Yazar "Celik, Emre" seçeneğine göre listele
Listeleniyor 1 - 20 / 32
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe (1+PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems(Springer London Ltd, 2021) Celik, Emre; Ozturk, Nihat; Arya, Yogendra; Ocak, CemilIn our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation.Öğe AGC performance amelioration in multi-area interconnected thermal and thermal-hydro-gas power systems using a novel controller(Elsevier - Division Reed Elsevier India Pvt Ltd, 2021) Arya, Yogendra; Dahiya, Pankaj; Celik, Emre; Sharma, Gulshan; Gozde, Haluk; Nasiruddin, IbraheemDue to varying structure, random load demands, nonlinearities, parameters ambiguity, steadily escalating size and intricacy of the interconnected power system (IPS), automatic generation control (AGC) is treated as one of the biggest crucial issues in IPS. Hence, expert, intelligent and robust control scheme is indispensable for stable operation of IPS and supply of electricity under sudden load demand disturbances. In vision of this, in this work, a novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS. Imperialist competitive algorithm is prolifically utilized for optimizing the controller parameters. Initially, a two area non-reheat thermal IPS is studied in detail and next to attest the efficacy of the technique, the study is extended to realistic two-area multi-source thermal-hydro-gas and reheat thermal three-area systems. The prominent benefit of cascade FPIDN-FOPIDN strategy comprises its great lethargy to large load demands and its supremacy over various latest intelligent classical/fuzzy controllers. The control strategy beats several techniques concerning significant lesser settling time, oscillations, over/under shoots and different performance index values. Finally, a robustness investigation is performed in order to validate the robustness of the controller. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.Öğe Application of Monte Carlo simulation and stochastic fractional search algorithm for solar PV placement considering diverse solar radiations(Elsevier, 2025) Barutcu, Ibrahim Cagri; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, EmreThis study employs Monte Carlo Simulation (MCS) within the structure of the Stochastic Fractional Search Algorithm (SFSA) to address circumstances involving uncertainty. The goal is to improve the system's performance by creating probability distribution functions for bus voltages and branch currents. We will use the resultant distribution in chance-constrained stochastic scheduling. The objective of the present research is to analyze the impact of uncertainties in the operation of photovoltaic (PV) systems, specifically in relation to different solar radiation conditions, on the amount of power loss. The approach focuses on including stochastic constraints in distribution systems instead of depending solely on precise deterministic boundaries. The goal is to enhance efficiency and ensure optimal consumption of power. This research enhances the knowledge base on PV unit positioning in distribution systems by integrating meta-heuristic optimization and MCS into a comprehensive framework. The investigation centers on the implementation of a chance-constrained method. We evaluate the optimization results using MCS under various uncertainty scenarios to demonstrate the effectiveness of the recommended approach. Furthermore, we conduct an analysis to assess the likelihood of exceeding the system's boundaries. The strategy's effectiveness is assessed by comparing the results of the SFSA with the Firefly algorithm (FA) utilizing probabilistic evaluation and simulation.Öğe Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization(Nature Portfolio, 2024) Tejani, Ghanshyam G.; Mashru, Nikunj; Patel, Pinank; Sharma, Sunil Kumar; Celik, EmreThe study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. The optimization aims to minimize both mass and compliance simultaneously. MOCS2arc is an advanced version of the traditional Multi-Objective Cuckoo Search (MOCS) algorithm, enhanced through a dual archive strategy that significantly improves solution diversity and optimization performance. To evaluate the effectiveness of MOCS2arc, we conducted extensive comparisons with several established multi-objective optimization algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, and MOCS. Such a comparison has been made with various performance metrics to compare and benchmark the efficacy of the proposed algorithm. These metrics comprehensively assess the algorithms' abilities to generate diverse and optimal solutions. The statistical results demonstrate the superior performance of MOCS2arc, evidenced by enhanced diversity and optimal solutions. Additionally, Friedman's test & Wilcoxon's test corroborate the finding that MOCS2arc consistently delivers superior optimization results compared to others. The results show that MOCS2arc is a highly effective improved algorithm for multi-objective truss structure optimization, offering significant and promising improvements over existing methods.