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Öğe AISI 2507 süper dubleks paslanmaz çeliğin tornalanmasında hibrit soğutma/yağlama tekniklerinin yüzey pürüzlülüğü ve kesme sıcaklığı üzerindeki etkisi(Düzce Üniversitesi, 2019) Çelik, Emre; Kıvak, TurgayBu çalışmada, AISI 2507 dubleks paslanmaz çeliğinin farklı soğutma/yağlama şartları altında tornalanmasında, kesme parametrelerinin kesme sıcaklığı ve yüzey pürüzlülüğü üzerindeki etkileri incelenmiştir. Deneyler üç farklı soğutma yağlama koşulu altında (MMY, Kriyo ve Kriyo+MMY), üç farklı kesme hızında (80,120 ve 160 m/dak) ve üç farklı ilerleme hızında (0,16-0,20 ve 0,24 mm/dev) gerçekleştirilmiştir. Tornalama deneylerinde PVD yöntemi ile TiCN kaplanmış karbür kesici takımlar (CNMG 120408 ML) kullanılmıştır. MMY sisteminde kesme yağı olarak bitkisel esaslı kesme yağı, kriyojenik soğutma sisteminde ise sıvı azot (LN2) kullanılmıştır. Deneyler Taguchi ortogonal dizilimli L27 deney tasarımına göre gerçekleştirilmiş olup deneyler sonucunda elde edilen verilerin değerlendirilmesinde sinyal gürültü oranları (S/N) kullanılmıştır. Faktörlerin etki seviyelerinin belirlenmesinde ise varyans analizi (ANOVA) uygulanmıştır. Ayrıca tahmin denklemlerinin oluşturulması amacıyla çoklu regresyon analizi yapılmıştır. Deneysel çalışma sonucunda en düşük yüzey pürüzlülük değeri Kriyo+MMY soğutma yağlama şartında, 160 m/dak kesme hızı ve 0,16 mm/dev ilerleme hızında elde edilmiştir. En düşük kesme sıcaklığı ise yine Kriyo+MMY soğutma yağlama koşulunda, 80 m/dak kesme hızı ve 0,16 mm/dev ilerleme hızında elde edilmiştir. MMY'nin üstün yağlama özelliği ile kriyojenik soğutmanın üstün soğutma özelliğinin kombine edilmesi yüzey kalitesinin (yüzey pürüzlülüğü ve topografyası) artması ve kesme sıcaklığının düşmesi üzerinde önemli bir etkiye sahip olduğu görülmüştür. ANOVA sonuçlarına göre yüzey pürüzlülüğü üzerinde %81,54 katkı oranı ile en etkili parametrenin ilerleme hızı olduğu kesme sıcaklığı üzerinde ise %91,30 katkı oranı ile en etkili parametrenin soğutma/yağlama yönteminin olduğu görülmüştür. Çoklu regresyon analizi sonucu elde edilen denklemlerin belirleme katsayıları yüzey pürüzlülüğü ve kesme sıcaklığı için sırasıyla 0,9551 ve 0,9875 olarak belirlenmiştir.Öğe AISI 2507 Süper Dubleks Paslanmaz Çeliğinin Hibrit Soğutma/Yağlama Yöntemleri Altında Tornalanmasında Yüzey Kalitesinin İncelenmesi(2021) Kıvak, Turgay; Şirin, Şenol; Çelik, EmreSon yıllarda ekolojik soğutma/yağlama yöntemleri sürdürülebilir imalat için metal işleme operasyonlarında kullanılmaya başlanmıştır. Bu yöntemlerin başında ise birbirine göre üstün özelliklerin bir araya getirildiği hibrit soğutma/yağlama yöntemlerinin kullanıldığı çalışmalar ön plana çıkmaktadır. Bu çalışmada; AISI 2507 dubleks paslanmaz çeliğinin Minimum Miktarda Yağlama (MMY), kriyojenik soğutma (Kry) ve hibrit (Kry+MMY) soğutma/yağlama koşulları altında tornalanmasında, yüzey kalitesi incelenmiştir. İşlenen yüzeylerin kalitesinin belirlenmesinde yüzey pürüzlülük (Ra), iki boyutlu yüzey görüntüleri ve üç boyutlu yüzey topografyaları kullanılmıştır. Deneyler üç farklı soğutma/yağlama koşulunda (MMY, Kry ve Kry+MMY), kesme hızında (80, 120 ve 160 m/dak) ve ilerlemede (0,16-0,20 ve 0,24 mm/dev) gerçekleştirilmiştir. Deney tasarımında ve optimum koşulların belirlenmesinde Taguchi L27 tasarımı kullanılmıştır. Deneysel sonuçlara etki eden faktörler ve faktörlerin etki oranlarını belirlemek için varyans analizi (ANOVA) kullanılmıştır. Deney sonuçlarına göre yüzey kalitesi için optimum koşullar, Kry+MMY hibrit soğutma/yağlama koşulu, 160 m/dak kesme hızı ve 0,16 mm/dev ilerleme olarak belirlenmiştir. En iyi Ra değeri (1,151 µm) A3, B3, C1 koşulunda, en kötü Ra değeri ise (-2,861 µm) A2, B1, C3 koşulunda elde edilmiştir.Öğe Attenuating saturated-regulator operation effect of brushless DC motors through genetic-based fuzzy logic estimator(Tubitak Scientific & Technical Research Council Turkey, 2018) Çelik, Emre; Öztürk, NihatAs brushless DC motor (BLDCM) speed approaches base speed, current regulators gradually saturate and lose their ability to perform their regulating task, which causes a dramatic fall in the phase currents and motor power. To control the current to a greater extent and avoid power decline, a new reference current generation technique based on a simple fuzzy logic estimator (FLE) is introduced in this paper. According to motor speed and current command, the developed FLE decides the proper commutation angle a, which is the angle relative to normal commutation instant used for setting the current slew rate during commutation. In this sense, current references are obtained with the same slew rates of commutated phases all the time, ensuring the noncommutation phase current is constant. The validity of the study is widely verified using DSP of TMS320F28335 and it is concluded that promising performance and simplicity are important advantages of our proposal that render it convenient for a BLDCM drive system that requires boosted power in high-speed ranges.