Detail publikace
A hybrid risk analysis model for wind farms using Coloured Petri Nets and interpretive structural modelling
Zeinalnezhad, M. Chofreh, A.G. Goni, F.A. Hashemi, L.S. Klemeš, J.J.
Anglický název
A hybrid risk analysis model for wind farms using Coloured Petri Nets and interpretive structural modelling
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
en
Originální abstrakt
This research presents an integrated approach combining Coloured Petri Nets and Interpretive Structural Modelling, called hybrid ISM-CPN model, to risk assessment of wind farms development. The dynamic nature of the component elements of wind farms and considering the risks interdependencies motivate this combination. A questionnaire survey targeting experts is conducted for calculating the modified Risk Priority Numbers (RPNs). Thirty-four factors are ranked, and the nine critical risks identified as “Political instability”, “Sanctions”, “Economic insecurity”, “Interest rate fluctuations”, “Exchange rate fluctuations”, “Inflation rate fluctuations”, “Feasibility risk”, “Shortage of capital risk”, and “Supplier risk”. The values of RPNT = 260.26, RPNC = 251.31, and RPNQ = 238.77 indicate that “Exchange rate fluctuations” is the most important critical risk. The second one, is “Political instability” with RPNT = 255.35, RPNC = 247.28, and RPNQ = 230.56. The simulation results of a 50 MW wind farm reveal, with a 90% confidence level, “Sanctions” would cause 43.9% increase in project execution time and 28% decrease in project quality, and “Shortage of capital risk” has the greatest impact on project cost, with a 25.79% increase. This work further proposes several strategies to respond to the CRs and concludes that investments in REs can support post-COVID-19 economic recovery. © 2021 Elsevier Ltd
Anglický abstrakt
This research presents an integrated approach combining Coloured Petri Nets and Interpretive Structural Modelling, called hybrid ISM-CPN model, to risk assessment of wind farms development. The dynamic nature of the component elements of wind farms and considering the risks interdependencies motivate this combination. A questionnaire survey targeting experts is conducted for calculating the modified Risk Priority Numbers (RPNs). Thirty-four factors are ranked, and the nine critical risks identified as “Political instability”, “Sanctions”, “Economic insecurity”, “Interest rate fluctuations”, “Exchange rate fluctuations”, “Inflation rate fluctuations”, “Feasibility risk”, “Shortage of capital risk”, and “Supplier risk”. The values of RPNT = 260.26, RPNC = 251.31, and RPNQ = 238.77 indicate that “Exchange rate fluctuations” is the most important critical risk. The second one, is “Political instability” with RPNT = 255.35, RPNC = 247.28, and RPNQ = 230.56. The simulation results of a 50 MW wind farm reveal, with a 90% confidence level, “Sanctions” would cause 43.9% increase in project execution time and 28% decrease in project quality, and “Shortage of capital risk” has the greatest impact on project cost, with a 25.79% increase. This work further proposes several strategies to respond to the CRs and concludes that investments in REs can support post-COVID-19 economic recovery. © 2021 Elsevier Ltd
Klíčová slova anglicky
Coloured petri networks; COVID-19; Interpretive structural modelling; Renewable energy; Risk analysis; Wind farm
Vydáno
15.08.2021
Nakladatel
Elsevier Ltd.
Místo
PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
ISSN
0360-5442
Číslo
229
Strany od–do
120696–120696
Počet stran
13
BIBTEX
@article{BUT171838,
author="Abdoulmohammad {Gholamzadeh Chofreh} and Feybi Ariani {Goni} and Jiří {Klemeš},
title="A hybrid risk analysis model for wind farms using Coloured Petri Nets and interpretive structural modelling",
year="2021",
number="229",
month="August",
pages="120696--120696",
publisher="Elsevier Ltd.",
address="PERGAMON-ELSEVIER SCIENCE LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND",
issn="0360-5442"
}