Öğe Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references(Springer, 2021) Celik, Emre; Ozturk, NihatAlthough direct phase current control of brushless DC motor prevents commutation current ripple at low speed, it occurs at high speed which has not received the deserved attention in the literature. Dealing with this current ripple is of practical significance because commutation becomes more influential for high speeds as its duration and the current ripple's amplitude increase with speed. This paper concerns with the successful application of a fuzzy logic estimator (FLE) as an expert control technique to minimize the so-called current ripple profitably. Phase current reference waveforms are programmed as a function of commanded current, angular position, and commutation angle which is adjusted online by the developed FLE as per the motor working condition. The presented approach renders the current references with changing but equal slopes during commutation to keep the other phase current constant at all times. A genetic algorithm is also deployed to optimize the FLE's rule table. Unlike the reported researches, this study does not require calculating commutation time, and use of torque observer and/or commutation detection circuits. The acceptability of our proposal is widely illustrated by simulated and experimental results using DSP TMS320F28335, which signifies that prolific performance toward commutation current ripple minimization is achieved.Öğe Design of new fractional order PI-fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems(Springer, 2021) Celik, EmreOwing to integrating the dense range of distinct electric power sources, high volume of power generation units, abrupt and continuous changes in load demand, and rising utilization of power electronics, the electric power system (EPS) is striving for high-performance control schemes to counterwork the concerns depicted above. Additionally, it is highly creditable to have the controller structure as simple as possible from a viewpoint of practical implementation. Thus, this paper describes a virgin application of fractional order proportional integral-fractional order proportional derivative (FOPI-FOPD) cascade controller for load frequency control (LFC) of electric power generating systems. The proposed controller includes fractional order PI and fractional order PD controllers connected in cascade wherein orders of integrator (lambda) and differentiator (mu) may be fractional. The gains and fractional order parameters of the controller are concurrently tuned using recently proposed dragonfly search algorithm (DSA) by minimizing the integral time absolute error (ITAE) of frequency and tie-line power deviations. DSA is the mathematical model and computer simulation of static and dynamic swarming behaviors of dragonflies in nature, and its implementation in LFC studies is very rare, unveiling additional research gap to be bridged. Performance of the advocated approach is first explored on popular two-area thermal PS with/without governor dead band (GDB) nonlinearity and then on three-area hydrothermal PS with suitable generation rate constraints. To highlight the prominence and universality of our proposal, the work is extended to single-/multi-area multi-source EPSs. Several comparisons with DSA optimized FOPID controller and the relevant recent works for each test system indicate the contribution of proposed DSA optimized FOPI-FOPD cascade controller in alleviating settling time/undershoot/overshoot of frequency and tie-line power oscillations.Öğe Dynamic load frequency control in Power systems using a hybrid simulated annealing based Quadratic Interpolation Optimizer(Nature Portfolio, 2024) Izci, Davut; Ekinci, Serdar; Celik, Emre; Bajaj, Mohit; Blazek, Vojtech; Prokop, LukasEnsuring the stability and reliability of modern power systems is increasingly challenging due to the growing integration of renewable energy sources and the dynamic nature of load demands. Traditional proportional-integral-derivative (PID) controllers, while widely used, often fall short in effectively managing these complexities. This paper introduces a novel approach to load frequency control (LFC) by proposing a filtered PID (PID-F) controller optimized through a hybrid simulated annealing based quadratic interpolation optimizer (hSA-QIO). The hSA-QIO uniquely combines the local search capabilities of simulated annealing (SA) with the global optimization strengths of the quadratic interpolation optimizer (QIO), providing a robust and efficient solution for LFC challenges. The key contributions of this study include the development and application of the hSA-QIO, which