Power Quality

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Aboelazm, Y. M., W. E. Wahba, and M. M. A. Hassan, "Simulation of advanced STATCOM for voltage swell mitigation in large-scale test system based on swarm intelligence algorithms ", European Journal of Electrical Engineering, vol. 20, issue 3, pp. 253-266, 2018.
Aboelazm, Y. M., W. E. Wahba, and M. M. A. Hassan, "Mitigation of voltage swells in IEEE 30 bus and IEEE 57 bus systems using evolutionary techniques", European Journal of Electrical Engineering, vol. 20, issue 4, pp. 499-516, 2018.
Sayed, R. M., M. A. M. Hassan, and A. A. Hassan, "Power System Quality Improvement Using Flexible AC Transmission Systems Based on Adaptive Neuro-Fuzzy Inference System", WESAS Transaction on Power Systems, vol. 8, no. 1: Worl Scientific and Engineering Academy and Societ, pp. 65–78, 2013. AbstractCU-PDF

This paper introduces comprehensive fast control characteristics and continuous compensation means using Adaptive Neuro-Fuzzy Inference System. Flexible AC Transmission System (FACTS) devices have been investigated and adopted in power engineering area. There are so many advantages in using FACTS devices. It can increase dynamic stability, loading capability of transmission lines, improve power quality as well as system security. It can also increase utilization of lowest cost generation. This paper presents a detailed Adaptive Neuro-Fuzzy Inference System based algorithm for improving power system quality using Advanced Flexible AC Transmission Systems (FACTS) controllers. Namely, Advanced Thyristor Controlled Series Capacitors (ATCSCs), and Advanced Static Var Compensator (ASVC) were utilized in this research. This paper focuses on the operation of the FACTS device under generator fault that may cause any other transmission lines to be overflowed. Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to determine the value of capacitor connected to the FACTS. The proposed algorithm in this paper is tested on the IEEE 30 bus system as well as IEEE 14 bus system.

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