Novel Wind Power Station Site Selection Framework Based on Multipolar Fuzzy Schweizer-Sklar Aggregation Operators

Ali Ghous; Muhammad Anwar; Bander Almutairi; Muhammad Faheem; Sabeeha Kanwal

doi:10.1109/ACCESS.2024.3516825

Novel Wind Power Station Site Selection Framework Based on Multipolar Fuzzy Schweizer-Sklar Aggregation Operators

Ali Ghous, Muhammad Anwar, Bander Almutairi, Muhammad Faheem^*, Sabeeha Kanwal

^*Corresponding author for this work

BA4706 Smart grids

Research output: Contribution to journal › Article › Scientific › peer-review

1 Citation (Scopus)

Abstract

Nowadays, wind power stations play a significant role in eco-friendly energy production by efficiently harnessing wind energy to produce electricity. A crucial factor in constructing a wind power station is the site selection process, which identifies ideal locations for wind turbines to optimize energy generation, minimize costs, and reduce environmental impact. This complex decision-making involves multipolar attributes, including technical and environmental categories. An m-polar fuzzy (mP ^F) set model is an effective tool for addressing such uncertain problems involving multi-dimensional parameters. The main goal of this study is to integrate Schweizer-Sklar operations with mP ^F information to determine the aggregated results in a more generalized environment. We develop some novel mP ^F-geometric and mP ^F-averaging aggregation operators (A _gOs), including the mP ^F Schweizer-Sklar weighted averaging (mP ^FSSWA), mP ^F Schweizer-Sklar ordered weighted averaging (mP ^FSSOWA), mP ^F Schweizer-Sklar hybrid averaging (mP ^FSSHA), mP ^F Schweizer-Sklar weighted geometric (mP ^FSSWG), mP ^F Schweizer-Sklar ordered weighted geometric (mP ^FSSOWG), and mP ^F Schweizer-Sklar hybrid geometric (mP ^FSSHG) operators. We support these A _gOs by presenting numerical examples and some fundamental properties, like monotonicity, boundedness, idempotency, and commutativity. Further, we propose an algorithm for both mP ^FSSWA and mP ^FSSWG operators to minimize uncertainty in various MCDM problems. Next, we investigate a case study of Sindh province in Pakistan (i.e., choosing the best site for a wind power station) by implementing the suggested algorithm. Finally, we compare the developed mP ^F Schweizer-Sklar A _gOs with the preexisting mP ^F-Yagar, mP ^F-Dombi, mP ^F-Aczel-Alsina A _gOs, mP ^F-AHP (Analytical Hierarchy Process), mP ^F-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and mP ^F-ELECTRE-I (ELimination and Choice Expressing REality)-I methods.

Original language	English
Pages (from-to)	194030-194052
Number of pages	23
Journal	IEEE Access
Volume	12
DOIs	https://doi.org/10.1109/ACCESS.2024.3516825
Publication status	Published - 2024
MoE publication type	A1 Journal article-refereed

Funding

This research is supported by project number RSPD2025R650, King Saudi University, Riyadh, Saudi Arabia. The work of Muhammad Faheem is supported by the Technical Research Center VTT, Finland. This work is supported by the University of Vaasa, Vaasa, Finland; also this research is supported by researchers supporting project number RSPD2025R650, King Saudi University, Riyadh, Saudi Arabia.

Keywords

m-polar fuzzy sets
Schweizer-Sklar
aggregation operators
wind power station.
multi-criteria decisionmaking,
multi-criteria decision-making
wind power station
m-Polar fuzzy sets
Schweizer-Sklar t-norm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ACCESS.2024.3516825Licence: CC BY

Cite this

@article{436890222ac24ba7a37fc65149752072,

title = "Novel Wind Power Station Site Selection Framework Based on Multipolar Fuzzy Schweizer-Sklar Aggregation Operators",

abstract = "Nowadays, wind power stations play a significant role in eco-friendly energy production by efficiently harnessing wind energy to produce electricity. A crucial factor in constructing a wind power station is the site selection process, which identifies ideal locations for wind turbines to optimize energy generation, minimize costs, and reduce environmental impact. This complex decision-making involves multipolar attributes, including technical and environmental categories. An m-polar fuzzy (mP F) set model is an effective tool for addressing such uncertain problems involving multi-dimensional parameters. The main goal of this study is to integrate Schweizer-Sklar operations with mP F information to determine the aggregated results in a more generalized environment. We develop some novel mP F-geometric and mP F-averaging aggregation operators (A gOs), including the mP F Schweizer-Sklar weighted averaging (mP FSSWA), mP F Schweizer-Sklar ordered weighted averaging (mP FSSOWA), mP F Schweizer-Sklar hybrid averaging (mP FSSHA), mP F Schweizer-Sklar weighted geometric (mP FSSWG), mP F Schweizer-Sklar ordered weighted geometric (mP FSSOWG), and mP F Schweizer-Sklar hybrid geometric (mP FSSHG) operators. We support these A gOs by presenting numerical examples and some fundamental properties, like monotonicity, boundedness, idempotency, and commutativity. Further, we propose an algorithm for both mP FSSWA and mP FSSWG operators to minimize uncertainty in various MCDM problems. Next, we investigate a case study of Sindh province in Pakistan (i.e., choosing the best site for a wind power station) by implementing the suggested algorithm. Finally, we compare the developed mP F Schweizer-Sklar A gOs with the preexisting mP F-Yagar, mP F-Dombi, mP F-Aczel-Alsina A gOs, mP F-AHP (Analytical Hierarchy Process), mP F-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and mP F-ELECTRE-I (ELimination and Choice Expressing REality)-I methods.",

