This paper proposes a novel robust power system stabilizer (PSS), based on hybridization of fractional order PID controller (PIλDμ) and PSS for optimal stabilizer (FOPID-PSS) for the first time, ...using a new metaheuristic optimization Bat algorithm (BA) inspired by the echolocation behavior to improve power system stability. The problem of FOPID-PSS design is transformed as an optimization problem based on performance indices (PI), including Integral Absolute Error (IAE), Integral Squared Error (ISE), Integral of the Time-Weighted Absolute Error (ITAE) and Integral of Time multiplied by the Squared Error (ITSE), where, BA is employed to obtain the optimal stabilizer parameters. In order to examine the robustness of FOPID-PSS, it has been tested on a Single Machine Infinite Bus (SMIB) power system under different disturbances and operating conditions. The performance of the system with FOPID-PSS controller is compared with a PID-PSS and PSS. Further, the simulation results obtained with the proposed BA based FOPID-PSS are compared with those obtained with FireFly algorithm (FFA) based FOPID-PSS. Simulation results show the effectiveness of BA for FOPID-PSS design, and superior robust performance for enhancement power system stability compared to other with different cases.
The power quality and protection enhancement of wind turbine becomes an important paramount. This requires a competitive controller with high performances. For this purpose, the paper presents a ...novel hybrid controller named fractional fuzzy PID (FFPID) strategy tunning with an efficient metaheuristic optimization bat algorithm (BA) for controlling the wind turbine equipped with permanent magnet synchronous generator (WT-PMSG). The main control objectives are to drive WT-PMSG for extracting the maximum power point (MPPT) in the low range of weather conditions and further to protect the wind turbine in high-wind region using pitch angle control. The performance of proposed strategy is analysed for all regions low–high wind speed disturbances. The obtained results are obviously proved that the optimal hybrid fractional-order fuzzy PID controller is highly better than the optimal classical PID, fuzzy PID (FPID) and fractional-order PID (FOPID) controllers in terms of response, overshoot and indices performances. Further, the WT-PMSG is effectively controlled at different conditions of wind velocities by the proposed scheme.
Abstract Power systems exhibit nonlinearity. causing dynamic instability and complex power oscillations. This research proposes an innovative strategy using the Novel Bat Algorithm (NBA) to achieve ...ideal Power System Stabilizers (PSSs) in a multimachine power system. The approach shifts electromechanical modes to specific areas in the s-plane. Enhancing the multi-machine power system and establishing stabilizer parameters for dynamic performance. The study examines the designed approach aptitude for standard lead-lag PSSs configurations. In order to elevate the global search problem and transfer some static operators for the optimum optimization process. the chaos mapping. also known as CNBA. is introduced into NBA. Four different forms of chaos maps are compared in experiments to resolve unconstrained mathematical issues in order to illustrate CNBA performance. In any other case. the challenge of designing PSS under a wide range of loading situations is transformed into an optimization challenge with the damping ratio of electromechanical modes with low damping as the target function. The optimal stabilizers’ gains are gotten by employing the CNBA algorithm. Second plan. an effective technique is astutely established to delineate the PSS location and quantity using CNBA and another side using participation factor. To examine the efficacy of the proposed CNBA-based PSS on a large system; it is tested on the interconnected of New-England/New-York (16 generators and 68 buses) power grid. and verified by comparative study with NBA through eigenvalue analysis and nonlinear simulation to provide evidence the algorithmic competence of CNBA. The CNBA approach yields a minimum damping ratio of 37%. which is consistent with the its eigenvalue. In contrast, the NBA approach achieves a minimum damping ratio of 31%. The simulation results reveal the fine performance of the proposed CNBA-PSS in a convincing manner and its capacity to provide an excellent damping for inter-area and local oscillations under diverse operating cases compared to NBA-PSS then in the case of PSS location.
This paper proposes a controller to track the maximum power point (MPP) of a photovoltaic (PV) system using a fractional-order proportional integral derivative (FOPID) controller. The employed MPPT ...is operated based on a dp/dv feedback approach. The designed FOPID-MPPT method includes a differentiator of order (μ) and integrator of order (λ), meaning it is an extension of the conventional PID controller. FOPID has more flexibility and achieves dynamical tuning, which leads to an efficient control system. The contribution of our paper lies is optimizing FOPID-MPPT parameters using Aquila optimizer (AO). The obtained results with the proposed AO-based FOPID-MPPT are contrasted with those acquired with moth flame optimizer (MFO). The performance of our FOPID-MPPT controller with the conventional technique perturb and observe (P&O) and the classical PID controller is analyzed. In addition, a robustness test is used to assess the performance of the FOPID-MPPT controller under load variations, providing valuable insights into its practical applicability and robustness. The simulation results clearly prove the superiority and high performance of the proposed control system to track the MPP of PV systems.