Öğe Boosted sooty tern optimization algorithm for global optimization and feature selection(Elsevier Ltd, 2023) Houssein, Essam H.; Oliva, D.; Çelik, Emre; Emam, M.M.; Ghoniem, R.M.Feature selection (FS) represents an optimization problem that aims to simplify and improve the quality of highly dimensional datasets through selecting prominent features and eliminating redundant and irrelevant data to classify results better. The goals of FS comprise dimensionality reduction and enhancing the classification accuracy in general, accompanied by great significance in different fields like data mining applications, pattern classification, and data analysis. Using powerful optimization algorithms is crucial to obtaining the best subsets of information in FS. Different metaheuristics, such as the Sooty Tern Optimization Algorithm (STOA), help to optimize the FS problem. However, such kind of techniques tends to converge in sub-optimal solutions. To overcome this problem in the STOA, an improved version called mSTOA is introduced. It employs the balancing exploration/exploitation strategy, self-adaptive of the control parameters strategy, and population reduction strategy. The proposed approach is proposed for solving the FS problem, but also it has been validated over benchmark optimization problems from the CEC 2020. To assess the performance of the mSTOA, it has also been tested with different algorithms. The experiments in terms of FS provide qualitative and quantitative evidence of the capabilities of the mSTOA for extracting the optimal subset of features. Besides, statistical analyses and no-parametric tests were also conducted to validate the result obtained by the mSTOA in optimization. © 2022 Elsevier LtdÖğe Cogging torque minimization using skewed and separated magnet geometries(2020) Dalcalı, Adem; Kurt, Erol; Çelik, Emre; Öztürk, NihatIn the study, analytical design, analysis and optimization of a 2.5 kW 14-pole, 84-slot permanent magnet synchronous generator(PMSG) have been performed. The performance characteristics of this PMSG such as efficiency, torque, cogging torque andmagnetic flux density are assessed. Then, 3D model of the respective generator is acquired to examine the effect of magnetgeometry on the cogging torque produced. In that context, the effects of splitted and skewed magnet structures are examined. Inthe first design, the magnet is modelled with one piece and the rms value of the cogging torque is found as 436.75 mNm. In thesecond case, a certain skewed slit is made alongside the magnet and that yields a slightly reduced cogging torque of 434.58 mNm.In the other design, the magnet of the first design is divided into two sub-parts, which are then combined together in a skewedfashion. Thus, the value of cogging torque is found as 159.60 mNm. Eventually, by making two certain slits on the last model,cogging torque is further depressed down to 89.95mNm. It is concluded from the obtained results that the last design contributesan improvement in the value of cogging torque up to 80% compared to the initial design.Öğe Değişken Hava Aralıklı Gölge Kutuplu Asenkron Motorun Faz Endüktanslarının Tespitine Yönelik Detaylı Bir Çalışma(2019) Dalcalı, Adem; Akbaba, Mehmet; Çelik, EmreGölge kutuplu asenkron motorlar (GKAM) yapılarının basit, maliyetlerinin düşük olması ve az bakıma ihtiyaç duymaları nedeniyle endüstriyel uygulamalarda, ev aletlerinde ve havalandırma sistemlerinde yoğun bir şekilde kullanılmaktadırlar. GKAM’da eliptik döner alanın oluşumu motorun analizini oldukça zorlaştırmaktadır. Bu karmaşıklığın sonucu olarak, bu tip motorların teorisi, tasarımı ve analizi konusunda nispeten sınırlı yayın bulunmaktadır. Çoğunlukla bu motorların tasarımları deneme-yanılma yöntemine dayanmaktadır. Bilindiği üzere elektrik makinalarının performansının doğru bir şekilde hesaplanması, hesaplamalarda kullanılan sargı endüktanslarının doğruluğu ile yakından ilişkilidir. Bu nedenle, çalışmada 4 kutuplu GKAM’ın stator sargısı ve gölge kutup sargısı sargı başı endüktansı, stator sargısı öz endüktansı, stator sargısı toplam kaçak endüktansı ve stator-rotor ortak endüktansı analitik denklemler ve gerçek zamanlı deneyler yardımıyla elde edilmiştir. Aynı zamanda manyetik doyumun stator öz endüktansı ve kaçak endüktansına etkisi ile stator-rotor ortak endüktansının rotor pozisyonuyla değişimi incelenmiştir. Çalışmanın sonunda, hesaplanan stator sargısı öz endüktansının doğruluğu deneysel bir yaklaşımla doğrulanmıştır.