significantly enhances the performance of the PID-F controller. The proposed hSA-QIO was evaluated on unimodal, multimodal, and low-dimensional benchmark functions, to demonstrate its robustness and effectiveness across diverse optimization scenarios. The results showed significant improvements in solution quality compared to the original QIO, with lower objective function values and faster convergence. Applied to a two-area interconnected power system with hybrid photovoltaic-thermal power generation, the hSA-QIO-tuned controller achieved a substantial reduction in the integral of time-weighted absolute error by 23.4%, from 1.1396 to 0.87412. Additionally, the controller reduced the settling time for frequency deviations in Area 1 by 9.9%, from 1.0574 s to 0.96191 s, and decreased the overshoot by 8.8%. In Area 2, the settling time was improved to 0.89209 s, with a reduction in overshoot by 4.8%. The controller also demonstrated superior tie-line power regulation, achieving immediate response with minimal overshoot.Öğe Effective speed control of brushless DC motor using cascade 1PDf-PI controller tuned by snake optimizer(Springer London Ltd, 2024) Celik, Emre; Karayel, MehmetThis paper introduces a cascade one proportional derivative incorporating filter (1PDf)-proportional integral (PI) controller abbreviated as c-1PDf-PI to deal effectively with the speed control issue of brushless DC (BLDC) motors. Two problems exist with implementing this controller such as iterated integral overflow and derivation-based chattering owing to the noise. The former is resolved by using an equivalent expression for the integral operation, while the latter is addressed by putting a first-order filter on the derivative term. To achieve the best performance from the controller, snake optimizer (SO) is fruitfully employed for optimizing the controller parameters without need for expert knowledge/interpretation. Here, a more reasonable cost function to assess the candidate solutions is also described. Simulations and laboratory experiments using DSP of TI TMS320F28335 are performed and the results are presented which show that the reference tracking performance, torque disturbance capability and robustness of the c-1PDf-PI controller have potential. These results are also contrasted by those offered by PI and 1PDf speed control schemes individually, affirming the superior performance of our proposal. As per the results, discussion and observation of this research, we stress that good performance and simplicity are salient advantages of the c-1PDf-PI controller, rendering it a good alternative over the complicated controller designs.Öğe Enhanced automatic voltage regulation using an extended PIDA controller optimised by the snake algorithm(Elsevier, 2025) Chetty, Nelson Dhanpal; Gandhi, Ravi; Sharma, Gulshan; Celik, Emre; Kumar, RajeshMaintaining voltage stability within acceptable limits is crucial in power systems, with Automatic Voltage Regulation (AVR) ensuring consistent performance. Traditionally, PID controllers have been widely used; however, they struggle in complex, nonlinear environments with fluctuating conditions and disturbances. This study proposes an Extended PID-Acceleration (ePIDA) controller incorporating a novel state observer-based Disturbance Observer (DOB) for enhanced voltage regulation. The Snake Optimiser (SO) is introduced for the first time in AVR tuning, leveraging its dynamic leader-follower mechanism to achieve faster convergence and optimal controller gains. The SO-ePIDA framework extends the traditional PIDA structure with a three-degree-offreedom (3DOF) approach, enhancing setpoint tracking and disturbance rejection. The proposed approach is evaluated against six widely used optimisation strategies through comparative statistical and graphical analyses, considering step-load variations and system parameter settings. Results demonstrate that the SO-ePIDA controller achieves a rise time of 0.1679 s, a settling time of 0.3123 s, and the lowest ISTAE value of 0.0046, ensuring superior transient response and steady-state accuracy. Furthermore, under a 30 % step-load disturbance, the proposed controller exhibits the fastest recovery time of 0.1065 s, significantly outperforming other methods. The AVR system was tested with +25 % and +50 % variations in system parameters to assess robustness under parametric uncertainty. The results confirm that the SO-ePIDA controller maintains stability, with rise time deviations limited to 0.1577 and 0.2004 s and ISTAE variations between 0.0116 and 0.1891, demonstrating strong adaptability under extreme operating conditions. These findings establish the SO-ePIDA framework as a robust, high-performance solution for real-world AVR applications.