K.R. Sudha

Data Encryption Technique Using Random Number Generator

The coding theory is an application of algebra that has become increasingly important over the decades. There are some different works that have been devoted to the problems of cryptography/cryptology. Cryptography is the study of sending and receiving secret messages. With the widespread use of information technologies and the rise of digital computer networks in many areas of the world, securing the exchange of information has become a crucial task. Currently, very active research is being done with electronic or communication applications. In the present paper an innovative technique for data encryption is proposed based on the random sequence generation using the recurrence matrices and a quadruple vector. The new algorithm provides data encryption at two levels and hence security against crypto analysis is achieved at relatively low computational overhead.

Robust Load Frequency Control of multi-area interconnected system including SMES units using Type-2 Fuzzy controller

Load Frequency Control (LFC) problem plays an vital role in power systems; its main role is to maintain the system frequency and tie line flow at their scheduled values during normal period in an interconnected system. This paper proposes a new methodology to study the Load Frequency Control (LFC) problem of a three area inter-connected system including Superconducting Magnetic Energy Storage (SMES) units using Type -2 Fuzzy system (T2FS) approach. Here, the technique is applied to control systems include three areas considering Generation Rate constraint (GRC) having two steam turbines and one hydro -turbine tied together through power lines including Superconducting Magnetic Energy Storage (SMES) units. As a consequence of continually load variation, the frequency of the power system changes over time. The salient advantage of this controller is its high insensitivity to large load changes and plant parameter variations even in the presence of non-linearities. The proposed method is tested on a three-area power system to illustrate its robust performance with various area load changes. The results obtained by using Type-2 (T2)Fuzzy controller explicitly show that the performance of the proposed controller is superior to the conventional controller and Fuzzy PI Controller(Type-1 Fuzzy) controller in terms of the overshoot, settling time and robustness. Simulation results confirm the high robustness of the proposed SMES controller with small power capacity against various disturbances and system uncertainties in comparison with SMES in the previous research.

Load Frequency Control in Deregulated Power System using Fuzzy C-Means

this paper, a fuzzy C-means controller proposed to the generation of optimal fuzzy rule base by Fuzzy C - Means clustering technique (FCM) for load frequency control in deregulated environment. The phase-plane plot of the inputs of the fuzzy controller is utilized to obtain the rule-base in the linguistic form. The proposed method is tested on a two-area power system with different contracted scenarios under various operating conditions. The results of the proposed controller are compared with the fuzzy PID controller and conventional PID controller to illustrate its robust performance. These comparisons demonstrate the superiority and robustness of the proposed controller. and/or similarity functions. These groups can later be used directly in selecting appropriate fuzzy set boundaries. Also the algorithms can automatically combine similar objects (data entries) in order to reduce the global size of the data. Finally the clustering algorithms let us easily detect potential outliers (clusters containing one or very few data entries). This feature is taken into consideration to design a decentralized fuzzy controller. The phase plane plot of the input space is formed into clusters with the cluster centers is formed to obtain the required rule-base of the proposed fuzzy controller(22).The proposed control has simple structure and does not require an accurate model of the plant. Thus, its construction and implementation are fairly easy and can be useful for the real world complex power system. The proposed method is applied to a two-area restructured power system as a test system. The results of the proposed Fuzzy-C-means controller are compared with the Fuzzy PID (FPID) controller (18) and conventional PID controller (9) through some performance indices in the presence of large parametric uncertainties and system nonlinearities under various area load changes

Dynamic Stability Margin Evaluation of Multi-machine Power Systems Using Genetic Algorithm

This paper presents a method to find the dynamic stability margin of power system using genetic algorithm. Power systems are subjected to wide range of operating conditions. Modern power systems are equipped with fast-acting protective devices for transient stability problems. Hence, power systems are operated above the transient stability limit. The dynamic behaviour of system can be evaluated using small signal stability analysis. The maximum loading to which the system can be subjected can be obtained by observing the eigenvalue variations of the system under different loading conditions. The loading for which system exhibits a pair of imaginary eigenvalues is the maximum loading limit. Beyond this limit, the system will become unstable. The loading for which the power system exhibits imaginary eigenvalues is evaluated by using genetic algorithm. The dynamic stability margin is evaluated for a 3-machine 9-bus system. The efficacy of the proposed method is tested for the power system including conventional power system stabilizers (CPSS).

Fuzzy C-means load frequency controller in deregulated power environment

The load frequency control (LFC) problem has been a major subject in the power system design/operation. The evolution of many socialised companies for power generation affects the formulation of LFC problem. In the present paper, a fuzzy load frequency controller with minimum rule-base is proposed. The optimal rule base for the proposed controller is obtained from fuzzy C-means clustering technique. The efficacy of the proposed fuzzy C-means load frequency controller is verified and compared with existing techniques in the literature for a three area interconnected power system in deregulated environment for various operating conditions under different nonlinearities. The proposed controller is tested for practical generation plants (NTTPS, KTPS, and RTPS) in India.