Öğe Design and Robustness Analysis of Multiple Extended State Observer Based Controller (MESOBC) for AVR of the Power System(Hindawi Limited, 2023) Gandhi, Ravi; Masikana, S.B.; Sharma, Gulshan; Çelik, EmreAutomatic voltage regulator (AVR) is installed on the synchronous generators in the power system and plays a very important role in maintaining the generator output voltage besides changes in load demand, parametric uncertainties, and operating temperature. As the load is continuously varying in the system, the AVR needs controllers to track and regulate the voltage of the synchronous generator much faster. This paper shows an initial attempt to design a robust multiple extended state observer (MESO) to estimate the variation in lump disturbances (i.e., load demand and parametric uncertainties) from all the components of the AVR. MESO-based controller (MESOBC) can track such matching and mismatching of both types of irregularities and regulate the terminal voltage of the generator accordingly. MESOBC performance is matched with strong published AVR designs for a standard condition, ±30% load voltage variation and for simultaneous changes in AVR parameters with ±30% load voltage variations. Integrated square error (ISE) is chosen as an objective function to compare the output of MESOBC with other published AVR designs in view of graphical AVR responses and by calculating various numerical values for AVR responses. At last, the robustness of MESOBC is also checked through sensitivity analysis, and it is seen that MESOBC guaranteed robust performance for the AVR of the power system under diverse operating conditions. © 2023 Ravi Gandhi et al.Öğe Enhanced speed control of a DC servo system using PI plus DF controller tuned by stochastic fractal search technique(Pergamon-Elsevier Science Ltd, 2019) Çelik, Emre; Gör, HalilSince Proportional +Integral +Derivative (PID) controller is still the workhorse in taking over the workload of process control systems, this article introduces a new design methodology toward improving the performance of such controller. After a PI control law with windup protection is given, it is combined with a derivative path employing a first-order low pass filter in an innovative way to develop a performant controller called PI + DF controller. In attempting to attain a high level of control performance, gains of this controller including proportional, integral, derivative and filter gains are tuned choosing the recently introduced Stochastic Fractal Search (SFS) algorithm owing to its superiority to many state-of-the-art algorithms considering convergence, accuracy and robustness. To evaluate the efficacy of SFS, Particle Swarm Optimization (PSO) is also applied to the case study. Furthermore, the presented SFS optimized PI + DF controller is compared to a recently reported control scheme through simulation and experimental tests on an identical DC servo system. After providing the stability proof, SFS tuned PI + DF controller is found to be the pioneer in exhibiting the most accurate speed response profile under complicated scenarios, which is followed by PSO tuned PI + DF controller and the existing control approach, respectively. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.Öğe Estımatıon Of Synchronous Motor Excıtatıon Current Usıng Multıple Lınear Regressıon Model Optımızed By Symbıotıc Organısms Search Algorıthm(2018) Çelik, EmreIn this paper, an effective and simple means of estimating the excitation current of a synchronous motor (SM) is presented for power factor correction task. First, a multiple linear regression model with four predictor variables such as motor load current, actual power factor, power factor error and excitation current change is formed to estimate the SM excitation current. Then, recently introduced symbiotic organisms search (SOS) algorithm is benefitted in the hope of searching better values of regression coefficients in that model using the data collected from the prepared experimental setup. The supremacy of SOS over some recently published algorithms such as genetic algorithm, artificial bee colony and gravitational search algorithm is widely attested through comparative computer simulations for the similar compensation system. The results exhibited in this article show that the presented technique outperforms the other reported popular algorithms from the aspects of simplicity, robustness and accuracy. In view of this, the suggested tuning of regression coefficients of the multiple linear regression model yields a better estimating performance of SM excitation current than the earlier studies.