Öğe An enhanced sea-horse optimizer for solving global problems and cluster head selection in wireless sensor networks(Springer, 2024) Houssein, Essam H.; Saad, Mohammed R.; Celik, Emre; Hu, Gang; Ali, Abdelmgeid A.; Shaban, HassanAn efficient variant of the recent sea horse optimizer (SHO) called SHO-OBL is presented, which incorporates the opposition-based learning (OBL) approach into the predation behavior of SHO and uses the greedy selection (GS) technique at the end of each optimization cycle. This enhancement was created to avoid being trapped by local optima and to improve the quality and variety of solutions obtained. However, the SHO can occasionally be vulnerable to stagnation in local optima, which is a problem of concern given the low diversity of sea horses. In this paper, an SHO-OBL is suggested for the tackling of genuine and global optimization systems. To investigate the validity of the suggested SHO-OBL, it is compared with nine robust optimizers, including differential evolution (DE), grey wolf optimizer (GWO), moth-flame optimization algorithm (MFO), sine cosine algorithm (SCA), fitness dependent optimizer (FDO), Harris hawks optimization (HHO), chimp optimization algorithm (ChOA), Fox optimizer (FOX), and the basic SHO in ten unconstrained test routines belonging to the IEEE congress on evolutionary computation 2020 (CEC'20). Furthermore, three different design engineering issues, including the welded beam, the tension/compression spring, and the pressure vessel, are solved using the proposed SHO-OBL to test its applicability. In addition, one of the most successful approaches to data transmission in a wireless sensor network that uses little energy is clustering. In this paper, SHO-OBL is suggested to assist in the process of choosing the optimal power-aware cluster heads based on a predefined objective function that takes into account the residual power of the node, as well as the sum of the powers of surrounding nodes. Similarly, the performance of SHO-OBL is compared to that of its competitors. Thorough simulations demonstrate that the suggested SHO-OBL algorithm outperforms in terms of residual power, network lifespan, and extended stability duration.Öğe Enhancing automatic generation control in renewable energy-integrated thermal power systems with a novel PID+Iλ controller tuned by INFO algorithm(Sage Publications Ltd, 2025) Can, Ozay; Ayas, Mustafa Sinasi; Celik, EmreElectrical systems need to balance generation and demand to ensure that customers are supplied with safe and high-quality electricity. Failure to maintain this balance may result in unwanted frequency oscillation and, accordingly, tie-line power variation. Automatic generation control (AGC) is an important mechanism for controlling system responses and keeping them within predetermined bounds. Integrating renewable energy sources (RESs) into the grid can be complicated due to their erratic and weather-dependent nature, leading to imbalances in generation and consumption. To reduce these disparities, this study focuses on developing a novel proportional-integral-derivative (PID)+I-lambda controller for the AGC in a two-area thermal power system utilizing wind turbines and photovoltaic (PV) panels as renewables. For achieving the best possible performance, the controller parameters are optimized using the weighted mean of vectors (INFO) algorithm. Simulation studies are conducted to evaluate the performance of the proposed controller under different load demands and RES scenarios. Comparative studies are also conducted to evaluate the true efficacy of the INFO-tuned PID+I-lambda controller against some published control schemes available in the literature. It is found that our proposal outperforms its rivals in mitigating the unwanted system oscillations, lessening the overshoot/undershoot, and shortening the settling time of frequency and tie-line power responses.Öğe Frequency and voltage stability improvement in a two-area thermal power system using a novel controller and RIME optimizer(Pergamon-Elsevier Science Ltd, 2025) Can, Ozay; Ayas, Mustafa Sinasi; Celik, EmreThis work presents a novel method for integrating the Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) processes to enhance frequency and voltage stability in two-area non-reheat thermal power systems. In this study, we present a novel Proportional Derivative-(1+Double Integral) (PD-(1+II)) controller, which is optimized through the utilization of the recently created Rime Optimization Algorithm (RIME). This represents the first time that the RIME algorithm and the PD-(1+II) controller are used in the context of coupled LFC-AVR systems. Our comprehensive research encompasses six distinct scenarios, including AVR system tuning, LFC system tuning, combined LFC-AVR system tuning, disturbance analysis, nonlinearity analysis, and parameter sensitivity analysis. A comparative analysis is conducted between the proposed RIME-tuned PD-(1+II) controller and established techniques such as the Nonlinear Threshold Accepting (NLTA) algorithm