Enhancing power system security using soft computing and machine learning
Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe...
Saved in:
| Date: | 2023 |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine
2023
|
| Subjects: | |
| Online Access: | http://eie.khpi.edu.ua/article/view/282307 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Journal Title: | Electrical Engineering & Electromechanics |
Institution
Electrical Engineering & Electromechanics| id |
eiekhpieduua-article-282307 |
|---|---|
| record_format |
ojs |
| spelling |
eiekhpieduua-article-2823072023-06-27T18:29:22Z Enhancing power system security using soft computing and machine learning Enhancing power system security using soft computing and machine learning Venkatesh, P. Visali, N. machine learning particle swarm optimization power system security interline power flow controller unified power flow controller машинне навчання оптимізація рою частинок безпека енергосистеми вбудований контролер потоку потужності уніфікований контролер потоку потужності Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe the stability analysis with and without the unified power flow controller and interline power flow controller, as well as the associated costs. This allows for rapid prediction of the most affected transmission line and the location for compensation. Results. Many contingency conditions, such as the failure of a single transmission line and change in the load, are built into the power system. The single transmission line outage and load fluctuation used to determine the contingency ranking are the primary emphasis of this work. Practical value. In order to set up a safe transmission power system, the suggested stability analysis has been quite helpful. Мета. Щоб гарантувати правильну роботу системи, запропонований метод передбачає втрату однієї лінії передачі розрахунку рейтингу непередбачених обставин. Методи. Запропонована математична модель з алгоритмом машинного навчання з оптимізацією рою частинок використовувалася для спостереження за аналізом стійкості з уніфікованим регулятором потоку потужності та міжлінійним регулятором потоку потужності та без нього, а також з відповідними витратами. Це дозволяє швидко передбачити найбільш постраждалу лінію передачі та місце для компенсації. Результати. Багато позаштатних ситуацій, таких як відмова однієї лінії електропередачі та зміна навантаження, вбудовані в енергосистему. Основна увага у цій роботі приділяється відключенню однієї лінії електропередачі та коливанням навантаження, які використовуються для визначення рейтингу непередбачених обставин. Практична цінність. Пропонований аналіз стійкості виявився дуже корисним до створення безпечної системи передачі електроенергії. National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine 2023-06-27 Article Article application/pdf http://eie.khpi.edu.ua/article/view/282307 10.20998/2074-272X.2023.4.13 Electrical Engineering & Electromechanics; No. 4 (2023); 90-94 Электротехника и Электромеханика; № 4 (2023); 90-94 Електротехніка і Електромеханіка; № 4 (2023); 90-94 2309-3404 2074-272X en http://eie.khpi.edu.ua/article/view/282307/276697 Copyright (c) 2023 P. Venkatesh, N. Visali http://creativecommons.org/licenses/by-nc/4.0 |
| institution |
Electrical Engineering & Electromechanics |
| baseUrl_str |
|
| datestamp_date |
2023-06-27T18:29:22Z |
| collection |
OJS |
| language |
English |
| topic |
machine learning particle swarm optimization power system security interline power flow controller unified power flow controller |
| spellingShingle |
machine learning particle swarm optimization power system security interline power flow controller unified power flow controller Venkatesh, P. Visali, N. Enhancing power system security using soft computing and machine learning |
| topic_facet |
machine learning particle swarm optimization power system security interline power flow controller unified power flow controller машинне навчання оптимізація рою частинок безпека енергосистеми вбудований контролер потоку потужності уніфікований контролер потоку потужності |
| format |
Article |
| author |
Venkatesh, P. Visali, N. |
| author_facet |
Venkatesh, P. Visali, N. |
| author_sort |
Venkatesh, P. |
| title |
Enhancing power system security using soft computing and machine learning |
| title_short |
Enhancing power system security using soft computing and machine learning |
| title_full |
Enhancing power system security using soft computing and machine learning |
| title_fullStr |
Enhancing power system security using soft computing and machine learning |
| title_full_unstemmed |
Enhancing power system security using soft computing and machine learning |
| title_sort |
enhancing power system security using soft computing and machine learning |
| title_alt |
Enhancing power system security using soft computing and machine learning |
| description |
Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe the stability analysis with and without the unified power flow controller and interline power flow controller, as well as the associated costs. This allows for rapid prediction of the most affected transmission line and the location for compensation. Results. Many contingency conditions, such as the failure of a single transmission line and change in the load, are built into the power system. The single transmission line outage and load fluctuation used to determine the contingency ranking are the primary emphasis of this work. Practical value. In order to set up a safe transmission power system, the suggested stability analysis has been quite helpful. |
| publisher |
National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine |
| publishDate |
2023 |
| url |
http://eie.khpi.edu.ua/article/view/282307 |
| work_keys_str_mv |
AT venkateshp enhancingpowersystemsecurityusingsoftcomputingandmachinelearning AT visalin enhancingpowersystemsecurityusingsoftcomputingandmachinelearning |
| first_indexed |
2025-07-17T11:49:47Z |
| last_indexed |
2025-07-17T11:49:47Z |
| _version_ |
1850412120814911488 |