Optimal Design of Modified Power System Stabilizer Using Multi Objective Based Bio Inspired Algorithms

Optimal Design of Modified Power System Stabilizer Using Multi Objective Based Bio Inspired Algorithms

Dasu Butti, Siva Kumar Mangipudi, Srinivasarao Rayapudi
Copyright: © 2018 |Pages: 39
DOI: 10.4018/IJEOE.2018100102
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In this article, a multi objective and a novel objective based Power System Stabilizer (PSS) design is proposed for a modified Heffron - Philiphs model (MHP) using bio inspired algorithms. A conventional Heffron – Philphs (CHP) model is developed by taking infinite bus voltage as reference, whereas MHP model is developed by taking transformer high voltage bus voltage as reference, which makes independent of external system data for the PSS design. PSS parameters are optimized using differential evolution (DE) algorithm and Firefly (FF) algorithm to obtain better dynamic response. The proposed method is tested on various operating conditions under different typical disturbances to test efficacy and robustness. Simulation results prove that better dynamic performance is obtained with the proposed stabilizers over the fixed gain stabilizers. This method of tuning would become a better alternative to conventional stabilizers as conventional stabilizers require retuning of parameters mostly when operating condition changes, which is a time-consuming process and laborious. Eigen value analysis is also done to prove the efficacy of the proposed method over the conventional methods.
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Power System is a huge interconnected and highly nonlinear network that suffers from various disturbances. Hence it has become a big challenging issue to every power engineer to face this disturbance and protect the system from these disturbances. In a generator, the behavior of the electromechanical coupling between the rotor and rest of the system resembles with behavior of spring mass and damper system following any disturbance. Oscillations in the range of 0.2 to 3.0 Hz exited by the disturbances in the system may limit the power handling capacity or sometimes causes loss of synchronism and leads to failure of the total system. (Schleif, Hunkins, Martin, & Hattan, 1968), (Demello & Concordia, 1969) have mentioned that power system stabilizers can be used as auxiliary controllers to counter the instability problems by producing additional damping in the system that arose in the power system. After (E. V. Larsen & Swann, 1981) (E. Larsen & Swann, 1981) has given an exhaustive coverage of general tuning procedures of PSS and concepts related to PSS applications using different signals. (Kundur, Klein, Rogers, & Zywno, 1989) gave a detailed PSS design methodology and implementation of PSS in Ontario Hydro generating station. (Gibbard, 1988), (Gibbard & Vowles, n.d.), (Gibbard & Vowles, 2004) did very useful work in the design of power system stabilizers. Similarly, from the last few decades various techniques have been suggested to design power system stabilizers. It includes traditional techniques like robust control, sliding mode and output - feedback control techniques.

Table 1.
IJEOE.2018100102.m01 = Rotor angle
IJEOE.2018100102.m02 = Rotor angle with respect to transformer secondary bus voltage
IJEOE.2018100102.m03 = Slip speed
IJEOE.2018100102.m04 = Inertia constant
IJEOE.2018100102.m05 = Mechanical toque
IJEOE.2018100102.m06 = Electrical torque
IJEOE.2018100102.m07 = Damping coefficient
IJEOE.2018100102.m08 = Field flux transient emf
IJEOE.2018100102.m09 = Open circuit time constant of d-axis
IJEOE.2018100102.m10 = d-axis reactance
IJEOE.2018100102.m11 = q-axis reactance
IJEOE.2018100102.m12 = d-axis stator current component
IJEOE.2018100102.m13 = q-axis stator current component
IJEOE.2018100102.m14 = Field voltage
IJEOE.2018100102.m15 = Time constant of exciter
IJEOE.2018100102.m16 = Gain of exciter
IJEOE.2018100102.m17 = Reference voltage
IJEOE.2018100102.m18 = Input of PSS
IJEOE.2018100102.m19 = Generator terminal voltage
IJEOE.2018100102.m20 = Transformer secondary bus voltage
IJEOE.2018100102.m21 = Reactance of transformer
0 = To represent initial conditions

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