and its multi-objective version (MONLTA) tuned PID controllers, i.e. MONLTA-PID and NLTA-PID controllers. The simulation results demonstrate that the RIME-tuned PD-(1+II) controller consistently outperforms existing techniques. It exhibits superior performance in terms of overshoot reduction (100 % decrease in frequency deviation and 30 % decrease in terminal voltage) and faster settling times (50 % decrease in frequency control and 30 % decrease in voltage control) when compared to current methods. Furthermore, the controller demonstrates resilience in the presence of a diverse range of disturbances, nonlinearities, and parameter variations, highlighting its adaptability and reliability in a multitude of operational scenarios. The efficacy and reliability of the proposed methodology are further substantiated by statistical analysis, which demonstrates that it outperforms existing optimization algorithms, including the Gorilla Troops Optimizer (GTO) and the Whale Optimization Algorithm (WOA), with the RIME algorithm achieving an average ITSE value of 0.0881 compared to 0.1023 for GTO and 0.1057 for WOA.Öğe Frequency regulation in solar PV-powered thermal power system using FPA-PID controller through UPFC and RFB(Springer, 2024) Masikana, S. B.; Sharma, Gulshan; Sharma, Sachin; Celik, EmreThe integration of additional renewable energy sources, such as solar PV, into the current power grid is a global priority due to the depletion of traditional supplies and rising power demand. In order to achieve load frequency control (LFC) of the power system with integration of solar PV, this study employs the construction of a proportional integral derivative (PID) scheme that has been fine-tuned via the flower pollination algorithm (FPA). When evaluating the performance of FPA-PID on an interconnected thermal power system, three distinct error values-integral time absolute error (ITAE), integral time multiplied by square error (ITSE), and integral of absolute error (IAE)-are taken into consideration. The results are compared with those of genetic algorithm, particle swarm optimization, and hybrid bacteria foraging optimization based PID. It can be observed that the error values achieved with FPA-PID are substantially lower than those obtained with other PID designs, which are ITSE of 2.07e-05, ITAE of 0.01839, and IAE of 0.008889. Furthermore, the PV integration has further decreased the ITSE to 7.872e-06, the ITAE to 0.008953, and the IAE to 0.005376. All error levels have been further reduced because of the integration of unified power flow control (UPFC) in series with the tie-line and redox flow battery (RFB) separately, utilizing the FPA-PID scheme with solar PV. Finally, it is seen that FPA-PID with solar PV and with UPFC outperforms other LFC designs. The graphical LFC plots verify that FPA-PID with solar PV and with UPFC has capability to reduce the frequency, tie-line power, and area control error excursions in comparison to other LFC designs.Öğe Frequency Support Studies of a Diesel-Wind Generation System Using Snake Optimizer-Oriented PID with UC and RFB(Mdpi, 2023) Rameshar, Vikash; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, EmreThe present paper discusses the modeling and analysis of a diesel-wind generating system capable enough to cater to the electrical power requirements of a small consumer group or society. Due to high variations of the load demand or due to changes in the wind speed, the frequency of the diesel-wind system will be highly disturbed, and hence to regulate the frequency and power deviations of the wind turbine system, an effective controller design is a necessary requirement, and therefore this paper proposes a novel controller design based on PID scheme. The parameters of this controller is effectively optimized through a new snake optimizer (SO) in an offline manner to minimize frequency and power deviations of an isolated diesel-wind system. The performance of SO-PID for the diesel-wind system is evaluated by considering the integral of time multiplied absolute error (ITAE), integral absolute error (IAE), and integral of time multiplied square error (ITSE). The results were calculated for a step change in load, step change in wind speed, load change at different instants of time with diverse magnitude, and for random load patterns, and they were compared with some of the recently published results under similar working conditions. In addition, the effect of an ultracapacitor (UC) and redox flow battery (RFB) on SO-PID was investigated for the considered system, and the application results demonstrated the advantages of our proposal over other studied designs.