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Escape velocity: a new operator for gravitational search algorithm
(Springer London Ltd, 2019) Güvenç, Uğur; Katırcıoğlu, Ferzan
Gravitational search algorithm (GSA) is based on the feature of reciprocal acceleration tendency of objects with masses. The total force, which is formed as an influence of other agents, is an important variable in the calculation of agent velocity. It has been determined that the total force and, thus, the velocity of the agents that are located far away, is low due to the distance. In this case, they continue their search in bad areas, as their velocity is low, which means a decrease in their contribution to optimization result. In this paper, a new operator called escape velocity has been proposed which is inspired by the real nature of GSA. It has been suggested that adding the escape velocity negatively will enable the agents that remain far away or outside of group behavior to be included in the group or to be increased in velocity. Thus, the study of perfecting the herd or group approach within the search scope has been carried out. To evaluate the performance of our algorithm, we applied it to 23 standard benchmark functions and six composite test functions. Escape velocity gravitational search algorithm (EVGSA) has been compared with some well-known heuristic search algorithms such as GSA, genetic algorithm (GA), particle swarm optimization (PSO), and recently the new algorithm dragonfly algorithm (DA). Wilcoxon signed-rank tests were also utilized to execute statistical analysis of the results obtained by GSA and EVGSA. Standard and composite benchmark tables and Wilcoxon signed-rank test and visual results show that EVGSA is more powerful than other algorithms.
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, Halil
Since 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.
ENERJİ VERİMLİ İŞBİRLİKÇİ DTV SPEKTRUM ALGILAMA
(Gazi Univ, Fac Engineering Architecture, 2013) Kulaç, Selman; Sazlı, Murat Hüsnü
Gelişmekte olan bilişsel radyoda spektrum algılama kalitesinin iyi olması önem arz etmektedir. Etkin spektrum algılama yöntemlerinden birisi de pilot ton algılama yöntemidir. DTV (Sayısal TV) pilot enerji algılamada, 6 MHz’lik DTV kanalı için enerji toplamı yerine, sadece pilot sinyali frekans bölgesindeki genlik değerleri ile enerji toplamı hesaplanarak ciddi anlamda hesaplama tasarrufu sağlanması ile de enerji tasarrufu sağlanabilmektedir. Fakat bir alıcıda, 6 MHz’lik bir DTV kanalına odaklanmak yerine sadece bir pilot sinyali ile ilgilenilmesi ile direkt pilot sinyalinin derin sönümlemeye uğraması durumunda algılamanın yapılamaması olasılığı da vardır. Bu çalışmada, yenilikçi bir yaklaşımla, işbirlikçi yapı ile Goertzel algoritmasından yararlanarak ve sadece pilot sinyali dar bandında enerji algılama yapılması durumunda, tüm işbirlikçi alıcılara gelen pilot sinyalinin derin sönümlemeye uğrama olasılığının çok düşük olduğu ve spektrum algılama kalitesi yanında toplamda enerji verimliliğinin de arttığı yapılan detaylı benzetimlerle gösterilmiştir.
Genetic algorithms to determine the critical values of a power energy system for different operating conditions
(Sila Science, 2012) Kandara, Osman; Öztürk, Ali
Critical values of a power system are the values of load bus active power, load bus voltage amplitude, and load bus angle when the load bus has the highest active power value. These values depend on various factors such as the length, voltage, the number, and the serial and shunt compensation rates of the line. In this study, we take the IEEE's 6-bus power system as our base system. We first used the Newton Raphson (NR) method to determine the critical values under various operating conditions. Then, we used genetic algorithms, which is an artificial intelligence method commonly used in optimization, to determine the critical values under the same operating conditions. At the end, we compared the results. The results show that overall the critical values determined using GA is as good as with or better than those obtained using the traditional NR method.
