Optimal Design of Single Machine Power System Stabilizer using Chemical Reaction Optimization Technique

Optimal Design of Single Machine Power System Stabilizer using Chemical Reaction Optimization Technique

Sourav Paul, Provas Kumar Roy
Copyright: © 2015 |Pages: 19
DOI: 10.4018/IJEOE.2015040104
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PSSs are added to excitation systems to enhance the damping during low frequency oscillations. The non-linear model of a machine is linearized at different operating points. Chemical Reaction optimization (CRO), a new population based search algorithm is been proposed in this paper to damp the power system low-frequency oscillations and enhance power system stability. Computation results demonstrate that the proposed algorithm is effective in damping low frequency oscillations as well as improving system dynamic stability. The performance of the proposed algorithm is evaluated for different loading conditions. In addition, the proposed algorithm is more effective and provides superior performance when compared other population based optimization algorithms like differential evolution (DE) and particle swarm optimization (PSO).
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1. Introduction

Stability of power systems is one of the most important aspects for power system operations. Low frequency oscillations are generally observed when large power systems are interconnected by relatively weak tie lines. Modern generators are equipped with high gain and fast response exciters. These exciters, also known as Automatic Voltage Regulators (AVR), enhance the transient stability and prevent voltage fluctuation by simply increasing the synchronizing torque which reduces the generator angle and avoid non-oscillatory instability. The AVR, conversely, contributes to low frequency oscillation by decreasing the damping torque to a negative value, which adversely affects stability. These oscillations may sustain and grow to cause system separation if no adequate damping is provided (Kundur, 1994). In (Sidorov, Panasetsky, & Smidl, 2010) address early on-line detection of inter-area electro-mechanical oscillations in power systems using dynamic data such as currents, voltages and angle differences measured across transmission lines in real time. The approach has been demonstrated on real retrospective data recorded in a 500KV power grid. (Voropai, Glazunova, Kurbatsky, Sidorov, Spiryaev, & Tomin, 2010) proposed two approaches namely Kalman filter based algorithms and nonlinear optimization for dynamical state estimation of power system. (Sidorov, Grishin, Yu, & Smidl, 2010) address on-line early detection of inter-area electro-mechanical oscillation in power systems with the main objective to give transmission operator qualitative information regarding stability margins. Power system stabilizer (PSS) is now routinely used in the industry to damp out these oscillations (Talaat, Abdennour, & Al-Sulaiman, 2010). The use of PSS in power system is economical and becomes successful in improving the power system stability, and is expected to be installed on many generators connected to the system. PSS generates a supplementary stabilizing signal that is added to excitation control loop of generating unit to produce extra damping. Conventional PSS (CPSS) is a lead-lag network (Larsen, & Swann, 1981). The CPSS makes a great contribution in enhancing power system dynamic stability. Generally, design of CPSS parameters is based on linearized model of power system at nominal operating point. However, power system is highly non-linear in nature with configurations and parameters changing with different operating conditions. CPSS design based on linearized model of the power system at nominal operating point does not result satisfactory and optimal performance for a practical operating environment.

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