Fuzzy Algorithm for Supervisory Voltage/Frequency Control of a Self Excited Induction Generator

This paper presents the application of a Fuzzy Logic Controller (FLC) to regulate the voltage of a Self Excited Induction Generator (SEIG) driven by Wind Energy Conversion Schemes (WECS). The proposed FLC is used to tune the integral gain (KI) of a Proportional plus Integral (PI) controller. Two types of controls, for the generator and for the wind turbine, using a FLC algorithm, are introduced in this paper. The voltage control is performed to adapt the terminal voltage via self excitation. The frequency control is conducted to adjust the stator frequency through tuning the pitch angle of the WECS blades. Both controllers utilize the Fuzzy technique to enhance the overall dynamic performance.  The simulation result depicts a better dynamic response for the system under study during the starting period, and the load variation. The percentage overshoot, rising time and oscillation are better with the fuzzy controller than with the PI controller type.

Alone Self-Excited Induction Generators

In recent years, some converter structures and analyzing methods for the voltage regulation of stand-alone self-excited induction generators (SEIGs) have been introduced. However, all of them are concerned with the three-phase voltage control of three-phase SEIGs or the single-phase voltage control of single-phase SEIGs for the operation of these machines under balanced load conditions. In this paper, each phase voltage is controlled separately through separated converters, which consist of a full-bridge diode rectifier and one-IGBT. For this purpose, the principle of the electronic load controllers supported by fuzzy logic is employed in the two-different proposed converter structures. While changing single phase consumer loads that are independent from each other, the output voltages of the generator are controlled independently by three-number of separated electronic load controllers (SELCs) in two different mode operations. The aim is to obtain a rated power from the SEIG via the switching of the dump loads to be the complement of consumer load variations. The transient and steady state behaviors of the whole system are investigated by simulation studies from the point of getting the design parameters, and experiments are carried out for validation of the results. The results illustrate that the proposed SELC system is capable of coping with independent consumer load variations to keep output voltage at a desired value for each phase. It is also available for unbalanced consumer load conditions. In addition, it is concluded that the proposed converter without a filter capacitor has less harmonics on the currents

Robust fuzzy PSS design using ABC

This paper presents an Artificial Bee Colony (ABC) algorithm to tune optimal rule-base of a Fuzzy Power System Stabilizer (FPSS) which leads to damp low frequency oscillation following disturbances in power systems. Thus, extraction of an appropriate set of rules or selection of an optimal set of rules from the set of possible rules is an important and essential step toward the design of any successful fuzzy logic controller. Consequently, in this paper, an ABC based rule generation method is proposed for automated fuzzy PSS design to improve power system stability and reduce the design effort. The effectiveness of the proposed method is demonstrated on a 3-machine 9-bus standard power system in comparison with the Genetic Algorithm based tuned FPSS under different loading condition through ITAE performance indices

FUZZY LOGIC CONTROL FOR MULTI-MACHINE POWER SYSTEM

Stability enhancement is of great importance in power system design. Excitation control and static var compensator (SVC) play important roles in stability enhancement of power system. In this paper, an indirect adaptive fuzzy excitation control is proposed to enhance transient stability for the power system, which based on input-output linearization technique. A three-bus system, which contains a generator and static var compensator (SVC) is considered in this paper, the SVC is located at the midpoint of the transmission lines. Simulation results show that the proposed controller can enhance the transient stability of the power system under a large sudden fault, which may occur nearly at the generator bus terminal

A shape memory alloy adaptive tuned vibration absorber: design and implementation

In this paper a tuned vibration absorber (TVA) is realized using shape memory alloy (SMA) elements. The elastic modulus of SMA changes with temperature and this effect is exploited to develop a continuously tunable device.A TVA with beam elements is described, a simple two-degree-of-freedom model developed and the TVA characterized experimentally. The behaviour during continuous heating and cooling is examined and the TVA is seen to be continuously tunable. A change in the tuned frequency of 21.4% is observed between the cold, martensite, and hot, austenite, states. This corresponds to a change in the elastic modulus of about 47.5%, somewhat less than expected.The response time of the SMA TVA is long because of its thermal inertia. However, it is mechanically simple and has a reasonably good performance, despite the tuning parameters depending on the current in a strongly nonlinear way

Design of Power System Stabilizer

A power system stabilizer (PSS) installed in the excitation system of the synchronous generator improves the small-signal power system stability by damping out low frequency oscillations in the power system. It does that by providing supplementary perturbation signals in a feedback path to the alternator excitation system. In our project we review different conventional PSS design (CPSS) techniques along with modern adaptive neuro-fuzzy design techniques. We adapt a linearized single-machine infinite bus model for design and simulation of the CPSS and the voltage regulator (AVR). We use 3 different input signals in the feedback (PSS) path namely, speed variation(w), Electrical Power (Pe), and integral of accelerating power (Pe*w), and review the results in each case. For simulations, we use three different linear design techniques, namely, root-locus design, frequency-response design, and pole placement design; and the preferred non-linear design technique is the adaptive neuro-fuzzy based controller design. The MATLAB package with Control System Toolbox and SIMULINK is used for the design and simulations