Experimental Performance Investigation of a Novel Magnetic Levitation System
(Ieee-Inst Electrical Electronics Engineers Inc, 2013) Hasırcı, Uğur; Balıkçı, Abdulkadir; Zabar, Zivan; Birenbaum, Leo
This paper deals with the design, construction, and especially the testing of a new magnetic levitation (maglev) train driven by an air-cored tubular linear induction motor. The proposed new design topology uses only one force-generating system (motor) to produce the three forces required in a maglev system: propulsion, levitation, and guidance, whereas classical maglev trains use separate motors or permanent magnets to produce each of these forces. Moreover, the system eliminates the need for control of the levitation and guidance forces. This paper presents a condensed design guideline, simply explains the implementation process of a laboratory-scale prototype, shows in detail the experimental test results-including the low-damping problem-and then addresses the advantages of the proposed system over existing maglev systems.
Experimental performance comparison of a 2-axis sun tracking system with fixed system under the climatic conditions of Duzce, Turkey
(Tubitak Scientific & Technical Research Council Turkey, 2016) Öztürk, Ali; Alkan, Selman; Hasırcı, Uğur; Tosun, Salih
In this study, an experimental performance comparison of a 2-axis tracking system with a fixed panel in a solar renewable energy system is conducted. The paper mainly focuses on a cost benefit analysis of fixed and tracking modules. For this aim, an experimental setup was built and periodical measurements were then obtained from the setup. To provide a better comparison, the panels were exposed to the same conditions during the measurements. By considering the real-time experimental results, the paper provides a quantitative analysis of the feasibility of tracking panels for domestic applications as well as an analysis of payback period if a tracking system is used for a home-building application instead of using a conventional fixed module. The study is restricted to the geographical region of Duzce, Turkey.
Electrical & mechanical diagnostic indicators of wind turbine induction generator rotor faults
(Pergamon-Elsevier Science Ltd, 2019) Zappala, Donatella; Sarma, Nur; Djurovic, Sinisa; Crabtree, Cristopher J.; Mohammad, Anees; Tavner, P.J.
In MW-sized wind turbines, the most widely-used generator is the wound rotor induction machine, with a partially-rated voltage source converter connected to the rotor. This generator is a significant cause of wind turbine fault modes. In this paper, a harmonic time-stepped generator model is applied to derive wound rotor induction generator electrical & mechanical signals for fault measurement, and propose simple closed-form analytical expressions to describe them. Predictions are then validated with tests on a 30 kW induction generator test rig. Results show that generator rotor unbalance produces substantial increases in the side-bands of supply frequency and slotting harmonic frequencies in the spectra of current, power, speed, mechanical torque and vibration measurements. It is believed that this is the first occasion in which such comprehensive approach has been presented for this type of machine, with healthy & faulty conditions at varying loads and rotor faults. Clear recommendations of the relative merits of various electrical & mechanical signals for detecting rotor faults are given, and reliable fault indicators are identified for incorporation into wind turbine condition monitoring systems. Finally, the paper proposes that fault detectability and reliability could be improved by data fusion of some of these electrical & mechanical signals. (C) 2018 The Authors. Published by Elsevier Ltd.
Effective cooperative DTV detection using the Goertzel algorithm
(Tubitak Scientific & Technical Research Council Turkey, 2015) Kulaç, Selman; Sazlı, Murat Hüsnü
In digital TV (DTV) detection, to monitor the DTV spectrum, only pilot tone frequency values can be observed in order to achieve calculation and energy savings. These savings can be achieved using the Goertzel algorithm. However, more than one receiver sensor is needed in order to increase the detection quality. In this technique, the Goertzel algorithm is used for energy-efficient pilot tone detection and a new effective cooperative structure is proposed. There is no extra fusion center and more than one DTV band can be monitored with this OR rule-based cooperative structure. With this new cooperative structure, reaching the desired levels of ROC curves for probability of detection and probability of false alarm with the total energy efficiency is also demonstrated with detailed simulations for all DTV multipath profiles.