Öğe Frequency Support Studies of a Microgrid Having DG-WTG Using ANFIS and with the Application of HAE-FC and RFB(Taylor & Francis Inc, 2023) Rameshar, Vikash; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, Emre; Öztürk, NihatThe micro-grid (mu-grid) has picked up momentum worldwide with the ability to supply cost-effective, clean, and reliable electrical power to the present-day demand. The practical mu-grids are comprised of non-conventional and conventional sources such as wind turbine generators (WTG) and diesel generators (DG). Due to the encouragement of wind power which is exceedingly sporadic in nature and thus the frequency of the mu-grid is exceedingly vulnerable due to the erratic nature of wind speed. Variations in the load demand have also added to the vulnerability of the mu-grid at distinctive moments of time. Consequently, this paper appears to be a novel plan that utilizes artificial neuro-fuzzy inference system (ANFIS) within the built frequency regulation of the mu-grid. The proposed research has been employed within the mu-grid, and the application outcomes have taken all possibilities, such as load variety at the distinctive moment of time, modification of the load demand on the mu-grid, and step alteration of the wind input. The achieved results are coordinated with a few of the most recent results, which presents the ANFIS ahead over other strategies. Although there is a probable scope for improvement which subsequently involves the fuel cell (FC) with a hydrogen aqua electrolyzer (HAE) unit, as well as a redox flow battery (RFB), that is introduced one at a time in the mu-grid and the results of mu-grid are calculated for various working conditions to show the impact that the ANFIS technology has upon storage devices with regards to the mu-grid architecture.Öğe An improved honey badger algorithm for global optimization and multilevel thresholding segmentation: real case with brain tumor images(Springer, 2024) Houssein, Essam H.; Emam, Marwa M.; Singh, Narinder; Samee, Nagwan Abdel; Alabdulhafith, Maali; Celik, EmreGlobal optimization and biomedical image segmentation are crucial in diverse scientific and medical fields. The Honey Badger Algorithm (HBA) is a newly developed metaheuristic that draws inspiration from the foraging behavior of honey badgers. Similar to other metaheuristic algorithms, HBA encounters difficulties associated with exploitation, being trapped in local optima, and the pace at which it converges. This study aims to improve the performance of the original HBA by implementing the Enhanced Solution Quality (ESQ) method. This strategy helps to prevent becoming stuck in local optima and speeds up the convergence process. We conducted an assessment of the enhanced algorithm, mHBA, by utilizing a comprehensive collection of benchmark functions from IEEE CEC'2020. In this evaluation, we compared mHBA with well-established metaheuristic algorithms. mHBA demonstrates exceptional performance, as shown by both qualitative and quantitative assessments. Our study not only focuses on global optimization but also investigates the field of biomedical image segmentation, which is a crucial process in numerous applications involving digital image analysis and comprehension. We specifically focus on the problem of multi-level thresholding (MT) for medical image segmentation, which is a difficult process that becomes more challenging as the number of thresholds needed increases. In order to tackle this issue, we suggest a revised edition of the standard HBA, known as mHBA, which utilizes the ESQ approach. We utilized this methodology for the segmentation of Magnetic Resonance Images (MRI). The evaluation of mHBA utilizes existing metrics to gauge the quality and performance of its segmentation. This evaluation showcases the resilience of mHBA in comparison to many established optimization algorithms, emphasizing the effectiveness of the suggested technique.Öğe Improved stochastic fractal search algorithm and modified cost function for automatic generation control of interconnected electric power systems(Pergamon-Elsevier Science Ltd, 2020) Celik, Emrey An improved stochastic fractal search algorithm (ISFS) and a modified cost function are proposed in this paper to skillfully handle the issue of automatic generation control (AGC) of power systems. Most employed power system models namely two-area non-reheat thermal power system with and without governor dead band nonlinearity, and three-area hydro-thermal power plant with generation rate constraints are considered to be controlled by a PID controller. Then the gains of this controller are optimized with SFS and ISFS individually by minimizing the value of cost function proposed. This function consists in minimizing the integral time absolute error (ITAE) and also the time rates of frequency and tie-line power deviations. After recognizing the supremacy of SFS tuned PID controller over some existing methods in improving settling time and oscillations of frequency and tie-line power deviations, ISFS tuned PID controller is shown to promote the system performance further to compete with some other control schemes of higher degree and complexity available in the literature. This outcome has unveiled the superior tuning ability of ISFS over the original version of SFS. Also, convergence curves of the algorithms are analyzed from which it is observed that the speed of convergence for ISFS is remarkable.