Yazar "Akdag, Ozan" seçeneğine göre listele
Listeleniyor 1 - 12 / 12
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Adaptive protection method with fault current limiting mechanism for directional over current relays coordination problem(Gazi Univ, Fac Engineering Architecture, 2022) Yeroglu, Celaleddin; Akdag, OzanCoordination of Directional Over Current Relays (DOCR) is an important issue in the protection of power systems. In this paper, DOCR coordination, which has the problem of nonlinear and high constraints, is discussed The object function, reported in the literature, has been re-written by adding relay setting constraints multiplied by a weight factor to ensure optimum coordination of DOCRs. At first, the Evaporation Rate Controlled Water Cycle Algorithm (ER-WCA) and Harris Hawk Optimization (HHO) algorithms were used to compute the optimum coordination of the DOCR problem. The proposed algorithms are applied to the 9-bus test system. In addition, the results obtained using ER-WCA and HHO were compared with those obtained using other algorithms in the literature. Then, a new adaptive protection method, which adapts to changing power system conditions in power grids with Distributed Generation (DG) system, is proposed. In this new adaptive protection method, the HHO algorithm has been used to ensure optimum coordination of DOCRs. Also, in this new adaptive protection method, a structure with Fault Current Limiting (FCL) mechanism, which determines the critical fault point based on the both of the current and voltage index, is proposed in power systems. Then, by applying this new adaptive protection method to 10 bus Turkey distribution system, the effectiveness of the study was discussed.Öğe Combination of electromagnetic field and harris hawks optimization algorithms with optimization to optimization structure and its application for optimum power flow(Taylor & Francis Ltd, 2023) Akpamukcu, Mehmet; Ates, Abdullah; Akdag, OzanElectromagnetic Field Optimization (EFO) and Harris Hawk Optimization (HHO) algorithms are combined with the optimization to optimization (OtoO) approach, and the EFO-HHO algorithm pair is presented in this study. EFO method was used as the essential algorithm and HHO method was used as the auxiliary algorithm according to the OtoO structure. The constant parameters (R_rate, Ps_rate, P_field, N_field) of the EFO algorithm that affect the optimization performance are optimized with the HHO optimization algorithm for the related optimization problem. The proposed method was tested on 10 different benchmark functions according to different dimensional (30, 50100). The EFO-HHO algorithm pair can produce better results than the existing literature, especially in cases of increased dimension with the proposed approach. In addition to these, the OPF problem was tested on the IEEE 30 test bus system for the engineering application of the proposed method. The results are compared with the existing literature results. As it can be seen from the results, it has been shown on the real engineering problem that the optimization performance can be increased with the OtoO approach without changing the basic philosophy of the EFO algorithm.Öğe An evaluation of an offshore energy installation for the Black Sea region of Turkey and the effects on a regional decrease in greenhouse gas emissions(Wiley Periodicals, Inc, 2020) Akdag, Ozan; Yeroglu, CelaleddinOffshore wind power plants (OWPPs), which are not yet installed in Turkey, are becoming a popular method of energy production around the world because of their environmentally friendly nature. Thus, the installation of OWPPs should be an important agenda item in terms of Turkey's renewable energy policies as a contribution to the global greenhouse gas emission targets. This study proposes a model for installing OWPPs in a suitable part of the Black Sea region of Turkey and simulates the results. The suitable locations for OWPP installation were evaluated according to the technical and geographical conditions of this region and site criteria. Meteorological data from these locations were analyzed in the Wind Atlas Analysis and Application Program (WAsP) to determine the best location. In this study, an OWPP model with a 204.6 MW installed power capacity was proposed for the identified location, which has a wind speed of 8.77 m s(-1) and a wind power density of 348 W m(-2). Then, an OWPP model and regional energy transmission system was modeled using DigSilent software. The load flow analysis was performed using this model, and the results show that 7616 tons of toxic gas and 1.527 million tons of greenhouse gas could be reduced in the region in a year if the proposed OWPP were put into operation. Thus, with the installation of OWPP, this study shows that annual CO2 emissions can be reduced by 7.63% for the entire Black Sea region. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.Öğe Load Flow Optimization of 154 kV Malatya Transmission Line Using Differential Evolution Algorithm(Ieee, 2017) Akdag, Ozan; Karadogan, Ismail; Okumus, Fatih; Yeroglu, Celaleddin; Karci, AliAmplitude, phase angle, active and reactive powers flowing in each busbar of a power system can be seen by performing a load flow analysis. From these data, it is possible to determine the voltage drop, the distribution of the forces, the loading of the equipment and the losses of the related power system. Then, Active power losses can be reduced by making improvements at the points where losses are present in the power system. Power losses can be reduced by reactive power compensation considerably. In this study, Differential Evolution (DE) algorithm is used to determine the values of the capacitor groups to be added to the corresponding busbar to reduce the losses of 154 kV transmission system. The optimum load flow is ensured by optimizing a transmission system with the developed algorithm.