Direction Finding in the Presence of Direction-Dependent Mutual Coupling
(Ieee-Inst Electrical Electronics Engineers Inc, 2017) Elbir, Ahmet Musab
Direction-of-arrival (DOA) estimation in the presence of mutual coupling (MC) is an important problem in direction-finding applications. Previous methods in the literature assume that the MC in the array is modeled with a single direction-independent MC matrix. However, this assumption is not valid in practice where the effect of MC varies for different directions. In this letter, a new method is proposed in order to estimate both source DOA angles and MC coefficients in the presence of direction-dependent MC. The proposed method iteratively estimates the source DOA angles using the MUSIC algorithm. In order to estimate the direction-dependent MC coefficients, a unified transformation approach is proposed, which can be applied for any array geometry. Then, a convex minimization problem is outlined using the signal-noise subspace orthogonality. The performance of the proposed method is evaluated for uniform linear and circular arrays. It is shown that the proposed method effectively estimates both source and array coupling parameters and it has superior performance than the conventional techniques.
Determination of voltage stability boundary values in electrical power systems by using the Chaotic Particle Swarm Optimization algorithm
(Elsevier Sci Ltd, 2015) Kuru, Leyla; Öztürk, Ali; Kuru, Ersen; Kandara, O.
A power system has critical values which are the limit values of voltage stability. These values are the highest active power taken by the load busses, voltage amplitude and the angle of the busses. In this research the critical values in electric power systems are defined with use of Chaotic Particle Swarm Optimization (CPSO) algorithm. In this study CPSO has been aimed to use logistic map and Henon map as chaotic maps to control the values of the parameters in velocity update formulation. Initially, critical values of voltage stability have been found by simple Particle Swarm Optimization (PSO). Then the same values have been found with CPSO. Accordingly, the results have been evaluated and observed that the stability critical values found by CPSO can be used to produce good potential solutions. Simulation results are promising and show the effectiveness of the applied approach. (C) 2014 Elsevier Ltd. All rights reserved.
Determination of Effective Mode Selection for Ensuring Spectrum Efficiency with Massive MIMO in IoT Systems
(Mdpi, 2019) Dikmen, Osman; Kulaç, Selman
Wireless Sensor Networks (WSNs) based on Internet of Things (IoT) applications are increasing day by day. These applications include healthcare, infrastructure monitoring, smart homes, wearable devices and smart cars. However, considering the fact that many different application areas will emerge in next generation wireless communication systems, efficient use of frequency spectrum is important. Because the whole frequency spectrum is now very crowded, it is important to ensure maximum spectrum efficiency for effective WSNs based on IoT. This study sought to determine which mode more effectively achieves spectrum efficiency for the performance of effective IoT systems under given conditions with respect to the length of the pilot sequence, Time Division Duplexing (TDD) or Frequency Division Duplexing (FDD). The results were obtained by Monte Carlo simulations. To the best of our knowledge, a study of effective mode selection analysis for spectrum efficiency in IoT based systems has not been available in the literature yet. The results of this study are useful for determining the appropriate design conditions for WSNs based on IoT.
Design and operation of a multifunction photovoltaic power system with shunt active filtering using a single-stage three-phase multilevel inverter
(Tubitak Scientific & Technical Research Council Turkey, 2017) Sezen, Serkan; Aktaş, Ahmet; Uçar, Mehmet; Özdemir, Engin
In this paper, the control of a multifunction grid-connected photovoltaic (PV) system with a three-phase three level (3L) neutral point clamped (NPC) inverter is proposed, which can perform shunt active filtering. Normally, the shunt active filtering is achieved by detecting the harmonic and reactive currents of the nonlinear load and then injecting the compensating current into the grid. Therefore, the proposed system can inject PV power to a grid with power factor correction and current harmonic filtering features simultaneously. In addition, a single-stage compact and efficient transformerless power conversion topology is used in this paper for the grid-connected solar PV system with maximum power point tracking capability. In order to control the multilevel inverter-based combined system, a synchronous reference frame control technique and hysteresis current control pulse width modulation method have been applied. The system configuration and control strategy are verified and validated by simulations based on MATLAB/Simulink and implemented in real-time using the dSPACE DS1103 controller board. The simulation with experimental results indicates that the injected currents are sinusoidal and current total harmonic distortion is about 3.9%, lower than the IEEE 519 harmonic limit.
