Fahmy M. Bendary

LMI static output-feedback design of fuzzy power system stabilizers

The design of a model-free fuzzy power system stabilizer (PSS) lacks systematic stability analysis and performance guarantees. This paper provides a step towards the design of a model-based fuzzy PSS that guarantees not only stability but also performance specifications of power systems. A new practical and simple design based on static output feedback is proposed. The design guarantees robust pole-clustering in an acceptable region in the complex plane for a wide range of operating conditions. A power system design model is approximated by a set of Takagi-Sugeno (T-S) fuzzy models to account for nonlinearities, uncertainties and large scale power systems. The proposed PSS design is based on parallel distributed compensation (PDC). Sufficient design conditions are derived as linear matrix inequalities (LMI). The design procedure leads to a tractable convex optimization problem in terms of the stabilizer gain matrix. Simulations results of both single-machine and multi-machine power systems confirm the effectiveness of the proposed PSS design.

LMI static output feedback design of fuzzy power system stabilisers

The design of a model-free fuzzy power system stabiliser (PSS) lacks systematic stability analysis and performance guarantees. This paper provides a step towards the design of a model-based fuzzy PSS that guarantees not only stability, but also performance specifications of power systems. A new practical and simple design based on static output feedback is proposed. The design guarantees robust pole clustering in an acceptable region in the complex plane for a wide range of operating conditions. A power system design model is approximated by a set of Takagi-Sugeno (T-S) fuzzy models to account for non-linearities, uncertainties and large-scale power systems. The proposed PSS design is based on parallel distributed compensation (PDC). Sufficient design conditions are derived as linear matrix inequalities (LMIs). The design procedure leads to a tractable convex optimisation problem in terms of the stabiliser gain matrix. Simulations results of both single machine and multimachine power systems confirm the e...

Application of Particle Swarm Optimization in Design of PID Controller for AVR System

This paper presents a method to get the optimal tuning of Proportional Integral Derivative PID controller parameters for an AVR system of a synchronous generator using Particle Swarm Optimization PSO algorithm. The AVR is not initially robust to variations of the power system parameters. Therefore, it was necessary to use PID controller to increase the stability margin and to improve performance of the system. Fast tuning of optimum PID controller parameter yield high quality solution. New criteria for time domain performance evaluation was defined. Simulation for comparison between the proposed method and Ziegler-Nichols method is done. The proposed method was indeed more efficient also. The terminal voltage step response for AVR model will be discussed in different cases and the effect of adding rate feed back stabilizer to the model on the terminal voltage response. Then the rate feedback will be compared with the proposed PID controller based on use of PSO method to find its coefficients. Different simulation results are presented and discussed.

Improved Random Drift Particle Swarm Optimization With Self-Adaptive Mechanism for Solving the Power Economic Dispatch Problem

This paper proposes an improved version of the random drift particle swarm optimization algorithm for solving the economic dispatch problem. The improvement is achieved through adding a crossover operation followed by a greedy selection process while replacing the mean best position of the particles with the personal best position of each particle in the velocity updating equation. The improved algorithm is also augmented with a self-adaption mechanism that eliminates the need for tuning the algorithm parameters based on characteristics of the considered optimization problem. Practical features such as valve point effects, prohibited operating zones, multiple fuel options, and ramp rate limits are considered in the mathematical formulation of the economic dispatch problem. In order to demonstrate the efficacy of the proposed algorithm, five benchmark test systems are utilized. The obtained results showed that the improved random drift particle swarm optimization algorithm is capable of providing superior results compared to the original algorithm and the state of the art techniques proposed in previous literature.

Enhancement of Turbo-Generators Phase Backup Protection Using Adaptive Neuro Fuzzy Inference System

This research work presents an advanced solution for the problem due to the current setting of Relay (21). This problem arises when it is set to provide thermal backup protection for the generator during two common system disturbances, namely a system fault and a sudden application of a large system load. These investigations are carried out using Adaptive Neuro Fuzzy Inference System (ANFIS). The results of the investigations have shown that the ANFIS has a promising tool when applied for turbo-generators phase backup protection. The effect of this tool varies according to the type of input data used for ANFIS testing and validation. The proposed method in this paper proposes the use of two different sets of inputs to the ANFIS, these inputs are the generator terminal impedance measurements (R and X) and the generator three phase terminal voltages and currents (V and I). The dynamic simulations of a test benchmark have been conducted using the PSCAD/EMTDC software. The results obtained from the ANFIS scheme are encouraging.