Öğe A hybrid symbiotic organisms search and simulated annealing technique applied to efficient design of PID controller for automatic voltage regulator(Springer, 2018) Çelik, Emre; Öztürk, NihatThis article is motivated by incorporating a hybrid symbiotic organisms search and simulated annealing (hSOS-SA) technique into efficient design of PID controller for automatic voltage regulator (AVR). Symbiotic organism search (SOS) algorithm is contemplated first to optimize parameters of PID controller using a new cost function which considers both time-domain and frequency-domain specifications. The excellence of SOS over some state-of-the-art techniques is confirmed through transient response analysis, root locus analysis and bode analysis for the identical AVR system. To fine-tune controller parameters for enhancing the system stability margin further, simulated annealing algorithm is invoked subsequently at the instant SOS has converged. Extensive numerical results computed from time and frequency response specifications affirm the superiority of proposed hSOS-SA algorithm such that after a minimal overshoot, hSOS-SA tuned AVR system settles to the step reference quickly and follows it with the least steady-state error. Such response is found to ensure a better stability margin than that using original SOS and earlier studies. Finally, robustness analysis is realized to verify that the designed controller is robust with regard to parameter uncertainties.Öğe IEGQO-AOA: Information-Exchanged Gaussian Arithmetic Optimization Algorithm with Quasi-opposition learning(Elsevier, 2023) Çelik, EmreArithmetic optimization algorithm (AOA) is a math optimizer proposed to solve optimization chal-lenges. Its capability to find the global solution comes from the behavior of four arithmetic operators: multiplication, division, subtraction and addition. Local minima stagnation and sluggish convergence are the major concerns of AOA. To handle these issues, three effective modifications are proposed. Information exchange is introduced among the search agents first. Then, promising solutions around the best and current solutions are visited by a plausible way based on the Gaussian distribution. Finally, quasi-opposition of the best solution is obtained to have a higher chance of approaching the global solution. The proposed approach is named as Information-Exchanged Gaussian AOA with Quasi-Opposition learning (IEGQO-AOA). 23 standard benchmark functions, 10 CEC2020 test functions and 1 real-life engineering design problem are solved by the proposed IEGQO-AOA and its competing peers such as the original and modified versions of AOA, dwarf mongoose optimization, reptile search algorithm, aquila optimizer, bat algorithm, sine cosine algorithm, original and enhanced version of salp swarm algorithm, dragonfly search algorithm, LSHADE-EpSin, stochastic fractal search, improved jaya and moth-flame optimization, perturbed stochastic fractal search and nelder-mead simplex orthogonal learning moth-flame optimization algorithm. Comparative results based on the statistical tests ratify the potential of IEGQO-AOA in solving problems concerning accuracy and convergence without compromising on the algorithm's simplicity much.(c) 2022 Elsevier B.V. All rights reserved.Öğe Improved load frequency control of interconnected power systems using energy storage devices and a new cost function(Springer London Ltd, 2023) Çelik, Emre; Öztürk, Nihat; Houssein, Essam H.This paper investigates the use of energy storage devices (ESDs) as back-up sources to escalate load frequency control (LFC) of power systems (PSs). The PS models implemented here are 2-area linear and nonlinear non-reheat thermal PSs besides 3-area nonlinear hydro-thermal PS. PID controller is employed as secondary controller in each control area and ESDs such as battery energy storage system, flywheel energy storage system and ultra-capacitor are employed to assist LFC task during crest