Mehmet Demirtas

dSPACE based control of voltage source utility interactive inverter

Interest of renewable energy sources increases with the increasing world power demand and decreasing of fossil energy sources. Many of the new energy sources like the PV, the fuel cell or the wind, produces direct voltage so it is needed a suitable direct current to alternating current inverter to connect them to an alternating current load or the utility line. In this case utility interactive inverters became more important. In this study, a dSPACE based current controlled utility interactive inverter has been designed and implemented. PI current controller was used for the production of switching pattern and the output of the inverter was filtered by an LCL type filter. A graphical user interface has been designed to monitor the analog and the digital variables. Results of both MATLAB/Simulink simulation and experimental studies show that inverter output current is in phase with line voltage and current harmonics in the limits of international standards (<5%).

Low-cost and high sensitive microcontroller based data acquisition system for renewable energy sources

This paper describes the design and implementation of a data acquisition card for the hybrid energy system. Parameters of the solar and the wind sources such as the current, the voltage, the direction of wind, the operation conditions and the position of the solar system can be changed and illustrated on an LCD and displayed on a PC using the card developed. The hybrid system including a PIC 18F452 and a 18F2550 microcontroller has been tested on a 2.5 kW solar panel and a 2.5 kW wind turbine. It has been observed that this hybrid system works successfully and gives good performance such as low cost and easy programming.

Prediction of solar radiation using meteorological data

Solar radiation prediction has a great importance in electricity generation from solar energy and helps to size photovoltaic power systems. Therefore, the solar radiation parameter was predicted at 10-min intervals in this study. Outside temperature, outside humidity and barometric pressure parameters were used as meteorological input variables by the developed k-nearest neighbor (k-NN) classifier. On the one hand, it is mined that solar radiation prediction was affected by the number of nearest neighbors, the dimension of input parameters and the type of distance metrics. On the other hand, it is shown that the k-NN classifier which uses Euclidean distance metric for k=4 in 3-dimensional input space outperformed the other models in terms of the prediction accuracy. Adversely, the k-NN classifier which only uses barometric pressure input provided the weakest prediction performance for k=15 in Euclidean distance metric.

Design, optimisation and application of a resonant DC link inverter for solar energy systems

Purpose – The purpose of this paper is to examine diminish switching losses in a solar energy conversion system in order to utilise the full efficiency of a solar panel. Design/methodology/approach – In this paper, a boost converter and a resonant DC link (RDCL) inverter are controlled by a microcontroller. The maximum power point tracker (MPPT) algorithm implemented for boost converter supplies to track maximum power point of solar panel. The Class D full-bridge resonant inverter (RI) that is considered to be supplied by boost converter is modeled and zero voltage switching operation is performed by controlling the inverter with sinusoidal pulse width modulation (SPWM) control scheme. The control algorithm is managed with a feedback detecting the current of the boost converter and the zero voltage levels of capacitor voltage in the resonant circuit. Findings – There are several control techniques have been proposed to reduce switching losses and harmonic contents in conventional or RDCL inverters. Solar ...

Building of W&S energy system

This study introduces building and operation of a wind and a solar power sources as a clean energy park. This park includes efficient wind and solar power sources that are controlled by a PIC microcontroller to manage the energy storage in batteries and the parallel connection of the system with the grid. There are 14 solar panels producing 2.5 kW in total and a 2.5 kW wind turbine installed in the system. Alternating current energy obtained from wind turbine and direct current energy obtained from solar panels are collected on the direct current bar, where the level of the direct current voltage is kept constant. A hybrid system based on microcontroller has been applied in this study to control the power flow in all directions between the wind turbine, the solar panels, the batteries and the grid.

Modeling of meteorological parameters and improving the classification accuracy for the wind turbines

In this study novel solutions are presented for challenge subjects such as the weighting of wind energy parameters and classifying of meteorological data that should be consider in the installation of wind turbines. For this purpose, the relationships between the meteorological parameters and wind turbines are explored with an intuitive k-Nearest Neighbor algorithm. Thus, the effects of meteorological data on the power of wind turbines are modeled. In the experimental studies the power class of wind turbines is determined depending on the weighted and unweighted parameters and the performances of various classifiers are compared. The results show that the intuitive classification algorithm determines the power class of wind turbines successfully and produce more correct results than classic k-NN approach.

Design and simulation of a drive system for speed control of travelling wave ultrasonic motor

This paper presents a low cost, user friendly and effective drive system for the speed control of travelling wave ultrasonic motor (TWUSM). Driving frequency and voltage were used as control inputs in the speed control. Driving frequency was adjusted by semiconductor switches existing in a two-phase half-bridge serial-resonant inverter circuit controlled by digital integrated circuits, whereas driving voltage was adjusted by a high performance power supply which has full bridge inverter and rectifier circuits controlled by a microcontroller. The drive system designed was tested under several operating parameters in Orcad PSpice 9.1. The simulation results obtained have demonstrated effective achievements for the speed control of TWUSM and so the drive system is convenient for the speed control applications.

A Parameter Determination System for Wind Turbines Based on Naive Bayes Classification Algorithm

Among the renewable energy types, wind energy gets popularity in these days. To install a new wind energy turbine, measurement and evaluation of the meteorological data are quite important. In this paper, a novel system is developed for the installation of wind turbines. Firstly, necessary data including the speed and the direction of wind, the solar insolation, the ultraviolet radiation and the rainfall are received from a meteorology station, and then data acquired are converted into useful information using a rule-based inference mechanism. Finally, the useful information obtained are evaluated in a Naive Bayes algorithm. The power and the size of wind turbine are determined automatically using data measured. Thus, some complicated calculations including more than parameters related to fields where the large-sized wind turbines will be installed can easily be accomplished by means of the powerful decision support system developed.

ANN controlled single phase inverter for solar energy systems

In this study, a single phase inverter is simulated, designed and implemented for solar-powered systems. The use of inverters converting DC voltage generated to AC voltage with intelligent algorithms is a growing practice recently. Unlike classical algorithms, a novel control algorithm based on artificial neural network has been developed and implemented for the inverter. Artificial neural network training is done with FannTool Program. The inverter capable of learning and making decision changes the switching rates for the specified input and output value. Consequently, the inverter also provides constant output value for variable loads.

Determining Suitability of Locations for Installation of Solar Power Station Based on Probabilistic Inference

This paper presents a novel system is to develop to determine the suitability of a location for installation of solar power stations. Necessary data including speed and direction of wind, solar radiation and rainfall are received from a meteorology station, and data acquired are then converted to the labels. Finally, the labels are evaluated in a Naive Bayes algorithm to determine the suitability of the location for the installation and axial structure of a Solar Power Plant. This helps to determine complicated calculations by means of the support system developed.