2009Unpublished venueRequires access

Implementation of Static VAR Compensator for Improvement of Power System Stability

B. Venkateswara Rao, G. V. Nagesh Kumar, M. Ramya Priya, Polamraju V.S. Sobhan

Open publisher page 12 citations

Abstract

Static VAR compensator (SVC) is incorporated in Newton Raphson method in which Power Flow Solution is a solution of the network under steady state conditions subjected to certain constraints under which the system operates. The power flow solution gives the nodal voltages and phase angles given a set of power injections at buses and specified voltages at a few, both the models of SVC i.e.SVC Susceptance and Firing Angle Models are discussed. It is also shown that the power system losses are decreased after incorporating the SVC in this N-R method. The results are generated for 24-Bus system. The reactors are thyristor-controlled and the capacitors can be either fixed or controlled. Advanced load flow models for the SVC are presented in this paper. The models are incorporated into existing load flow (LF) Newton Raphson algorithm. The new models depart from the generator representation of the SVC and are based instead on the variable susceptance concept. The SVC state variables are combined with the nodal voltage magnitudes and angles of the network in a single frame of reference for a unified, iterative solution through Newton methods. The algorithm for Load Flow exhibit very strong convergence characteristics, regardless of the network size and the number of controllable devices. Results are presented which demonstrate the process of the new SVC models.

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What this paper is about

Static VAR compensator (SVC) is incorporated in Newton Raphson method in which Power Flow Solution is a solution of the network under steady state conditions subjected to certain constraints under which the system operates. The power flow solution gives the nodal voltages and phase angles given a set of power injections at buses and specified voltages at a few, both the models of SVC i.e.SVC Susceptance and Firing Angle Models are discussed. It is also shown that the power system losses are decreased after incorporating the SVC in this N-R method. The results are generated for 24-Bus system. The reactors are thyristor-controlled and the capacitors can be either fixed or controlled. Advanced load flow models for the SVC are presented in this paper. The models are incorporated into existing load flow (LF) Newton Raphson algorithm. The new models depart from the generator representation of the SVC and are based instead on the variable susceptance concept. The SVC state variables are combined with the nodal voltage magnitudes and angles of the network in a single frame of reference for a unified, iterative solution through Newton methods. The algorithm for Load Flow exhibit very strong convergence characteristics, regardless of the network size and the number of controllable devices. Results are presented which demonstrate the process of the new SVC models.

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Available abstract

Static VAR compensator (SVC) is incorporated in Newton Raphson method in which Power Flow Solution is a solution of the network under steady state conditions subjected to certain constraints under which the system operates. The power flow solution gives the nodal voltages and phase angles given a set of power injections at buses and specified voltages at a few, both the models of SVC i.e.SVC Susceptance and Firing Angle Models are discussed. It is also shown that the power system losses are decreased after incorporating the SVC in this N-R method. The results are generated for 24-Bus system. The reactors are thyristor-controlled and the capacitors can be either fixed or controlled. Advanced load flow models for the SVC are presented in this paper. The models are incorporated into existing load flow (LF) Newton Raphson algorithm. The new models depart from the generator representation of the SVC and are based instead on the variable susceptance concept. The SVC state variables are combined with the nodal voltage magnitudes and angles of the network in a single frame of reference for a unified, iterative solution through Newton methods. The algorithm for Load Flow exhibit very strong convergence characteristics, regardless of the network size and the number of controllable devices. Results are presented which demonstrate the process of the new SVC models.

Key concepts: Static VAR compensator, Susceptance, Control theory (sociology), Electric power system, Newton's method, Thyristor, AC power, Convergence (economics)

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