An accurate and efficient control of the Maximum Power Point Tracking (MPPT) and pitch angle for the Wind Turbine (WT) system can provide more energy while also protecting the material. Thus, ...considering these economic aspects, many controllers are proposed to guarantees their performances. The most studied strategy is the classical PID controller. However, its performance is limited due to the nonlinear model and the difficult wind speed form, which inflict many uncertainties. To solve these drawbacks, an advanced controller named Type-2 Fractional Order Fuzzy PID (T2-FOPID) controller is suggested in this paper to improve the exigence controls. Meanwhile, an efficient optimization technique named the Salps Swarm Algorithm (SSA) has been introduced in order obtaining the best controller parameters. The efficiency of the proposed controller is tested to the 10 kW-WT under various wind speed scenarios. The derived results explicitly indicate that the proposed strategy outperforms the PID controller and other controllers, in terms. the minimum of error, the overshoot and the settling time.
•The pricipal controls of the wind turbine system are are the MPPT and the pitch angle.•The authers proposed the Type-2 Fractional order PID controller based on salps swarm algorithm.•The results proved the superiority of proposed controller than the classical PID controller and others are largely suggested in the literature .
In this study, the problem of optimal parameters in charge simulation method (CSM) is solved using the genetic algorithm (GA), particle swarm optimisation and differential evolution. The comparative ...study shows that the GA is more effective. A model based on a hybrid approach that combines CSM and the GA is proposed to calculate the electric field created by an overhead extra high voltage power line. The resulting field levels were compared with exposure values set by the ICNIRP and IRPA standards. The results show that these levels are less than the limit recommended by these standards. The simulation results of electric field intensity values are compared with those obtained from polarisation ellipse method. A good agreement has been reached.
•Integrating fractional-order chaos maps, with the Crayfish Optimizer is proposed.•Improved Crayfish Optimizer is applied to define PV’s models uncertain parameters.•Three different PV units are ...examined and tested under varied scenarios.•Some specific measures indicate the advantageous of the ICOA’s results compared to others.
The growing use of photovoltaic energy necessitates accurate modeling of modules, particularly in non-linear current–voltage characteristics, despite challenges in finding ideal circuit model parameters. Several meta-heuristic techniques have been developed to determine these parameters. This work presents a new method that combines the Crayfish Optimization Algorithm (COA) with fractional-order chaos maps (FC-maps), a recent development in the area. The goal of this addition is to adaptively adjust the COA settings. Moreover, the COA algorithm has been improved with the dimension learning-hunting (DLH) search scheme, inspired by crayfish hunting. This method establishes neighborhoods for each crayfish, enhancing local and global search efforts while preserving diversity. First, benchmark functions are used to conduct a thorough mathematical assessment of the improved COA (ICOA). Subsequently, the ICOA is combined with the Newton-Raphson numerical method to estimate PV parameters. Six cell and module types, including RTC France, Photowatt-PWP201, and STP6-120/36, are investigated using various PV models within the single-diode and double-diode models. The root mean squared error (RMSE) for RTC France, PWP201, and STP6-120/36 that our system employing (SDM, DDM) obtained is as follows, based on the experimental findings: (7.844017E-04, 7.520345E-04), (2.084019E-03, 2.067626E-03), and (1.441938E-02, 1.432568E-02), respectively. A statistical analysis between several well-established metaheuristic methods was conducted to showcase the superior performance of the ICOA. The results unequivocally exhibit that the ICOA excels in accurately estimating the best PV parameters when compared to the other techniques. In conclusion, ICOA surpasses alternative algorithms in terms of precision, consistency, and convergence.
In this present work, a new metaheuristic method called a Harris hawk optimizer (HHO) is applied to achieve the optimal design of a power system stabilizer (PSS) in a multimachine power system. ...Several well-known chaos maps are incorporated into the HHO to form a chaotic HHO (CHHO) with the aim of improving static operators and enhancing global searching. To assess the CHHO performance, exhaustive comparison studies are made between anticipated chaotic maps in handling unconstrained mathematical problems. At this moment, The PSS design problem over a wide permutation of loading conditions is formulated as a non-linear optimization problem. The adopted objective function defines the damping ratio of lightly damped electromechanical modes subject to a set of constraints. The best PSS parameters are generated by the proposed CHHO. The applicability of the proposed CHHO based on PSS is examined and demonstrated on a 10-generator and 39-bus multimachine power system model. The performance assessments of the CHHO results are realized by a comparative study with HHO through extensive simulations along with further eigenvalue analysis to prove its efficacy. The simulation results convincingly demonstrate the high performance of the proposed CHHO-PSS under various operating scenarios.
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