load disturbances. PID controller parameters are optimized by salp swarm algorithm (SSA) using a new cost function. This function is innovative, improving system stability by increasing stability margin of the system. Contribution of the proposed approach are thoroughly justified by contrasting it against the renowned works in the state-of-the-art. The comparison analysis clearly unveils that SSA optimized PID controller with ESDs is able to significantly reduce settling time and unwanted oscillations of frequency and tie-line power deviations with a greater stability margin. Our proposal is also more economic than the existing solutions considering the trade-off between simplicity and effectiveness.Öğe Influence of energy storage device on load frequency control of an interconnected dual-area thermal and solar photovoltaic power system(Springer London Ltd, 2022) Çelik, Emre; Öztürk, Nihat; Houssein, Essam H.The mismatch between power generation and load demand causes unwanted fluctuations in frequency and tie-line power, and load frequency control (LFC) is an inevitable mechanism to compensate the mismatch. For this issue, this paper explores the influence of energy storage device (ESD) on ameliorating the LFC performance for an interconnected dual-area thermal and solar photovoltaic (PV) power system. Initially, to alleviate the frequency and tie-line power deviations, a proportional-integral (PI) controller is chosen and utilized in the system due to its effectiveness and simplicity in practice. For achieving the highest performance from this controller, salp swarm algorithm (SSA) is employed to search for optimal controller parameters by using integral of time-multiplied absolute error (ITAE) criterion. To affirm the contribution of SSA optimized PI controller, it is contrasted with a recent approach utilizing PI controller optimized by genetic algorithm (GA) and firefly algorithm (FA). It is observed that the results acquired for SSA are better than for GA and FA. To improve the system performance further, ESD such as redox flow battery (RFB) famous for its excellent disturbance rejection capability is integrated with the thermal power unit for the first time in the literature. It is divulged from the results that the system performance with RFB has boosted considerably with regard to shorter settling time, less undershoot/overshoot and smaller ITAE value of the frequency and tie-line power fluctuations. According to the sensitivity analysis, our proposal is found robust against system parameters variations and different loading conditions.Öğe Novel fuzzy 1PD-TI controller for AGC of interconnected electric power systems with renewable power generation and energy storage devices(Elsevier - Division Reed Elsevier India Pvt Ltd, 2022) Çelik, Emre; Öztürk, NihatThe work prepared designs a novel fuzzy 1 + proportional + derivative-tilt + integral (F1PD-TI) controller and applies it to automatic generation control (AGC) of power systems (PSs) with renewable energy sources (RESs) based on solar thermal, wind and fuel cells. The capability of this unique controller is initially tested on a two-area reheat thermal power system and then on a multi-source two-area hydrothermal power system. To avert the malfunction owing to improper controller parameters, input scaling factors and other parameters of the F1PD-TI controller are meticulously procured using salp swarm algorithm (SSA) by minimizing the value of integral squared error (ISE) criterion. The worth and contribution of SSA optimized F1PD-TI controller are proclaimed by comparing the results with those offered by several latest controllers. Investigations disclose that the advocated approach beats its serious rivals in terms of shorter settling time, less undershoot/overshoot and smaller ISE value of frequency and tie-line power deviations. As more realistic scenarios, RESs uncertainties in wind speed and solar irradiation are studied and energy storage devices are employed to remedy the problem of surplus/deficient power due to the RESs penetration. Moreover, nonlinearities from governor dead band and generation rate constraint are examined. We realize that significantly better performance and relatively easier design are prominent features of our proposal, which may render it a suitable candidate for practical applications. (C) 2022 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Öğe Performance analysis of SSA optimized fuzzy 1PD-PI controller on AGC of renewable energy assisted thermal and