Microgrid Decentralized Frequency Control Performance Improvement: An Optimal Fuzzy-LQR Design Approach

This study addresses an optimal decentralized controller optimized using fuzzy logic, to improve frequency performance and meliorate active power sharing in a microgrid. The proposed controller can achieve frequency regulation and active power allocation without a communication network for information exchange. The design of this controller is based on a linear-quadratic cost function, for which an optimal solution has been provided using the LQR method. The weighing matrices Q and R in the proposed LQR controller are determined based on fuzzy logic, which results in the selection of the best weighing matrices and, as a result, better performance of the controller. In the design of this controller, only the dynamics of the low-pass filter in the droop control loop have been used. The proposed controller can be used in both online and offline operation modes. The simulation results have shown desirable frequency alignment and active power sharing in the presence of various disturbances.

Authors

Institutions

Publication Details

Published
2024-12-31
DOI
https://doi.org/10.1109/sgc64640.2024.10983233
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Microgrid Decentralized Frequency Control Performance Improvement: An Optimal Fuzzy-LQR Design Approach

Hassan Bevrani, Sharara Rehimi, Barmak Baigzadehnoe, Amir Fathi Haft Cheshme
Microgrid Control and Optimization
article

Microgrid Decentralized Frequency Control Performance Improvement: An Optimal Fuzzy-LQR Design Approach

Hassan Bevrani, Sharara Rehimi, Barmak Baigzadehnoe, Amir Fathi Haft Cheshme
article en

Abstract

This study addresses an optimal decentralized controller optimized using fuzzy logic, to improve frequency performance and meliorate active power sharing in a microgrid. The proposed controller can achieve frequency regulation and active power allocation without a communication network for information exchange. The design of this controller is based on a linear-quadratic cost function, for which an optimal solution has been provided using the LQR method. The weighing matrices Q and R in the proposed LQR controller are determined based on fuzzy logic, which results in the selection of the best weighing matrices and, as a result, better performance of the controller. In the design of this controller, only the dynamics of the low-pass filter in the droop control loop have been used. The proposed controller can be used in both online and offline operation modes. The simulation results have shown desirable frequency alignment and active power sharing in the presence of various disturbances.

University of Kurdistan (IR), Nagoya University (JP)
Affordable and clean energy
Openalex Percentile: Top 62%
Microgrid Control and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.