TY - JOUR
T1 - Hesitant fuzzy for conflicting criteria in multi-objective deployment of electric vehicle charging stations
AU - Panah, Payam Ghaebi
AU - Bornapour, Seyyed Mohammad
AU - Nosratabadi, Seyyed Mostafa
AU - Guerrero, Josep M.
N1 - Funding Information:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/10
Y1 - 2022/10
N2 - The penetration rate of electric vehicles is expected to experience continual growth. The expansion planning of charging stations includes conflicting interests in urban distribution systems. This paper addresses three different viewpoints from stakeholders, municipalities, and DSOs who may not easily agree on unanimous interests in infrastructure developments. A multi-objective optimization approach is suggested regarding profit, greenhouse gas (GHG) emission, and voltage profile. The vagueness and contradiction of experts’ opinions are taken into account. Multi-Criteria Decision Making (MCDM) techniques are employed to prioritize the candidates. Besides, uncertainties of price, load, and number of available electric vehicles are considered and the best solutions are selected using Crow Search Algorithm (CSA). Hesitant Fuzzy Independent Judgement (HFIJ), Analytic Hierarchy Process (AHP), and Hesitant Fuzzy AHP mechanisms are implemented to vote for the best expansion solution. IEEE 69-bus test system with modified loads along with the market data from Nordpool are considered in simulations. Sensitivity analysis is also provided to assess the solidity of MCDM. The results show that HFAHP makes more concrete and consistent assembly choices that even 30% variations in weighting coefficients cannot change the alternative rankings.
AB - The penetration rate of electric vehicles is expected to experience continual growth. The expansion planning of charging stations includes conflicting interests in urban distribution systems. This paper addresses three different viewpoints from stakeholders, municipalities, and DSOs who may not easily agree on unanimous interests in infrastructure developments. A multi-objective optimization approach is suggested regarding profit, greenhouse gas (GHG) emission, and voltage profile. The vagueness and contradiction of experts’ opinions are taken into account. Multi-Criteria Decision Making (MCDM) techniques are employed to prioritize the candidates. Besides, uncertainties of price, load, and number of available electric vehicles are considered and the best solutions are selected using Crow Search Algorithm (CSA). Hesitant Fuzzy Independent Judgement (HFIJ), Analytic Hierarchy Process (AHP), and Hesitant Fuzzy AHP mechanisms are implemented to vote for the best expansion solution. IEEE 69-bus test system with modified loads along with the market data from Nordpool are considered in simulations. Sensitivity analysis is also provided to assess the solidity of MCDM. The results show that HFAHP makes more concrete and consistent assembly choices that even 30% variations in weighting coefficients cannot change the alternative rankings.
KW - Crow Search Algorithm
KW - E-Transport
KW - GHG Emission Reduction
KW - Multi-Criteria Decision Making
KW - Voltage Profile
UR - http://www.scopus.com/inward/record.url?scp=85134304199&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2022.104054
DO - 10.1016/j.scs.2022.104054
M3 - Journal article
AN - SCOPUS:85134304199
SN - 2210-6707
VL - 85
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 104054
ER -