An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control-Reference-Cited by-同舟云学术

An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control

Published:2018-04 Issue: Volume:65 Page:121-138
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Gheisarnejad Meysam

Publisher

Elsevier BV

Subject

Software

Reference54 articles.

1. Robust Power System Frequency Control;Bevrani,2009

2. Design and analysis of BFOA-optimized fuzzy PI/PID controller for AGC of multi-area traditional/restructured electrical power systems;Arya;Soft Comput.,2016

3. Maiden application of bacterial foraging-based optimization technique in multiarea automatic generation control;Nanda;IEEE Trans. Power Syst.,2009

4. Comparative performance analysis of fruit fly optimisation algorithm for multi-area multi-source automatic generation control under deregulated environment;Mohanty;IET Gener. Transm. Distrib.,2015

5. Hybrid BFOA–PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems;Panda;Appl. Soft Comput.,2013

Cited by 141 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. A SSA-based CFFOPID drop deloaded tidal turbine controller using HVDC-link;ISA Transactions;2024-10

2. SDO: A novel sled dog-inspired optimizer for solving engineering problems;Advanced Engineering Informatics;2024-10

3. A hybrid optimization algorithm for improving load frequency control in interconnected power systems;Expert Systems with Applications;2024-09

4. Improving PID Controller Performance in Nonlinear Oscillatory Automatic Generation Control Systems Using a Multi-objective Marine Predator Algorithm with Enhanced Diversity;Journal of Bionic Engineering;2024-06-06

5. Equilibrium optimizer-based harmony search algorithm with nonlinear dynamic domains and its application to real-world optimization problems;Artificial Intelligence Review;2024-06-06