hydro-thermal power systems(Springer Heidelberg, 2022) Çelik, EmreNonlinear structure, vague loading characteristics and parameter uncertainties of the interconnected power system (IPS) have recently given birth to various controllers that better deal with automatic generation control (AGC). AGC plays a key role in ensuring the balance of generation and load demand in IPSs. If this balance is lost, then the system faces large frequency deviations. Thus, this work proposes a new fuzzy 1 + proportional + derivative-proportional + integral (F1PD-PI) controller to escalate AGC performance of different IPSs integrated with renewable energy sources (RES) including wind, solar and fuel cells. Inspiration for the proposed controller is unique and comes from combining the merits of fuzzy, 1PD and PI controllers. Salp swarm algorithm (SSA) is utilized to optimize the proposed controller's gains as well as fuzzy membership functions. The effectiveness and contribution of the advocated approach are demonstrated on a two-area reheat thermal system and a two-area multi-source hydro-thermal system by realizing an extensive comparison study with the state-of-the-art variants. The results substantiate that SSA optimized F1PD-PI controller has better performance than its competing peers in terms of minimum settling time, peak undershoot, peak overshoot and error-integrating performance criterion of the system responses. Nonlinearities from governor dead band and generation rate constraint are also studied, which verifies the performance of the control strategy in tackling nonlinearities. Additionally, the robustness of the controller is affirmed against parameter uncertainties and load disturbances. Finally, the stability of our proposal is checked using eigenanalysis.Öğe Performance enhancement of automatic voltage regulator by modified cost function and symbiotic organisms search algorithm(Elsevier - Division Reed Elsevier India Pvt Ltd, 2018) Çelik, Emre; Durgut, RafetThis article attempts to solve the problem of efficient design of proportional + integral + derivative (PID) controller applied to popular automatic voltage regulator (AVR) system by employing recently introduced symbiotic organisms search (SOS) algorithm, for the first time. PID controller design needs proper determination of three control parameters. Such a design problem can be taken as an optimization task and SOS is invoked to find out better controller parameters through a new cost function defined in the paper, which allows to evaluate the control behavior in both time-domain and frequency-domain. For the performance analysis, distinct analysis techniques are deployed such as transient response analysis, root locus analysis and bode analysis. Besides, robustness analysis of the closed-loop control system tuned by SOS is performed with regard to parameter uncertainties and external disturbance. The efficacy of the presented technique is widely illustrated by comparing the obtained results with those reported in some prestigious journals and it is shown that our proposal leads to a more satisfactory control performance from the perspective of both time-domain and frequency-domain specifications while with a good robustness to parameter uncertainties and unknown changes in the system output. (C) 2018 Karabuk University. Publishing services by Elsevier B.V.Öğe Self-adaptive Equilibrium Optimizer for solving global, combinatorial, engineering, and Multi-Objective problems(Pergamon-Elsevier Science Ltd, 2022) Houssein, Essam H.; Çelik, Emre; Mahdy, Mohamed A.; Ghoniem, Rania M.This paper proposes a self-adaptive Equilibrium Optimizer (self-EO) to perform better global, combinatorial, engineering, and multi-objective optimization problems. The new self-EO algorithm integrates four effective exploring phases, which address the potential shortcomings of the original EO. We validate the performances of the proposed algorithm over a large spectrum of optimization problems, i.e., ten functions of the CEC'20 benchmark, three engineering optimization problems, two combinatorial optimization problems, and three multi-objective problems. We compare the self-EO results to those obtained with nine other metaheuristic algorithms (MAs), including the original EO. We employ different metrics to analyze the results thoroughly. The self-EO analyses suggest that the self-EO algorithm has a greater ability to locate the optimal region, a better trade-off between exploring and exploiting mechanisms, and a faster convergence rate to (near)-optimal solutions than other algorithms. Indeed, the self-EO algorithm reaches better results than the other algorithms for most of the tested functions.