Weight optimization of a dry type core form transformer by using particle swarm optimization algorithm
(Sila Science, 2012) Demir, Hüseyin; Öztürk, Ali; Kuru, Leyla; Kuru, Ersen
There are two imported parameters affecting the weight of a transformer. These are the iron part and the copper part of a transformer. Reducing the weight is the basic criteria to reduce the cost of a transformer. In this study, a partial swarm optimization (PSO) method is used to optimize the weight of a three phase core form dry type transformer. The total weight of the transformer (G(T)), has been accepted as the goal function. The constraints are added to the fitness function as the penalty function to constrain fitness function values. The efficiency ( ) and (Ls/a) has been taken as constraints. The fitness function has been obtained as a function of current density and transformer iron cross section convenience value. The critical values have been computed using the PSO method and the results have been evaluated. The results are compared with the results of the classical method, described in. The total weight which has been founded by using PSO is less than the weight which is founded with the classical method. The weight of a 1,5 KVA three phase core form dry type transformer, founded by using PSO, is 23.5547 kg whereas the weight, founded by classical method was 30.84 kg. It has been seen that intuitive PSO method is an alternative and better way to estimate the minimum weight values.
V-Shaped Sparse Arrays for 2-D DOA Estimation
(Springer Birkhauser, 2019) Elbir, Ahmet Musab
This paper proposes a new sparse array geometry for 2-D (azimuth and elevation) direction-of-arrival (DOA) estimation. The proposed array geometry is V-shaped sparse array, and it is composed of two linear portions which are crossing each other. The degrees of freedom of the sparse array are enhanced by sparse sampling property. In this respect, V-shaped coprime (VCA) and V-shaped nested array (VNA) structures are developed. VCA can resolve both azimuth and elevation angles up to MN sources with 2M+N-1 sensors in each portion, and the total number of sensors is 4M+2N-3. VNA can resolve O(N2) sources with 2N sensors. Instead of 2-D grid search, the proposed method computes 1-D search for azimuth and elevation angle estimation in a computational efficient way. In order to solve the pairing problem in 2-D scenario, the cross-covariance matrix of two portion is utilized and 2-D paired DOA estimation is performed. The performance of the proposed method is evaluated with numerical simulations, and it is shown that the proposed array geometries VCA and VNA can provide much less sensors as compared to the conventional coprime planar arrays.
Two-Dimensional DOA Estimation via Shifted Sparse Arrays with Higher Degrees of Freedom
(Springer Birkhauser, 2019) Elbir, Ahmet Musab
Sparse antenna arrays provide larger virtual arrays to estimate the direction of arrivals (DOAs) of more sources than the number of physical antennas in the array. While the degrees of freedom (DOF) can be increased by the special structure of the antenna array, a shift in the antenna positions can generate new lags in the difference co-array; hence, more sources can be resolved. In this paper, we propose shifted sparse array structures composed of two overlapping arrays shifted by one lag. It is shown that the shifting property fills the holes in the co-array, which yields larger virtual arrays. We derive stationary and moving array models where overlapping sparse arrays can be realized. The proposed shifting property is applied to coprime, nested and sparse linear arrays, and we show that the proposed technique guaranteed to increase the DOF. Using the proposed sparse array structures, we also propose a 2-D DOA estimation algorithm by utilizing the cross-covariance matrix of an L-shaped sparse array. The performance of the proposed approach is evaluated through numerical simulations, and we show that it can resolve more sources than the conventional sparse arrays with the same number of physical antennas, providing less computational complexity.
