Open AccessA fuzzy‐logic–based control methodology for secure operation of a microgrid in interconnected and isolated modes
Author(s) -
Ameli Hossein,
Abbasi Ehsan,
Ameli Mohammad Taghi,
Strbac Goran
Publication year - 2017
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2389
Subject(s) - microgrid , control theory (sociology) , automatic frequency control , controller (irrigation) , fuzzy logic , engineering , renewable energy , frequency deviation , control engineering , voltage , superconducting magnetic energy storage , pid controller , inverter , electric power system , voltage controller , computer science , voltage regulator , power (physics) , electrical engineering , control (management) , voltage droop , temperature control , artificial intelligence , superconducting magnet , magnet , biology , quantum mechanics , agronomy , physics
Summary 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.