A fuzzy-logic-based control methodology for secure operation of a microgrid in interconnected and isolated modes
File(s)Hossein_Ameli_Revision_Submission.pdf (898.56 KB)
Accepted version
Author(s)
Ameli, Hossein
Abbasi, Ehsan
Ameli, Mohammad Taghi
Strbac, Goran
Type
Journal Article
Abstract
Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2-step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional-Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy-logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy-logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real-time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network.
Date Issued
2017-07-13
Date Acceptance
2017-05-10
Citation
International Transactions on Electrical Energy Systems, 2017, 27 (11)
ISSN
2050-7038
Publisher
Wiley
Journal / Book Title
International Transactions on Electrical Energy Systems
Volume
27
Issue
11
Copyright Statement
© 2017 John Wiley & Sons, Ltd. This is the peer reviewed version of the article, which has been published in final form at https://dx.doi.org/10.1002/etep.2389. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Sponsor
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (E
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000416238700004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
EP/G031681/1
EP/I031650/1
EP/K006274/1
A1300 (EP/N03466X/1)
J15119 - PO:500174140
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
energy storage systems
frequency control
fuzzy-logic
microgrid
particle swarm optimization
voltage control
PARTICLE SWARM OPTIMIZATION
LOAD FREQUENCY CONTROL
ENERGY-STORAGE
SYSTEM
IMPLEMENTATION
ALGORITHM
DSTATCOM
DESIGN
GAS
Publication Status
Published
Article Number
ARTN e2389