Nuran Yorukeren

Application of gravitational search algorithm for optimal reactive power dispatch problem

In this paper, Gravitational Search Algorithm (GSA) is applied to solve the optimal reactive power dispatch (ORPD) problem. The ORPD problem is formulated as a nonlinear constrained single-objective optimization problem where the real power loss and the bus voltage deviations are to be minimized separately. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system consisting 6 generator and compared other algorithms reported those before in literature. Results show that GSA is more efficient than others for solution of single-objective ORPD problem.

Optimal power flow incorporating FACTS devices using Gravitational Search Algorithm

This paper aims to solve the optimal power problem (OPF) incorporating flexible AC transmission systems (FACTS) devices using Gravitational Search Algorithm (GSA) that minimizes the fuel cost function in the problem. In the optimization problem, Thyristor controlled series compensation (TCSC) and thyristor controlled phase shifter (TCPS) FACTS devices are considered to find their optimum location in transmission lines. In order to evaluate the effectiveness of proposed algorithm, it has been tested on modified IEEE 30 bus system and compared with particle swarm optimization (PSO) and hybrid tabu search and simulated annealing (TS/SA) approach which are used in solving the same problem and reported before in the literature. Results show that GSA produces better results than others and has fast computing time for solving OPF problem with FACTS.

Load frequency control of a single area power system using Gravitational Search Algorithm

In this paper, a novel heuristic search method called Gravitational Search Algorithm (GSA) is proposed for determination of the optimal proportional-integral (PI) and proportional-integral-derivate (PID) parameters in load frequency control of a single area power system. A single area non reheat thermal system is considered to design the PI and PID controllers which have optimized parameters obtained using GSA. The effectiveness of the proposed PI and PID controllers are compared with those of conventional PI controller. The simulation results show that the enhanced PI and PID controllers with the proposed approach provide a better damping of oscillations compared to those of conventional PI controller in power system.

A novel MPPT algorithm based on optimized artificial neural network by using FPSOGSA for standalone photovoltaic energy systems

Maximum power point tracking (MPPT) algorithms are used to maximize the output power of the photovoltaic (PV) panel under different temperature and irradiance conditions in photovoltaic energy sources (PVES). In this paper, a novel MPPT method based on optimized artificial neural network by using hybrid particle swarm optimization and gravitational search algorithm based on fuzzy logic (FPSOGSA) is proposed to track the operation of the PV panel in maximum power point (MPP). The performance of the proposed MPPT approach is tested by doing the simulation and experimental studies under different environmental conditions. The proposed method is compared with the conventional perturb and observation (P&O) method for standalone PVES. The results of the comparison the obtained from the simulation and experimental studies demonstrate that the proposed MPPT method provides the reduction oscillations around the MPP and the increased maximum power yield of the PV system in the steady state.

A novel FACTS based on modulated power filter compensator for wind-grid energy systems

This paper represents a novel FACTS based on modulated power filter compensator (MPFC) for voltage stabilization in renewable wind energy with AC grid connected. Self-excited squirrel-cage induction generator (SEIG) is driven by a wind turbine for renewable a wind energy system. In order to improve voltage stabilization and energy utilization, the proposed FACTS technique is driven by a tri-loop dynamic error driven proportional-integral-derivate (PID) controller. To demonstrate the effectiveness of the proposed FACTS technique, a simulation model is developed for different operation conditions in MATLAB/SIMULINK software environment. Simulation results demonstrate that designed FACTS power filter compensator can be used to provide voltage regulation and efficient energy utilization.

The Evaluation of Medium Voltage Motor`s Current and Voltage Harmonics during Loading

This paper presents the results of investigating harmonic levels on medium voltage motors at loading conditions in air separation plant. The essential results of the measurements of the medium voltage motor harmonics are summarized in the values for the total harmonic distortion (THD). Motors loading case is used to assess the current and voltage harmonic distortions. Proper system analysis is important when adding a new motor starting and controlling the equipment. With the result of the paper it is possible to suggest the most appropriate starting and control method. Two medium voltage motors of air separation unit measurement results and simulations are summarized. Both current and voltage harmonic distortions are fitted by using a linear and exponential regression model. The prediction of THD values can be used for this kind of process for future planning by utilities.

An artificial neural-net based method for predicting distribution transformer’s total harmonic distortions

This paper presents a new method for predicting distribution transformerpsilas total current and total voltage harmonic distortion with artificial neural network. The method is based on the backpropagation learning technique. This paper shows the proposed method is promising in total harmonic distortion prediction. For better system planning it is necessary to analyze and predict the behavior of harmonics. By predicted values system planners take an appropriate strategy to decrease significant harmonics in distribution systems.