequency responsiveness of a multi-area interconnected power system with many connected generating units. Wild Horse optimizer (WHO), a contemporary metaheuristic optimization technique, is used to optimize the optimal gains of the provided controller. The focus of the investigation is a dual region interconnected hybrid power system with diverse conventional and renewable producing plants. Consideration is given to the physical restrictions of the speed turbines and governors. We analyse the efficacy of the suggested WHO-based PIDD2-PD controller by comparing its performance to that of other controllers described in the scientific literature (cascaded PID-TID, ID-T controller). In this study, many and diverse scenarios are utilized to assess the robustness of the proposed controller against random load disturbances, renewable energy source penetration, and system parameter modification. The findings demonstrate that the recommended controller outperforms alternative structural controllers in terms of settling time, maximum overshoot, and undershoot values for the system’s dynamic response. The outcomes are supplied as MATLAB/SIMULINK time-domain simulations.