Transient Stability Enhancement of a Wind Energy Distributed Generation System by Using Fuzzy Logic Stabilizers

This paper proposes a new power system stabilizer based on fuzzy systems. The new controller is applied to a wind turbine generating system comprising of a wind turbine driving a 3 - phase synchronous generator connected to a large power system. The new controller significantly improves system performance. The enhancement in the dynamic response of the system is verified through simulation results of a system under different operating points and exposed to both small and large disturbances. Extension to the wind energy distributed generation based multi-machine case is also included to illustrate the effectiveness of the proposed stabilizer in damping power system swing mode oscillations that follow disturbances.

Investigating the performance of a fuel cell based distributed generation system

This paper presents the design and simulation study of a proton exchange membrane fuel cell based distributed generation system. The topology chosen for the simulation consists of fuel cell power plant model, pulse width-modulation DC/DC boost converter and sinusoidal pulse width-modulation two-level inverter followed by an LC filter. Advanced control strategy is used for the overall system; its main objective is to regulate the output voltage from the DC/DC converter and to adjust the output voltage from the DC/AC inverter at different loading conditions. Simulation analysis was done using MATLAB/SIMULINK platform. Simulation results are given to show the overall system performance under heavy loading conditions, sudden increase in load and under unbalanced loading condition.

Loss of excitation detection in hydro-generators based on anfis approach using positive sequence components

This paper explains the talented impact of utilizing the Adaptive Neuro Fuzzy Inference System (ANFIS) technique on enhancing the performance of the generator Loss-of-Excitation (LOE) protection. In this context, investigations are conducted on a two-hydro generator power station model under a complete Loss of Excitation (LOE) conditions and a partial Loss of Excitation (LOE) conditions. The positive sequence components of the terminal voltage magnitude, phase current magnitude and angle (|V+ve|, |I+ve| and ∟I+ve) are used as inputs to the ANFIS. The obtained results are compared with those obtained from other techniques to prove the effectiveness of the proposed scheme. The time-domain simulation studies are conducted using PSCAD/EMTDC software. The obtained results are promising.

A novel study for hydro-generators loss of excitation faults detection using ANFIS

Abstract This paper presents a new approach for Loss of Excitation (LOE) faults detection in hydro-generators using adaptive neuro fuzzy inference system. The proposed scheme was trained by data from simulation of a 345 kV system under various faults conditions and tested for different loading conditions. Details of the design process and the results of performance using the proposed technique are discussed in the paper. Three techniques are used in this article based on the type of inputs to the proposed ANFIS unit, the generator terminal impedance measurements (R and X), the generator RMS Line to Line voltage and Phase current (Vtrms and Ia) and the positive sequence components of the generator voltage magnitude, phase current magnitude, and angle (│V+ve│, │I+ve│, and ∟I+ve). The obtained results from these schemes are compared with each other and are compared with other techniques. The results show that the proposed technique is effective in detecting the LOE faults and the obtained results are very encouraging.

Voltage Swell Mitigation Using Flexible AC Transmission Systems Based on Evolutionary Computing Methods

The main subject of these paper deals with enhancing the steady-state and dynamics performance of the power grids by using new idea namely Advanced Flexible AC Transmission Systems based on Evolutionary Computing Methods. Control of the electric power system can be achieved by using the new trends as Particle Swarm Optimization applied to this subject to enhance the characteristics of controller performance. This paper studies and analyzes Advanced Flexible AC Transmission System to mitigate only one of power quality problems is voltage swell. The Advanced Flexible AC Transmission System, which will be used in this paper, is the most promising one, which known as Advanced Thyristor Controlled Series Reactors, and Advanced Static VAR Compensator were utilized in this research to mitigate the voltage swell aiming to reach. This paper focuses on the operation of the AFACTS device under turning off heavy load that may causes transformer damaged, as no research covers this problem by this technique. Particle Swarm Optimization is used to determine the value of series inductor connected to the Advanced Flexible AC Transmission System. The proposed algorithm formatting, deriving, coding and programming the network equations required to link AFACTS during steady-state and dynamic behaviors to the power systems tested on the IEEE 30 bus system as well as IEEE 14 bus system, and 9 bus system.