Öğe Modification of Harris hawks optimization algorithm with random distribution functions for optimum power flow problem(Springer London Ltd, 2021) Akdag, Ozan; Ates, Abdullah; Yeroglu, CelaleddinHarris hawks optimization (HHO) algorithm, which is inspired from Harris hawks hunting strategy, uses uniform random numbers in the optimization process. This paper proposes modifying HHO with seven types of random distribution function definitions that are chi-square distribution, normal distribution, exponential distribution, Rayleigh distribution, Student's distribution,Fdistribution, and lognormal distribution to show effects on stochastic search-based optimization algorithm performance. The modified HHO algorithm is tested via some benchmark test functions. Results are compared with each other and with classical HHO solutions. Then, the HHO and its modified versions are applied to optimum power flow (OPF), which is an important problem for power system engineering for decades. The algorithms are applied to IEEE 30-bus test system to minimize total fuel cost of the power system, active/reactive power losses, and emission, by comparing with recent OPF researches. Considering the applicability of the proposed approach and the results achieved, one can confirm that it might be a different alternative method for solving OPF problems. One of the important results of the paper in the IEEE 30-bus test system is that the cost of fuel is calculated as 798.9105 $/h with classical HHO, while it is calculated as 798.66 $/h with the HHO modified with SD function.Öğe Modified Archimedes optimization algorithm for global optimization problems: a comparative study(Springer London Ltd, 2024) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanArchimedes Optimization Algorithm (AOA) is a recent optimization algorithm inspired by Archimedes' Principle. In this study, a Modified Archimedes Optimization Algorithm (MDAOA) is proposed. The goal of the modification is to avoid early convergence and improve balance between exploration and exploitation. Modification is implemented by a two phase mechanism: optimizing the candidate positions of objects using the dimension learning-based (DL) strategy and recalculating predetermined five parameters used in the original AOA. DL strategy along with problem specific parameters lead to improvements in the balance between exploration and exploitation. The performance of the proposed MDAOA algorithm is tested on 13 standard benchmark functions, 29 CEC 2017 benchmark functions, optimal placement of electric vehicle charging stations (EVCSs) on the IEEE-33 distribution system, and five real-life engineering problems. In addition, results of the proposed modified algorithm are compared with modern and competitive algorithms such as Honey Badger Algorithm, Sine Cosine Algorithm, Butterfly Optimization Algorithm, Particle Swarm Optimization Butterfly Optimization Algorithm, Golden Jackal Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, Salp Swarm Algorithm, and Atomic Orbital Search. Experimental results suggest that MDAOA outperforms other algorithms in the majority of the cases with consistently low standard deviation values. MDAOA returned best results in all of 13 standard benchmarks, 26 of 29 CEC 2017 benchmarks (89.65%), optimal placement of EVCSs problem and all of five real-life engineering problems. Overall success rate is 45 out of 48 problems (93.75%). Results are statistically analyzed by Friedman test with Wilcoxon rank-sum as post hoc test for pairwise comparisons.Öğe A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters(Ieee-Inst Electrical Electronics Engineers Inc, 2023) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, TeomanElectric vehicles (EVs) have positive impacts on reducing oil dependence and exhaust emissions. However, the range problem of EVs is a factor that raises concerns for individual users and bus operators. For this reason, studies on increasing the range of the electric buses in public transportation is extremely important to ensure optimum operation. In this study, a novel energy consumption model, MTECM (Malatya Trolleybus Energy Consumption Model), is developed using the multi-parameter linear regression method. The real-time big data was collected on the field of Trolleybus vehicles, which have been operated for 8 years in Malatya / Turkiye. Firstly, by calculating the correlation of the parameters affecting this model, the parameters that are suitable for the purpose of our study are determined and regression analysis is performed on the original Trolleybus dataset. A total of 75.497.472 data are analyzed for this model. The RMSE (Root Mean Square Error) of MTECM is calculated as 0.29996. The trained model is applied to the 10 busiest routes in Malatya in terms of passenger density. The RMSE value on these routes is calculated between 0.30299 and 0.31421. Based on the results, with lower error rates, the proposed novel model is more efficient than other studies in the literature. In addition, energy consumption can be calculated for any route planned to establish an electric bus operation with MTECM. Therefore, according to the consumption obtained, the correct determination and selection of parameters that significantly affect the investment cost such as route, vehicle length, engine power, and battery capacity can be made.