Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Load-frequency control

Load-frequency control

Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...

Time and frequency -Domain Interpretation of PI Control

Time and frequency -Domain Interpretation of PI Control

Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...

Time-Domain Interpretation of PD Control

Time-Domain Interpretation of PD Control

Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...

PID Controller

PID Controller

Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...

PI Controller: Design

PI Controller: Design

Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...

Fast Decoupled and DC Powerflow

Fast Decoupled and DC Powerflow

The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Application of an optimal tilt controller in a partial loading schedule of multi-area power system considering HVDC link and virtual inertia.

ISA transactions·2023

Same author

Stabilized frequency response of a microgrid using a two-degree-of-freedom controller with African vultures optimization algorithm.

ISA transactions·2023

Same author

A Novel Baseline Removal Paradigm for Subject-Independent Features in Emotion Classification Using EEG.

Bioengineering (Basel, Switzerland)·2023

Same author

Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-Heuristically Optimized Non-Local Means Filter.

Sensors (Basel, Switzerland)·2022

Same author

Automated Feature Extraction on AsMap for Emotion Classification Using EEG.

Sensors (Basel, Switzerland)·2022

Same author

SAM 40: Dataset of 40 subject EEG recordings to monitor the induced-stress while performing Stroop color-word test, arithmetic task, and mirror image recognition task.

Data in brief·2022

Search research articles

Related Experiment Video

Updated: May 6, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Solution to automatic generation control problem using firefly algorithm optimized I(λ)D(µ) controller.

Sanjoy Debbarma¹, Lalit Chandra Saikia², Nidul Sinha²

¹Department of Electrical and Electronics Engineering, National Institute of Technology Meghalaya, Shillong, India.

ISA Transactions

|October 22, 2013

Summary

A novel fractional order I(λ)D(µ) controller significantly improves automatic generation control (AGC) in multi-area power systems. This new controller, optimized using the firefly algorithm, outperforms traditional controllers under various conditions.

Keywords:

Automatic generation control Firefly algorithm I(λ)D(μ) controller Integer order controller

More Related Videos

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

Related Experiment Videos

Last Updated: May 6, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

Area of Science:

Electrical Engineering
Control Systems
Power Systems

Background:

Automatic Generation Control (AGC) is crucial for maintaining power system stability.
Traditional controllers struggle with complex multi-area systems and dynamic constraints like Generation Rate Constraints (GRC).

Purpose of the Study:

To propose and evaluate a novel fractional order (FO) I(λ)D(µ) controller for multi-area AGC.
To optimize controller parameters and system parameters using the Firefly Algorithm (FA).

Main Methods:

A fractional order I(λ)D(µ) controller based on crone approximation was developed.
The Firefly Algorithm (FA) was employed for simultaneous optimization of controller gains, fractional orders (λ, μ), and governor speed regulation parameters (R).
Dynamic responses were simulated and compared against classical integer order (IO) controllers (I, PI, PID).

Main Results:

The proposed I(λ)D(µ) controller demonstrated superior dynamic responses compared to IO controllers.
Sensitivity analysis confirmed the controller's robustness against variations in system loading, Single Load Perturbation (SLP) location/size, and system parameters.
The controller performed effectively even during simultaneous SLPs in multiple areas.

Conclusions:

The fractional order I(λ)D(µ) controller offers a significant advancement for multi-area AGC.
The proposed method provides robust and improved performance over conventional controllers, enhancing power system stability and reliability.