Model predictive control of plug-in hybrid electric vehicles for frequency regulation in a smart grid

Integration between energy storage systems and renewable energy sources (RESs) can effectively smooth natural fluctuations of the latter and ensure better frequency regulation. Optimal performance of the plug-in hybrid electric vehicle (PEHV) battery, having longer plug-in than driving time, makes i...

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Published inIET generation, transmission & distribution Vol. 11; no. 16; pp. 3974 - 3983
Main Authors Elsisi, M, Soliman, Mahmoud, Aboelela, Magdy A.S, Mansour, W
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 09.11.2017
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ISSN1751-8687
1751-8695
DOI10.1049/iet-gtd.2016.2120

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Abstract Integration between energy storage systems and renewable energy sources (RESs) can effectively smooth natural fluctuations of the latter and ensure better frequency regulation. Optimal performance of the plug-in hybrid electric vehicle (PEHV) battery, having longer plug-in than driving time, makes it a good candidate for integration with RESs. Decentralised model predictive control (MPC) is proposed here for frequency regulation in a smart three-area interconnected power system comprising PHEVs. Two MPCs in each area are considered to manipulate the input signals of the governor and PHEV in order to tolerate frequency perturbations subject to load disturbances and RES fluctuations. Setting the parameters of the six MPC controllers is carried out simultaneously based on imperialist competitive algorithm (ICA) and bat-inspired algorithm (BIA). Time-domain based objective function is suggested to account for system non-linearities emanating from governor dead bands and turbine generation rate constraints. The proposed tuning procedures utilising ICA and BIA are completely accomplished off-line. Comparative simulation results are presented to confirm the effectiveness of the proposed design.
AbstractList Integration between energy storage systems and renewable energy sources (RESs) can effectively smooth natural fluctuations of the latter and ensure better frequency regulation. Optimal performance of the plug‐in hybrid electric vehicle (PEHV) battery, having longer plug‐in than driving time, makes it a good candidate for integration with RESs. Decentralised model predictive control (MPC) is proposed here for frequency regulation in a smart three‐area interconnected power system comprising PHEVs. Two MPCs in each area are considered to manipulate the input signals of the governor and PHEV in order to tolerate frequency perturbations subject to load disturbances and RES fluctuations. Setting the parameters of the six MPC controllers is carried out simultaneously based on imperialist competitive algorithm (ICA) and bat‐inspired algorithm (BIA). Time‐domain based objective function is suggested to account for system non‐linearities emanating from governor dead bands and turbine generation rate constraints. The proposed tuning procedures utilising ICA and BIA are completely accomplished off‐line. Comparative simulation results are presented to confirm the effectiveness of the proposed design.
Author Soliman, Mahmoud
Elsisi, M
Mansour, W
Aboelela, Magdy A.S
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Issue 16
Keywords MPC
governor input signal manipulation
frequency perturbations
imperialist competitive algorithm
PEHV battery
governor dead bands
smart power grids
decentralised control
smart three-area interconnected power system
energy storage systems
energy storage
power system interconnection
system nonlinearities
BIA
RES fluctuations
smart grid
battery powered vehicles
renewable energy sources
turbine generation rate constraints
ICA
plug-in hybrid electric vehicles
time-domain based objective function
time-domain analysis
load disturbances
frequency control
frequency regulation
bat-inspired algorithm
hybrid electric vehicles
predictive control
decentralised model predictive control
Language English
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Snippet Integration between energy storage systems and renewable energy sources (RESs) can effectively smooth natural fluctuations of the latter and ensure better...
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SubjectTerms battery powered vehicles
bat‐inspired algorithm
BIA
decentralised control
decentralised model predictive control
energy storage
energy storage systems
frequency control
frequency perturbations
frequency regulation
governor dead bands
governor input signal manipulation
hybrid electric vehicles
ICA
imperialist competitive algorithm
load disturbances
MPC
PEHV battery
plug‐in hybrid electric vehicles
power system interconnection
predictive control
renewable energy sources
RES fluctuations
Research Article
smart grid
smart power grids
smart three‐area interconnected power system
system nonlinearities
time‐domain analysis
time‐domain based objective function
turbine generation rate constraints
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Title Model predictive control of plug-in hybrid electric vehicles for frequency regulation in a smart grid
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