Informatics Publishing Limited

Reza Sharifi ¹, Reza Khamooshi ¹, Hamid Radmanesh ², G. B. Gharehpetian ¹, Seyyed Hamid Fathi ¹, Javad S. H. Moghani ¹

Affiliations
1 Electrical Engineering Department, Amirkabir University of Technology, Tehran, IR
2 Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, IR

Abstract

Nowadays, Flexible AC Transmission System (FACTS) devices are widely used in different power systems. As the application of these technologies increases, possible interferences in operational tasks of controllers and inappropriate oscillations in different situations like fault and post-fault conditions make the coordination of their controllers inevitable. In this paper, a Fuzzy Inference System (FIS) based coordinated design of Static Synchronous Series Compensator (SSSC) controllers is presented and discussed. The main advantages of the proposed scheme are good damping and overshoot reduction of oscillations and thereby improving power oscillations damping. The Trajectory Sensitivities (TS) analysis, which is a time domain method to evaluate the stability of a system in the presence of disturbances, is also used to assess the validity of this coordinated controller design method. The comparison of simulation results with the conventional Proportional-Integral-Derivative (PID) controller based system validates the effectiveness of this design.

Keywords

Coordinated Design, Fuzzy Inference System, Flexible AC Transmission System, Power System Oscillations, Static Synchronous Series Compensator.

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Roozbeh Kamali ¹, Reza Sharifi ², Hamid Radmanesh ¹, S. H. Fathi ²

Affiliations
1 Electrical Engineering Department, Aeronautical University of Science and Technology, Tehran, IR
2 Electrical Engineering Department, Amirkabir University of Technology, Tehran, IR

Abstract

This paper present an Artificial Neural Network (ANN) model for online profile voltage estimation to aim distribution network voltage regulation with consider Distributed Generation (DG). Arrival of DG to the distribution network affect the feeder voltages. Commonly, the On-Load Tap Changer (OLTC) transformer with a Line Drop Compensation (LDC) that monitors the voltage along the feeder is used to regulate the voltage within allowable limits. But with presence DG because of multi-directional power flow, there are complications for the operation of the LDC to detect the correct amount of voltage profile along the feeder. The proposed estimation method employs Artificial Neural Network (ANN) concept and eliminates utilization of power flow calculations, resulting in low computational burden and online operation especially in case of systems with high order of complexity. Proposed technique is tested on a 13 bus distribution network and simulation outcomes validate effectiveness and efficiency of the suggested scheme.

Keywords

Artificial Neural Network (ANN), Distributed Generation, On-Load Tap Changer.

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