Robust Power System Stabilizer for Multi-machine Power Networks using Tunicate Swarm Algorithm-Reference-Cited by-同舟云学术

Robust Power System Stabilizer for Multi-machine Power Networks using Tunicate Swarm Algorithm

Published:2022-02-23 Issue: Volume: Page:
ISSN:
Container-title:2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS)
language:
Short-container-title:

Author:

Tayeb Jahid Hasan¹,Islam Md. Rashidul¹,Shafiullah Md²,Gani Sayed Md.Abrar¹,Hossain Md Ismail²

Affiliation:

1. International Islamic University,dept. of Electrical and Electronic Engineering,Chittagong,Bangladesh

2. King Fahad University of Petroleum & Minerals,IRC for Renewable Energy and Power Systems,Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9741824/9741825/09741828.pdf?arnumber=9741828

Reference22 articles.

1. Power system stability enhancement by designing optimal PSS employing backtracking search algorithm

2. Robust power system stabiliser design under multi-operating conditions using differential evolution

3. Comparison of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO) in Improving Power System Stability by UPFC Controller Employing a MultiObjective Approach;shahriar;1st International Conference on Advanced Information and Communication Technology 2016 (ICAICT 2016),2016

4. Robust design of PID power system stabilizer in multi-machine power system using artificial intelligence techniques

5. Enhancement of power system damping employing TCSC with genetic algorithm based controller design

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LFO Damping Enhancement in Multimachine Network Using African Vulture Optimization Algorithm;Journal of Energy and Power Technology;2024-01-30

2. A Review of Modern Computational Techniques and Their Role in Power System Stability and Control;Energies;2023-12-28

3. A Comprehensive Review of Power System Stabilizers;Energies;2023-02-15

4. Short‐term commercial load forecasting based on peak‐valley features with the TSA‐ELM model;Energy Science & Engineering;2022-05-31