Load Frequency Control in Microgrids Based on a Stochastic Non-Integer Controller

Mohammad Hassan Khooban, Taher Niknam, Mokhtar ShaSadeghi, Tomislav Dragicevic, Frede Blaabjerg

Research output: Contribution to journalJournal articleResearchpeer-review

39 Citations (Scopus)

Abstract

In this paper, an adaptive multi-objective Fractional-Order Fuzzy proportional-integral-derivative (MOFOFPID) controller is proposed for the load frequency control (LFC) of islanded Microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources (RESs), a new multi-objective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm (MBHA) is utilized for the adaptive tuning of the non-integer fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop (HIL) simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.
Original languageEnglish
JournalI E E E Transactions on Sustainable Energy
Volume9
Issue number2
Pages (from-to)853-862
Number of pages9
ISSN1949-3029
DOIs
Publication statusPublished - 2018

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Controllers
Electric vehicles
Renewable energy resources
Solar radiation
Energy storage
Tuning
Derivatives
Hardware
Degradation
Costs

Keywords

  • Load frequency control (LFC), modified black hole algorithm (MBHA), microgrid (MG), fractional controller, electric-vehicle (EV).

Cite this

@article{5d244919207e40c490dea646fcb4bc28,
title = "Load Frequency Control in Microgrids Based on a Stochastic Non-Integer Controller",
abstract = "In this paper, an adaptive multi-objective Fractional-Order Fuzzy proportional-integral-derivative (MOFOFPID) controller is proposed for the load frequency control (LFC) of islanded Microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources (RESs), a new multi-objective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm (MBHA) is utilized for the adaptive tuning of the non-integer fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop (HIL) simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.",
keywords = "Load frequency control (LFC), modified black hole algorithm (MBHA), microgrid (MG), fractional controller, electric-vehicle (EV).",
author = "Khooban, {Mohammad Hassan} and Taher Niknam and Mokhtar ShaSadeghi and Tomislav Dragicevic and Frede Blaabjerg",
year = "2018",
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issn = "1949-3029",
publisher = "IEEE",
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Load Frequency Control in Microgrids Based on a Stochastic Non-Integer Controller. / Khooban, Mohammad Hassan; Niknam, Taher; ShaSadeghi, Mokhtar; Dragicevic, Tomislav; Blaabjerg, Frede.

In: I E E E Transactions on Sustainable Energy, Vol. 9, No. 2, 2018, p. 853-862.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Load Frequency Control in Microgrids Based on a Stochastic Non-Integer Controller

AU - Khooban, Mohammad Hassan

AU - Niknam, Taher

AU - ShaSadeghi, Mokhtar

AU - Dragicevic, Tomislav

AU - Blaabjerg, Frede

PY - 2018

Y1 - 2018

N2 - In this paper, an adaptive multi-objective Fractional-Order Fuzzy proportional-integral-derivative (MOFOFPID) controller is proposed for the load frequency control (LFC) of islanded Microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources (RESs), a new multi-objective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm (MBHA) is utilized for the adaptive tuning of the non-integer fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop (HIL) simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.

AB - In this paper, an adaptive multi-objective Fractional-Order Fuzzy proportional-integral-derivative (MOFOFPID) controller is proposed for the load frequency control (LFC) of islanded Microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources (RESs), a new multi-objective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm (MBHA) is utilized for the adaptive tuning of the non-integer fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop (HIL) simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.

KW - Load frequency control (LFC), modified black hole algorithm (MBHA), microgrid (MG), fractional controller, electric-vehicle (EV).

U2 - 10.1109/TSTE.2017.2763607

DO - 10.1109/TSTE.2017.2763607

M3 - Journal article

VL - 9

SP - 853

EP - 862

JO - I E E E Transactions on Sustainable Energy

JF - I E E E Transactions on Sustainable Energy

SN - 1949-3029

IS - 2

ER -