Öğe Improving speed control characteristics of PMDC motor drives using nonlinear PI control(Springer London Ltd, 2024) Celik, Emre; Bal, Gungor; Ozturk, Nihat; Bekiroglu, Erdal; Houssein, Essam H.; Ocak, Cemil; Sharma, GulshanThis paper introduces a nonlinear PI controller for improved speed regulation in permanent magnet direct current (PMDC) motor drive systems. The nonlinearity comes from the exponential (Exp) block placed in front of the classical PI controller, which uses a tunable exponential function to map the speed error nonlinearly. Such a configuration has not been studied till now, thus meriting further investigation. We consider an exponential PI (EXP-PI) controller and to attain the best performance from this controller, its parameters are optimized offline using salp swarm algorithm (SSA), which borrows its inspiration from the way of forage and navigation of salps living in deep oceans. To indicate the credibility of SSA tuned EXP-PI controller convincingly, numerous experiments on speed regulation in PMDC motor have been implemented using DSP of TMS320F28335. The results obtained are also compared to similar results in the literature. It is shown that the proposed approach performs well in practice by ensuring tight tracking of the speed reference and superb torque disturbance rejection for the closed loop control. Furthermore, superior performance is achieved by the proposed nonlinear PI controller with respect to a fixed-gain PI controller.Öğe Investigating the Effectiveness of Wind Turbine and Salp Swarm Optimization in Alleviating Transmission Congestion of Power System(Taylor & Francis Inc, 2024) Gautam, Anurag; Nasiruddin, Ibraheem; Sharma, Gulshan; Ahmer, Mohammad F.; Celik, Emre; Bekiroglu, ErdalThe current power system grapples with congestion challenges arising from technological advancements and deregulation. Conversely, renewable energy sources like wind offer an inexhaustible, cost-effective, and environmentally friendly solution, potentially alleviating congestion in the modern transmission network by reducing the need for conventional generators to reschedule. This article conducts a thorough analysis of how the penetration of wind power impacts congestion costs in conventional energy systems. To address this, a novel approach utilizing the bus sensitivity factor is introduced for precise wind turbine placement. To efficiently mitigate congestion costs, a pioneering Salp Swarm Optimization Algorithm is proposed and validated on a modified IEEE 30 Bus system, demonstrating superior performance compared to other algorithms. The findings underscore the effectiveness of the proposed algorithm and highlight wind turbines, coupled with generator rescheduling, as a potent and cost-effective solution for alleviating transmission network congestion.Öğe Load Frequency Control of Hydro-Hydro Power System using Fuzzy-PSO-PID with Application of UC and RFB(Taylor & Francis Inc, 2023) Joshi, Milan; Sharma, Gulshan; Celik, EmreLoad frequency control (LFC) plays a crucial rule in matching the power generation with variable power demand, and hence, maintains the system frequency and tie-line power to its esteemed value. Further, most of the countries are dependent on thermal power plants to meet the electrical energy requirement, and hence, LFC strategies are available for these types of power plants only. As the world is moving to generate electrical energy via cleaner sources to reduce harmful environmental pollutants, and hence, hydro power are one of the well-developed and cleanest sources of electrical energy. Subsequently, this article shows up a novel LFC design for hydro-hydro system based on joint endeavors of fuzzy logic with PID viably optimized through particle swarm optimization (PSO) coming into a new and robust Fuzzy-PSO-PID for LFC. At to beginning with, the result of Fuzzy-PSO-PID is evaluated for step load alteration, and the outcomes of Fuzzy-PSO-PID are matched with recently published outcomes of LFC with regards to values of PID, error minimization, and graphical results. In any case, still, there may be a scope of LFC upgrade in Fuzzy-PSO-PID due to higher responding time of turbines used in hydro-hydro plants and subsequently, the combinations of storage devices such as ultra-capacitor (UC) in each zone and UC with redox flow battery combination are used to improve the LFC and the application outcomes are analyzed again and uncover considering the step load alteration, non-linearity, load pattern, and parametric modification to see the benefits of the proposed work for hydro-hydro LFC.
