Improved Step Response of Power System Stabilizer using Fuzzy Logic Controller

As every power system is constantly being subjected to disturbances, we should see that these disturbances do not make the system unstable. Therefor additional signals derived from speed deviation, excitation deviation and accelerating power are injected into voltage regulators. The device to provide these signals is referred as power system stabilizer. The use of power system stabilizers has become very common in operation of large electric power systems. The conventional PSS which uses lead-lag compensation, where gain settings designed for specific operating conditions, is giving poor performance under different loading conditions. Therefore, it is very difficult to design a stabilizer that could present good performance in all operating points of electric power systems. In an attempt to cover a wide range of operating conditions, Fuzzy logic control has been suggested as a possible solution to overcome this problem. In this paper, a systematic approach to fuzzy logic control design is proposed. The study of fuzzy logic power system stabilizer for stability enhancement of a single machine infinite bus system is presented. In order to accomplish the stability enhancement, speed deviation and acceleration of the rotor synchronous generator are taken as the inputs to the fuzzy logic controller. These variables take significant effects on damping the generator shaft mechanical oscillations. The stabilizing signals were computed using the fuzzy membership function depending on these variables. The performance of the system with fuzzy logic based power system stabilizer is compared with the system having conventional power system stabilizer and system without power system stabilize

A Novel Impedance Measurement Technique for Power Electronic Systems

When designing and building power systems that contain power electronic switching sources and loads, system integrators must consider the frequency-dependent impedance characteristics at an interface to ensure system stability. Stability criteria have been developed in terms of source and load impedance for both dc and ac systems and it is often necessary to measure system impedance through experiments. Traditional injection-based impedance measurement techniques require multiple online tests which lead to many disadvantages. The impedance identification method proposed in this paper greatly reduces online test time by modeling the system with recurrent neural networks. The recurrent networks are trained with measured signals from the system with only one injection. The measurement and identification processes for dc and three-phase ac interfaces are developed. Simulation tests demonstrate the effectiveness of this new technique

Implementation of Recurrent Neural Network to Control Rotational Inverted Pendulum using IMC Scheme

Abstract: Problem statement:This paper presents an overview of a controller for a Rotational Inverted Pendulum (RIP) based on a New Recurrent Neural Network (NRNN) using Internal Model control (IMC). The RIP consists of a DC servo motor, arm and pendulum. The RIP is modelled in MATLAB/Simulink and the simulation results are shown besides the experimental results. The proposed experiment shows intelligent method for stabilizing the RIP, which can recommend the control designers of nonlinear systems. The outcome exposed that the NRNN controller competent of controlling the RIP system productively, as exposed in the simulation results

New techniques to improve power quality and evaluate stability in modern all-electric naval ship power systems

This dissertation focuses on two crucial issues in the design and analysis of the power electronic systems on modern all-electric naval ships, i.e., power quality control and stability evaluation. It includes three papers that deal with active power filter topology, active rectifier control, and impedance measurement techniques, respectively. To mitigate harmonic currents generated by high-power high-voltage shipboard loads such as propulsion motor drives, the first paper proposes a novel seven-level shunt active power filter topology, which utilizes tapped reactors for parallel operations of switching devices. The multi-level system has been implemented in both regular digital simulation and real-time digital simulator for validation. In the second paper, a harmonic compensation algorithm for three-phase active rectifiers is proposed. Based on the theory of multiple reference frames, it provides fast and accurate regulation of selected harmonic currents so that the rectifier draws balanced and sinusoidal currents from the source, even when the input voltages are unbalanced and contain harmonics. Extensive laboratory tests on a 2 kW prototype system verifies the effectiveness of the proposed control scheme. The last paper presents a new technique for impedance identification of dc and ac power electronic systems, which significantly simplifies the procedure for stability analysis. Recurrent neural networks are used to build dynamic models of the system based on a few signal injections, then the impedance information can be extracted using off-line training and identification algorithms. Both digital simulation and hardware tests were used to validate the technique --Abstract, page iv