Öğe Sensitivity Factor-Based Congestion Mitigation in DPS Applying Novel Hybrid GWPSO(Taylor & Francis Inc, 2023) Gautam, Anubha; Sharma, Parshram; Kumar, Yogendra; Sharma, Gulshan; Gautam, Anurag; Çelik, Emre; Öztürk, NihatIn a deregulated power system, with a limited power system framework, alleviation in power transfer has been one of the most crucial problems. This alleviation of bulk power transmission came with congestion, where a transmission line transmits power very near the constrained thermal limits. Congestion has to be mitigated for reliable, economical, and stable operation of the power system. Congestion can be mitigated by applying several methods which may be cost-free or non-cost-free. This article presents a cost-free method employing TCSC as a FACTS device. FACTS devices are very costly. To make the TCSC operation economic, LUF and DLUF are used here to optimally locate the device. TCSC is used here as a variable impedance device. A novel hybrid heuristic optimization technique where Grey Wolf optimizer is merged with Particle Swarm Optimizer to optimize the size of TCSC. The proposed method is implemented to regulate the line reactance for congestion mitigation. The power loss and voltage deviation of the system are reduced by the proposed method to relieve the system congestion. The system security margin is enhanced significantly to make the system more reliable. The proposed algorithm is validated on IEEE 30 bus system and is also validated by comparing the results with parent algorithms. The results reveal that the proposed methodology successfully minimized the objectives for mitigating congestion.Öğe A Short-Term Load Demand Forecasting based on the Method of LSTM(Ieee, 2021) Bodur, İdris; Çelik, Emre; Öztürk, NihatElectricity energy is produced from another energy source like fossil source such as oil, coil, natural gas renewable energy sources such as hydraulic, wind, solar. Their storage in high amount is a problematic issue. Therefore, the balance between the power generation and demanded power must be satisfied at all times. This is an obligation especially for companies that generate, transmit and distribute electrical energy. In this paper, a short term load demand forecasting based on a long short term memory (LSTM) is addressed, which may help planning operators for Turkish electricity market. The results of advocated approach were compared by the ones based on recurrent neural network As a result, it is found that the proposed LSTM approach can predict especially daily and weekly demands with an accuracy more than 90%.Öğe Simplified Model and Genetic Algorithm Based Simulated Annealing Approach for Excitation Current Estimation of Synchronous Motor(Univ Suceava, Fac Electrical Eng, 2018) Kaplan, Orhan; Çelik, EmreReactive power demanded by many loads besides active power is one of the important issue in terms of the efficient use of energy. The optimal solution of reactive power demand can be performed by tuning the excitation current of synchronous motor available in power system. This paper presents an effective application of genetic algorithm-based simulated annealing (GASA) algorithm to solve the problem of excitation current estimation of synchronous motors. Firstly, the multiple linear regression model used in a few studies for estimation of excitation current of synchronous motor, is considered and regression coefficients of this model are optimized by GASA algorithm using training data collected from experimental setup performed. The supremacy of GASA over some recently reported algorithms such as gravitational search algorithm, artificial bee colony and genetic algorithm is widely illustrated by comparing the estimation results. Owing to the observation of weak regression coefficient of load current indicating that it is not much beneficial to excitation current, load current is removed from the regression model. Then, the remaining regression coefficients are tuned to accommodate new modification. It is seen from the findings that both training and testing performance of the simplified model are improved further. The major conclusions drawn from this study are that it introduces a new efficient algorithm for the concerned problem as well as the multiple linear regression model, which has the advantages of simplicity and cost-friendliness.