Öğe A novel modified Archimedes optimization algorithm for optimal placement of electric vehicle charging stations in distribution networks(Elsevier, 2023) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanThe number of electric vehicle charging stations (EVCSs) is increasing alongside electric vehicles (EVs). The unplanned rollout of EVCSs can lead to problems such as deterioration of the voltage profile, increased active power losses, and maximum load demand in distribution networks (DNs). Therefore, EVCSs should be placed in optimum locations on the DNs. The complexity of the problem requires efficiency and performance. In this paper, a novel modified Archimedes optimization algorithm (MAOA) is proposed for optimal placement of EVCSs in DNs. Five parameters of the AOA were modified using the Honey Badger Algorithm (HBA). This placement is based on a combination of indexes: power loss, voltage deviation, and voltage stability index (VSI). Next, Newton-Raphson based load flow analysis is used to compute the minimum cost. MAOA, AOA and eight other optimization algorithms are compared. The results provide the most appropriate buses in the DN. The efficiency of the proposed algorithm was tested on IEEE 33, 69, and 10-bus Hatay power network systems. In all test systems, the proposed MAOA provided the best results with consistently low standard deviation values. The results suggest that the proposed method is more effective in the integration of EVCSs into the DN. (c) 2017 Elsevier Inc. All rights reserved.Öğe A Novel Newton Raphson-Based Method for Integrating Electric Vehicle Charging Stations to Distribution Network(Aves, 2023) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanElectric vehicle sales are rising due to numerous factors such as government policies, falling prices, advanced, and eco-friendly technology. Built-in battery packs are charged using the energy from the distribution network. When a large number of electric vehicles are simultaneously charged with high power, the distribution network can be adversely affected. Differences in electricity supply and demand on the distribution network, voltage imbalance, and power losses are among the examples of effects. In this study, a mathematical model has been proposed in order to properly handle the effects of charging stations on the distribution network. According to the model, the optimum placement of electric vehicle charging stations is achieved within the constraints of the distribution network. In order to prove the robustness and validity of this model, the proposed model is applied to IEEE 33-bus radial test system. Results are discussed in cases.Öğe Optimal directional overcurrent relay coordination using MRFO algorithm: A case study of adaptive protection of the distribution network of the Hatay province of Turkey(Elsevier Science Sa, 2021) Akdag, Ozan; Yeroglu, CelaleddinCoordination of Directional Over Current Relays (DOCR) is an important issue in the protection of power sys-tems. In this paper, the object function of DOCR has been modified for better coordination. Manta Ray Foraging Optimization (MRFO) algorithm is adapted to the DOCR with the modified object function to maintain optimum relay coordination by preserving the relay coordination margin between the relay pairs. In order to show the success of the proposed technique, the algorithm has been applied to the 9-bus and 15-bus test system. The obtained results have been compared to other algorithms in the literature. Further, an adaptive protection structure, which provides optimum coordination of DOCR with MRFO algorithm according to changing power system conditions, has been proposed for a network that include Distributed Generation (DG) power plant. The proposed adaptive protection structure has been applied to the virtual model of a cross-section of 10 bus dis-tribution networks that includes a Wind Powered DG (WP-DG) in the Hatay province of Turkey.Öğe Optimization of Proportional-Integral-Derivative Parameters for Speed Control of Squirrel-Cage Motors with Seahorse Optimization(Aves, 2024) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, TeomanThe two different motion behaviors of seahorses in nature served as inspiration for the seahorse optimization (SHO) method, which is a new metaheuristic swarm intelligence-based approach to solving fundamental engineering problems. In this study, the propo rtion al-in tegra l-der ivati ve (PID) parameters for the simplified speed control of the manipulator joint using squirrel-cage induction motors were calculated with the SHO algorithm. As a result of these calculations, Kp, Ki, and Kd values were obtained as 0.0430, 0.00474, and 0.03254, respectively. Then, the time for the squirrel-cage motor to reach 50 rpm (revolutions per minute) and 90 rpm was calculated with the help of SHO. In PID + SHO operation, the squirrel-cage electric motor reached 50 rpm in 3 seconds and 90 rpm in 8 seconds. In this study, in which the SHO optimization method was used, it was calculated that the acceleration of the squirrel-cage motor and reaching the desired value gave 50% better results compared to the particle swarm optimization algorithm.Öğe Overcurrent Relay Coordination of 154/34,5 kV Hasancelebi Substation by League Championship Algorithm(Ieee, 2017) Seyyarer, Abubekir; Akdag, Ozan; Hark, Cengiz; Karci, Ali; Yeroglu, CelaleddinIn this study, non-directional overcurrent relay coordination was done in 154/34.5 kV Malatya Teias Hasancelebi transformer centre using League Championship Algorithm (LCA). Standard inverse time characteristic based on IEC 255-3 is used for the relay is coordinated. The results obtained by the LCA have been used in virtual model, obtained by DigSilent software for overcurrent relays at the Hasancelebi transformer centre. Then, the overcurrent relay coordination was performed by examining the response of the overcurrent relays to the 3-phase fault currents generated in the model.
