a novel fuzzy rpid controller for multiarea agc with iabc optimization

Clicks: 121
ID: 204372
2013
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #26 of 42 articles by views in Plant foods for human nutrition (Dordrecht, Netherlands)

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
An Interactive Artificial Bee Colony (IABC) Optimization based fuzzy (IABCF) to tune optimal gains of a Robust Proportional Integral Derivative (RPID) controller is proposed for the solution of multiarea automatic generation control (AGC) simulation problem in a restructured power system. One of the important problems in the proposed method is the exact tuning of the RPID parameters for achieving the desired level of robust performance. The problem of robustly tuning of RPID based AGC design is formulated as an optimization problem according to the time domain-based objective function, which is solved by the IABC technique that has a strong ability to find the most optimistic results. The robustness and effectiveness of the proffered method are shown on a two and four areas deregulated power system with possible contracted scenarios under large load demand and area disturbances in comparison with the other methods through FD and ITAE performance indices. The evaluation results show that the proposed control strategy achieves good robust performance for worldwide experience of automatic generation control in restructured systems parameters and load changes in the presence of system nonlinearities.
Reference Key
javidan2013journala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Javad Javidan;Ali Ghasemi
Journal Plant foods for human nutrition (Dordrecht, Netherlands)
Year 2013
DOI
10.1155/2013/510572
URL
http://dx.doi.org/10.1155/2013/510572
Keywords
engineering (general) civil engineering (general)

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.