The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
BFO Optimized Automatic Load Frequency Control of a Multi-Area Power System
Abstract
This chapter presents an analysis on operation of Automatic Load Frequency Control (ALFC) by developing models in SIMULINK which helps us to understand the principle behind ALFC including the challenges. The three area system is being taken into account considering several important parameters of ALFC like integral controller gains (KIi), governor speed regulation parameters (Ri), and frequency bias parameters (Bi), which are being optimized by using Bacteria Foraging Optimization Algorithm (BFOA). Simultaneous optimization of certain parameters like KIi, Ri and Bi has been done which provides not only the best dynamic response for the system but also allows us to use much higher values of Ri than used in practice. This will help the power industries for easier and cheaper realization of the governor. The performance of BFOA is also investigated through the convergence characteristics which reveal that that the Bacteria Foraging Algorithm is quite faster in optimization such that there is reduction in the computational burden and also minimal use of computer resource utilization.
Related Content
|
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
|
Stavros Kaperonis.
© 2024.
25 pages.
|
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
|
Nuno Geada.
© 2024.
12 pages.
|
|
|