Salih Tosun

Simulated annealing based passive power filter design for a medium voltage power system

Power quality problems on distribution systems are becoming an increasingly important issue because the increase of harmonic current sources not only caused poor supply quality but also can be damaged the system components. As is known passive power filters (PPFs) have been mostly used to restrict the harmonic currents in industrial distribution systems. Aim of this paper is PPF design according to IEEE standards by using simulated annealing (SA) which is one of the heuristic techniques. The main idea behind the PPF design is the minimization of rms current of distribution bus. First of all harmonic analysis of studied industrial power system has been done. After this analysis, PPF design for mitigation of current harmonics and also power factor correction is realized firstly by using the try and error (TAE) method taking into consideration IEEE 519-1992 standards. Similar to that PPF design is realized by using proposed SA method. Effectiveness and convenience of the designed single tuned PPFs in limitation of the harmonic distortions are analyzed via computer simulations. Simulation studies are carried out in Matlab/Simulink environment.

AN APPROACH FOR DESIGNING PASSIVE POWER FILTERS FOR INDUSTRIAL POWER SYSTEMS BY USING GRAVITATIONAL SEARCH ALGORITHM

Original scientific paper Harmonics are one of the important factors in determining the energy quality in power systems. Hence, eliminating or damping undesired harmonics is crucial in electrical power systems. Due to their low costs, Passive Power Filters (PPF) are widely used in industrial power systems to limit harmonics’ undesired affects. In this study, a new approach to design a PPF for power systems using heuristic Gravitational Search Algorithms (GSA) is proposed. Traditional Try and Error (TAE) method is, first, utilized to eliminate harmonics in our model power system. Then, GSA is adopted to minimize the effective current value of Point of Common Coupling (PCC) in the same model system. Our results yield that our proposed method with GSA eliminates the harmonics effectively.

THE EVALUATION OF MUNICIPAL SOLID WASTES AS ENERGY SOURCE

The waste combustion is a burning method in which wastes are burned under controlled conditions to produce energy under optimal conditions with a reduction in waste volume of 100-1000 times. Although this method is preferred due to the high energy gain, it is criticized in some societies due to the formation of some toxic combustion products and gases and high initial investment cost. The thermal processing or pyrolysis method is a method that brings out innovative technologies and designs around the world because of environmental factors as well as economic improvements. Municipal solid wastes can be disposed by the pyrolysis method which gained popularity in recent years, by producing economical value of the obtained thermal processing liquid and syngas and also the electricity can be produced during the process. In this study, the methods aforementioned in terms of energy production from municipal solid wastes were examined and an evaluation was made for Turkey .

Investigating voltage stability problem in the electrical power system using gravitational search algorithms

This study aims to utilize the Gravitational Search Algorithm (GSA) to find the optimal values of the proportional integral derivative (PID) controller parameters to control the automatic voltage regulator (AVR). GSA is categorized as a heuristic algorithm. In finding the optimal values, we try to minimize the performance index also called the error in the closed loop control diagram. We observed and compared the three different situations of the error, namely the integrated absolute error (IAE), the integral of squared error (ISE), and the integral time absolute error (ITAE). We, then, employed a conventional Ziegler-Nicolas Method (ZNM) to find the optimal values under the same conditions with GSA. The values obtained through both methods are compared at the end. We show that the proposed method using GSA has a better performance than ZNM in terms of settling time, oscillations and overshoot. We also compared our results with the ones obtained through Genetic Algorithms (GA). Similarly, our method performs better.

Speed control of wind turbine rotor using genetic algorithm

In wind farms, rotor speed control of generator is essential to generate appropriate electric energy. In this study, squirrel cage induction generator (SCIG) is used and its rotor speed is controlled with Genetic Proportional-Integral (GPI) method. Determination of PI coefficients providing SCIG to operate reference rotor speed promptly is obtained with Genetic Algorithm (GA) known as an optimization method. In addition, sensorless control of rotor speed is carried out with field oriented control (FOC). To do this purpose, the transfer function of rotor speed control of induction machine is created and employed in simulation model. Used in this control, PI coefficients, firstly, are obtained with a classical method called Ziegler-Nichols Method (ZNM) and then is obtained with GA. Wind turbine (WT) model created with Matlab/Simulink are used to operate the system simulation for these different methods which determine the PI coefficients. The system simulation of the results for ZNM and GA are compared. It is clearly seen that the results which are operated with PI coefficients calculated by GA is better than the others in the respect of reaching time to reference speed and determination.

Determination of voltage stability critical loading values using Simulated Annealing

In this study, critical bus values in a power system are determined by using simulated annealing (SA) algorithm. As an example, a power system which contains the slack, generator and load buses is analyzed. Firstly, load value of the selected load bus is augmented step-by-step and load flow analysis is done for each case. This process is continued till there is no solution and in this way the critical bus values that are limit values of voltage stability are obtained. Secondly, by using SA algorithm, critical values are directly determined without augmenting the load of the selected load bus. The results show that the critical values can be easily determined using SA.