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...

Turbine-Governor Control

Turbine-Governor Control

Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

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...

Feedback control systems

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...

Frequency-Domain Interpretation of PD Control

Frequency-Domain Interpretation of PD Control

Proportional-Derivative (PD) controllers are widely used in fan control systems to improve stability and performance. A fan control system can be effectively represented using a Bode plot to illustrate the impact of a PD controller through its transfer function. The Bode plot visually conveys how PD control modifies the fan's response across various frequencies, providing a frequency domain interpretation of the controller's behavior.
The proportional control gain, combined with the...

You might also read

Related Articles

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

Sort by

Same author

Wired and Wireless Photosynthetic Biohybrids: Design, Materials, and Mechanisms.

Chemical reviews·2026

Same author

Sensor and Sensorless Technology with Renewable Energy and Flexible Load Participation in Active Distribution Network.

Sensors (Basel, Switzerland)·2025

Same author

Particle on a Rod: Surface-Tethered Catalyst on CdS Nanorods for Enzymatically Active Nicotinamide Cofactor Generation.

Nano letters·2024

Same author

Nozzle Electrode Point Discharge-Enhanced Oxidation and Portable Gas Phase Molecular Fluorescence Spectrometry for Sensitive Field Detection of Sulfide.

Analytical chemistry·2023

Same author

Time Series Forecasting of Motor Bearing Vibration Based on Informer.

Sensors (Basel, Switzerland)·2022

Same author

Calibration of Radar RCS Measurement Errors by Observing the Luneburg Lens Onboard the LEO Satellite.

Sensors (Basel, Switzerland)·2022

Search research articles

Related Experiment Video

Updated: Jun 14, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

Optimization of Fuzzy Control Parameters for Wind Farms and Battery Energy Storage Systems Based on an Enhanced

Zejian Liu^1,2, Ping Yang¹, Peng Zhang¹

¹Key Laboratory of Clean Energy Technology of Guangdong Province, School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China.

Sensors (Basel, Switzerland)

|August 29, 2024

Summary

This study enhances wind farm frequency stability using an improved Artificial Bee Colony (ABC) algorithm to optimize fuzzy controllers for battery energy storage systems (BESSs) and doubly fed induction generators (DFIGs). The optimized system significantly reduces frequency fluctuations and improves power system stability.

Keywords:

ABC algorithm DFIG Gaussian walk mechanism fuzzy membership function multi-source sensor data primary frequency control

More Related Videos

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

Published on: November 15, 2014

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

Related Experiment Videos

Last Updated: Jun 14, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

Published on: November 15, 2014

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

Area of Science:

Electrical Engineering
Renewable Energy Systems
Control Systems

Background:

Large-scale wind farm grid connection can lead to low inertia states and frequency instability.
Battery energy storage systems (BESSs) offer fast response and flexibility to mitigate frequency fluctuations.
Fuzzy control in doubly fed induction generators (DFIGs) and BESSs can suffer from parameter errors affecting frequency control.

Purpose of the Study:

To propose an improved Artificial Bee Colony (ABC) algorithm for optimizing fuzzy controllers in DFIGs and BESSs.
To enhance the frequency control capabilities of BESSs and DFIGs in wind farm systems.
To address frequency instability caused by parameter errors in fuzzy membership functions.

Main Methods:

An improved Artificial Bee Colony (ABC) algorithm incorporating a Gaussian wandering mechanism was developed.
The improved ABC algorithm was used to optimize fuzzy controller membership function parameters for BESSs and DFIGs.
The proposed control strategy was validated using MATLAB/Simulink simulations.

Main Results:

The optimized control strategy significantly reduced oscillation amplitude by 0.15 Hz.
Frequency control precision was improved by 40% after optimization.
Steady-state frequency deviation was reduced by 26%.

Conclusions:

The proposed improved ABC algorithm effectively optimizes fuzzy controllers for enhanced frequency stability in wind farm systems.
The integration of BESSs and DFIGs with the optimized control strategy improves overall power system frequency response.
This method offers a significant improvement in the frequency stability of coordinated wind farm and BESS systems.