Symbiotic organisms search algorithm for economic load dispatch problem with valve-point effect
(Elsevier Science Bv, 2018) Güvenç, Uğur; Duman, Serhat; Sönmez, Yusuf; Kahraman, H. Tolga; Döşoğlu, M. Kenan
Symbiotic Organisms Search (SOS) is a brand new and effective metaheuristic optimization algorithm. This paper proposes the SOS algorithm to solve the Economic Load Dispatch (ELD) problem with valve-point effect, which is one of the essential optimization problems in modern power systems. The proposed algorithm is tested on five different test cases consisting of 3-machine 6-bus, IEEE 5-machine 14-bus, IEEE 6-machine 30-bus, and 13- and 40-unit test systems both with transmission loss and without transmission loss. These test cases show that SOS is able to converge on the global optima, successfully. Moreover, results obtained from the proposed algorithm are compared through different methods used in solving the ELD problem existing in the literature. According to these results, SOS produces the best values among all methods. (C) 2018 Sharif University of Technology. All rights reserved.
Symbiotic organisms search optimization algorithm for economic/emission dispatch problem in power systems
(Springer, 2018) Döşoğlu, Mehmet Kenan; Güvenç, Uğur; Duman, Serhat; Sönmez, Yusuf; Kahraman, H. Tolga
This paper presents symbiotic organisms search (SOS) algorithm to solve economic emission load dispatch (EELD) problem for thermal generators in power systems. The basic objective of the EELD is to minimize both minimum operating costs and emission levels, while satisfying the load demand and all equality-inequality constraints. In other research direction, this multi-objective problem is converted into single-objective function by using price penalty factor approach in order to solve it with SOS. The proposed algorithm has been implemented on various test cases, with different constraints and various cost curve nature. In order to see the effectiveness of the proposed algorithm, its results are compared to those reported in the recent literature. The results of the algorithms indicate that SOS gives good results in both systems and very competitive with the state of the art for the solution of the EELD problems.
SRF Based Output Voltage Control of 3-Level 3-Phase 4-Leg AT-NPC Inverter
(Gazi Univ, 2018) Avcı, Emre; Uçar, Mehmet
This paper proposes a synchronous reference frame (SRF) based high performance output voltage controller for the 3-level 3-phase 4-leg (3P4L) advanced T-type neutral point clamped (AT-NPC) inverter operated in stand-alone mode. 3-phase inverters for standalone operation are required to provide 3-phase balanced nominal voltage under different load types such as unbalanced linear and non-linear loads. 3P4L inverters working with these types of load allow controlling zero sequence voltage by additional fourth leg. The main contribution of this work is the control of the 3-level 3P4L AT-NPC inverter with an LC-type filter modeled based on the output voltage and capacitor current feedback in the synchronous coordinate system. According to obtained capacitor current decoupled model, double loop PI controller is adopted to control the output voltage of the inverter. An inner capacitor current feedback loop is employed to provide fast dynamic response and active damping of the capacitor current. Finally, transient and steady state operation performance of the controller have been tested with PSIM simulation studies considering different load types. Simulation results validate that the proposed SRF based double loop PI controller ensure high dynamic response and high quality output voltage with less than 3% total harmonic distortion (THD) value for the 3-level 3P4L AT-NPC inverter.
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, Emre
Reactive 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.
Sensor array calibration with joint-block-sparsity in the presence of multiple separable observations
(Springer London Ltd, 2019) Elbir, Ahmet Musab
In sparsity-based optimization problems, one of the major issue is computational complexity, especially when the unknown signal is represented in multi-dimensions such as in the problem of 2-D (azimuth and elevation) direction-of-arrival (DOA) estimation. In this paper, a low-complexity sparsity-based method is proposed for DOA estimation in the presence of array imperfections such as mutual coupling. In order to reduce the complexity of the optimization problem, this paper introduces a new sparsity structure that can be used to model the optimization problem in case of multiple data snapshots and multiple separable observations where the dictionary can be decomposed into two parts: azimuth and elevation dictionaries. The proposed sparsity structure is called joint-block-sparsity which exploits the sparsity in both multiple dimensions, namely azimuth and elevation, and data snapshots. In order to model the joint-block-sparsity in the optimization problem, triple mixed norms are used. In the simulations, the proposed method is compared with both sparsity-based techniques and subspace-based methods as well as the Cramer-Rao lower bound. It is shown that the proposed method effectively calibrates the sensor array with significantly low complexity and sufficient accuracy.

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