Fuzzy controller tuning of a boost rectifier unity power factor correction by experimental designs

This paper shows the validity of experimental designs as an efficient on-site tuning tool for fuzzy controllers, dedicated to electrical engineering applications with multi-objective criteria. Our purpose is to improve the input and output system characteristics that is to say the global quality of the electrical power in a boost rectifier with unity power factor correction. The desirability notion combines here time dynamic and harmonic criteria, it illustrates the trade-off that has to be satisfied between the different properties

Study on control strategy of the rotary synchronous fixed-length cutting system

According to the characteristics of rotating synchronous fixed-length cutting system and the principle of vector coordinate transformation, it respectively analyzes the mathematical model of three loops which are the position loop, speed loop and current loop of the servo fixed-length cutting system in this paper. In view of the different working conditions of the system and its nonlinear problem, it puts forward that the function of the speed loop is realized by the parameter adaptive fuzzy algorithm; the function of the position loop using is realized by feed forward proportional control algorithm; the function of the current loop is realized by the conventional PI control algorithm. It uses MATLAB to make simulation and verification, the results show that the combined control algorithm can make that the fixed-length cutting system has characteristics of fast speed, high precision and strong robustness properties

High-performance motor drives

This article reviews the present state and trends in the development of key parts of controlled induction motor drive systems: converter topologies, modulation methods, as well as control and estimation techniques. Two- and multilevel voltage-source converters, current-source converters, and direct converters are described. The main part of all the produced electric energy is used to feed electric motors, and the conversion of electrical power into mechanical power involves motors ranges from less than 1 W up to several dozen megawatts

Power Converter of Electric Machines, Renewable Energy Systems, and Transportation

Power converters and electric machines represent essential components in all fields of electrical engineering. In fact, we are heading towards a future where energy will be more and more electrical: electrical vehicles, electrical motors, renewables, storage systems are now widespread. The ongoing energy transition poses new challenges for interfacing and integrating different power systems. The constraints of space, weight, reliability, performance, and autonomy for the electric system have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this context, power converters and electric machines assume a key role in enabling higher performance of electrical power conversion. Consequently, the design and control of power converters and electric machines shall be developed accordingly to the requirements of the specific application, thus leading to more specialized solutions, with the aim of enhancing the reliability, fault tolerance, and flexibility of the next generation power systems

Power Quality

Electrical power is becoming one of the most dominant factors in our society. Power generation, transmission, distribution and usage are undergoing signifi cant changes that will aff ect the electrical quality and performance needs of our 21st century industry. One major aspect of electrical power is its quality and stability – or so called Power Quality. The view on Power Quality did change over the past few years. It seems that Power Quality is becoming a more important term in the academic world dealing with electrical power, and it is becoming more visible in all areas of commerce and industry, because of the ever increasing industry automation using sensitive electrical equipment on one hand and due to the dramatic change of our global electrical infrastructure on the other. For the past century, grid stability was maintained with a limited amount of major generators that have a large amount of rotational inertia. And the rate of change of phase angle is slow. Unfortunately, this does not work anymore with renewable energy sources adding their share to the grid like wind turbines or PV modules. Although the basic idea to use renewable energies is great and will be our path into the next century, it comes with a curse for the power grid as power fl ow stability will suff er. It is not only the source side that is about to change. We have also seen signifi cant changes on the load side as well. Industry is using machines and electrical products such as AC drives or PLCs that are sensitive to the slightest change of power quality, and we at home use more and more electrical products with switching power supplies or starting to plug in our electric cars to charge batt eries. In addition, many of us have begun installing our own distributed generation systems on our rooft ops using the latest solar panels. So we did look for a way to address this severe impact on our distribution network. To match supply and demand, we are about to create a new, intelligent and self-healing electric power infrastructure. The Smart Grid. The basic idea is to maintain the necessary balance between generators and loads on a grid. In other words, to make sure we have a good grid balance at all times. But the key question that you should ask yourself is: Does it also improve Power Quality? Probably not! Further on, the way how Power Quality is measured is going to be changed. Traditionally, each country had its own Power Quality standards and defi ned its own power quality instrument requirements. But more and more international harmonization efforts can be seen. Such as IEC 61000-4-30, which is an excellent standard that ensures that all compliant power quality instruments, regardless of manufacturer, will produce of measurement instruments so that they can also be used in volume applications and even directly embedded into sensitive loads. But work still has to be done. We still use Power Quality standards that have been writt en decades ago and don’t match today’s technology any more, such as fl icker standards that use parameters that have been defi ned by the behavior of 60-watt incandescent light bulbs, which are becoming extinct. Almost all experts are in agreement - although we will see an improvement in metering and control of the power fl ow, Power Quality will suff er. This book will give an overview of how power quality might impact our lives today and tomorrow, introduce new ways to monitor power quality and inform us about interesting possibilities to mitigate power quality problems. Regardless of any enhancements of the power grid, “Power Quality is just compatibility” like my good old friend and teacher Alex McEachern used to say. Power Quality will always remain an economic compromise between supply and load. The power available on the grid must be suffi ciently clean for the loads to operate correctly, and the loads must be suffi ciently strong to tolerate normal disturbances on the grid

Adaptive hysteresis based fuzzy controlled shunt active power filter for mitigation of harmonics

Active filters are widely employed in distribution system to reduce the harmonics produced by non-linear loads result in voltage distortion and leads to various power quality problems. In this work the simulation study of a Adaptive hysteresis based fuzzy logic controlled shunt active power filter capable of reducing the total harmonic distortion is presented. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system and it can adapt its gain according to the changes in load. The instantaneous p-q theory is used for calculating the compensating current. Fuzzy-adaptive hysteresis band technique is adopted for the current control to derive the switching signals for the voltage source inverter. The fuzzy-adaptive hysteresis band current controller changes the hysteresis bandwidth according to the supply voltage and slope of the reference compensator current wave. A fuzzy logic-based controller is developed to control the voltage of the DC Capacitor. This work presents and compares the performance of the fuzzy-adaptive controller with a conventional fuzzy and PI controller under constant load. The total Harmonic Distortion, Individual harmonic content with respect to % of fundamental in Supply current, source voltage have been analyzed. Various simulation results are presented. And also the performance of two current control techniques namely adaptive hysteresis current control and fixed hysteresis control techniques are compared with respect to average switching frequency. A neural network control method for regulating the DC Voltage across the capacitor connected to the inverter for harmonic suppression is proposed. The THD of the source current after compensation is well below 5%, the harmonic limit imposed by the IEEE-519 standard

Short-term wind speed forecasting system using deep learning for wind turbine applications

It is very important to accurately detect wind direction and speed for wind energy that is one of the essential sustainable energy sources. Studies on the wind speed forecasting are generally carried out for long-term predictions. One of the main reasons for the long-term forecasts is the correct planning of the area where the wind turbine will be built due to the high investment costs and long-term returns. Besides that, short-term forecasting is another important point for the efficient use of wind turbines. In addition to estimating only average values, making instant and dynamic short-term forecasts are necessary to control wind turbines. In this study, short-term forecasting of the changes in wind speed between 1-20 minutes using deep learning was performed. Wind speed data was obtained instantaneously from the feedback of the emulated wind turbine's generator. These dynamically changing data was used as an input of the deep learning algorithm. Each new data from the generator was used as both test and training input in the proposed approach. In this way, the model accuracy and enhancement were provided simultaneously. The proposed approach was turned into a modular independent integrated system to work in various wind turbine applications. It was observed that the system can predict wind speed dynamically with around 3% error in the applications in the test setup applications