II. STATIC VAR COMPENSATOR (SVC) DESCRIPTION
SVC’s are first generation FACTS controllers which are expected to revolutionize power transmission in future. SVC provides an excellent source of rapidly controllable reactive shunt compensation for dynamic voltage control through its utilization of high-speed thyristor switching controlled devices. SVC is typically made up of coupling transformer, thyristor valves, reactors, capacitance (often tuned for harmonic filtering)[4].They are used to control the voltage profile under load variations, increase power transfer capability and improve system stability[28]. They can be used for damping power system oscillations incorporating some auxiliary signals.
Fig 1. Configuration of SVC Controller
III. ABOUT PAST STUDIES
A number of evolutionary techniques like BFO, GA, PSO, hybrid BF-PSO, BF with PSO biased evolution Ant Colony, water droplet optimization technique & many more has been proposed by many researchers [6-11]. Wang has applied advanced no velocity PSO for grid scheduling [12]. Attractive and Repulsive Particle Swarm Optimization has been used for orienteering problem in paper [13]. Rehab [14] has applied Genetically Improved PSO Algorithm for Efficient Data Clustering. Paper [7] has optimized TCSC parameters using GA and PSO. Paper [15] has applied Hybrid PSO which is based on the fusion of the PSO, Clonal Selection Algorithm, and Mind Evolutionary Computation. An Ant Colony Optimization based clustering algorithm was introduced by Sheokar [10]. Jin-Zhu Hu has explained the algorithm of PSO with dynamic inertia weight in paper [18].Complex ELD problem has been solved by BF with PSO biased evaluation in which directed velocity based on the global best location (gbest p...
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...ion Damping’.
[24] M. Clerc, “The swarm and the queen: Toward a deterministic and adaptive particle swarm optimization,” in Proc. IEEE Int. Congr.Evolutionary Computation, vol. 3, 1999, p. 1957.
[25] M.. Clerc and J.Kennedy, “The particle swarm—Explosion, stability, andconvergence in a multi-dimensional complex space,” IEEE Trans. Evol.Comput., vol. 6, pp. 58–73, Feb. 2002.
[26] Asanga Ratanvweera, Saman K. Halgamuge,Harry C.watson, “Self Organising Hierarchical Particle Swarm Optimizater with Time-Varying Acceleration Coefficient.”
[27] K.Somsai,A.Oonsivilai,A.Srikaew & T.Kulworawanichpon, “Optimal Controller Design And Simulation of A Static Var Compensator Using MATLAB’s SIMULINK”
[28] Poonam Singhal, S.K.Agarwal, Narender Kumar & Monika,”Stability Enhancement of a multi-machine power system using Static Var Compensator”IJAIR, volume 2, issue 2,February 2013.
By Herman, Leonard, Horwitz, Jer, Kent, Steve, and Miller, Skyler .”the ultimate history of games”.2002.web.Gamespot.
This is known as the System Active Stability or (SAS). This framework diminishes the probability of horizontal and longitudinal tip overs. It works by detecting if the forklift is getting to be flimsy and will alter the pivot to adjust.
The evolution of a fluid (gas) can also be described by the exact dynamics of the individual particles that constitutes the fluid (gas) in terms of Newton equations. However, this is complicated in the sense that in order to compute the time evolution of the fluid, one will have to solve a system of 6N first order differential equations with 6N unknowns constituting the position and velocity vectors. A perquisite for this computation is the knowledge of 6N initial
My knowledge of engineering is reasonable and includes transformer substations, power plants, power distribution and transmission systems, industrial motor control and PLC programming, protective relay coordination, FACTS devices, grounding systems, Matlab programming and project management. In addition, I possess practical experience performing power flow, short-circuit and relay coordination analyses while using a power system modelling software such as ETAP, EDSA, DigSilent and CYME. Consequently, the aforementioned experience and solid engineering education along with your training will allow me to provide support to operating and new
Baudrillard, Jean. "Simulacra and Simulations." Jean Baudrillard, Selected Writings, ed Mark Poster. Stanford University Press, 1998, pp.166-184.
The PSS is an additional control system, which is often applied as a part of an excitation control system. The basic function of the PSS is to apply a signal to the excitation system, producing electrical torques to the rotor in phase with speed differences that damp out power oscillations. They perform within the generator’s excitation system to create a part of electrical torque, called damping torque, proportional to speed change. A CPSS can be modeled by a two stage (identical), lead-lag network which is represented by a gain K and two time constants T1 and T2. This network is connected with a washout circuit of a time constant Tw. The signal washout block acts as a high-pass filter with the time constant Tw that allows the signal associated with the oscillations in rotor speed to pass unchanged. Furthermore, it does not allow the steady state changes to modify the terminal voltages. The phase compensation blocks with time constants T1i – T4i supply the suitable phase-lead characteristics to compensate the phase lag between the input and the output signals. The commonly used structure of the PSS is shown in Fig
Genetic Algorithms provide a holistic search process based on principles of natural genetics and survivals of the fittest……
· B-phase transformer (EMTU-TT01) · Feedback electronic wattmeter · Multi-range moving-iron ammeter · Instrument voltage transformer THEORY AND INTRODUCTION ----------------------- Transformers are used all over the world to step-up and step-down electricity. The transformer is one of the most commonly used electrical devices. The reason the transformer is so popular is because they range in size from 240V to well over 240kV, stepping -up and stepping-down electricity all over the world.
...ter-3 gives the overall about genetic algorithms. An introduction of algorithm is given and how and why they work is explained with help of examples. Different procedures are explained that are used in genetic algorithms
... in Wireless Sensor Networks: Current proposal and Future Development, IEEE Xplore, Hong Kong, Oct- 2007.
Cormen T. H, Leiserson C. E., Rivest R. L. and Stein C. [1990] (2001). “Introduction to Algorithms”, 2nd edition, MIT Press and McGraw-Hill, ISBN 0-262-03293-7, pp. 27–37. Section 2.3: Designing algorithms..
Barbara Mowat and Paul Warstine. New York: Washington Press, 1992. Slethaug, Gordon. A. See "Lecture Notes" for ENGL1007.
... middle of paper ... ... Berk, L. (2007). The 'Standard'.
Natural systems exhibiting swarm intelligence is a colony of ants similar to a flock of birds or a herd of animals as they all move together in groups and are behaviourally distinct. Even though individual behaviour is distinct the group members have the ability to act in unanimity. Th...
When an algorithm is applied to solve a classification problem with a different set of parameters, the classification accuracy also differs abruptly in each case . The challenge in machine learning to find the most suitable parameter values of the algorithms that solves an engineering problem to the best possible way in terms of performance metrics. Therefore, one has to fine tune the algorithm parameters that best suits the problem. There are several optimization techniques like genetic algorithm, particle swarm optimization , Tabu search methods etc. The focus of the study is to calibrate the algorithm parameters using design of experiment