keywords = "m-polar fuzzy sets, Schweizer-Sklar, aggregation operators, wind power station., multi-criteria decisionmaking,, multi-criteria decision-making, wind power station, m-Polar fuzzy sets, Schweizer-Sklar t-norm",

author = "Ali Ghous and Muhammad Anwar and Bander Almutairi and Muhammad Faheem and Sabeeha Kanwal",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2024",

doi = "10.1109/ACCESS.2024.3516825",

language = "English",

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T1 - Novel Wind Power Station Site Selection Framework Based on Multipolar Fuzzy Schweizer-Sklar Aggregation Operators

AU - Ghous, Ali

AU - Anwar, Muhammad

AU - Almutairi, Bander

AU - Faheem, Muhammad

AU - Kanwal, Sabeeha

PY - 2024

Y1 - 2024

N2 - Nowadays, wind power stations play a significant role in eco-friendly energy production by efficiently harnessing wind energy to produce electricity. A crucial factor in constructing a wind power station is the site selection process, which identifies ideal locations for wind turbines to optimize energy generation, minimize costs, and reduce environmental impact. This complex decision-making involves multipolar attributes, including technical and environmental categories. An m-polar fuzzy (mP F) set model is an effective tool for addressing such uncertain problems involving multi-dimensional parameters. The main goal of this study is to integrate Schweizer-Sklar operations with mP F information to determine the aggregated results in a more generalized environment. We develop some novel mP F-geometric and mP F-averaging aggregation operators (A gOs), including the mP F Schweizer-Sklar weighted averaging (mP FSSWA), mP F Schweizer-Sklar ordered weighted averaging (mP FSSOWA), mP F Schweizer-Sklar hybrid averaging (mP FSSHA), mP F Schweizer-Sklar weighted geometric (mP FSSWG), mP F Schweizer-Sklar ordered weighted geometric (mP FSSOWG), and mP F Schweizer-Sklar hybrid geometric (mP FSSHG) operators. We support these A gOs by presenting numerical examples and some fundamental properties, like monotonicity, boundedness, idempotency, and commutativity. Further, we propose an algorithm for both mP FSSWA and mP FSSWG operators to minimize uncertainty in various MCDM problems. Next, we investigate a case study of Sindh province in Pakistan (i.e., choosing the best site for a wind power station) by implementing the suggested algorithm. Finally, we compare the developed mP F Schweizer-Sklar A gOs with the preexisting mP F-Yagar, mP F-Dombi, mP F-Aczel-Alsina A gOs, mP F-AHP (Analytical Hierarchy Process), mP F-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and mP F-ELECTRE-I (ELimination and Choice Expressing REality)-I methods.

AB - Nowadays, wind power stations play a significant role in eco-friendly energy production by efficiently harnessing wind energy to produce electricity. A crucial factor in constructing a wind power station is the site selection process, which identifies ideal locations for wind turbines to optimize energy generation, minimize costs, and reduce environmental impact. This complex decision-making involves multipolar attributes, including technical and environmental categories. An m-polar fuzzy (mP F) set model is an effective tool for addressing such uncertain problems involving multi-dimensional parameters. The main goal of this study is to integrate Schweizer-Sklar operations with mP F information to determine the aggregated results in a more generalized environment. We develop some novel mP F-geometric and mP F-averaging aggregation operators (A gOs), including the mP F Schweizer-Sklar weighted averaging (mP FSSWA), mP F Schweizer-Sklar ordered weighted averaging (mP FSSOWA), mP F Schweizer-Sklar hybrid averaging (mP FSSHA), mP F Schweizer-Sklar weighted geometric (mP FSSWG), mP F Schweizer-Sklar ordered weighted geometric (mP FSSOWG), and mP F Schweizer-Sklar hybrid geometric (mP FSSHG) operators. We support these A gOs by presenting numerical examples and some fundamental properties, like monotonicity, boundedness, idempotency, and commutativity. Further, we propose an algorithm for both mP FSSWA and mP FSSWG operators to minimize uncertainty in various MCDM problems. Next, we investigate a case study of Sindh province in Pakistan (i.e., choosing the best site for a wind power station) by implementing the suggested algorithm. Finally, we compare the developed mP F Schweizer-Sklar A gOs with the preexisting mP F-Yagar, mP F-Dombi, mP F-Aczel-Alsina A gOs, mP F-AHP (Analytical Hierarchy Process), mP F-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and mP F-ELECTRE-I (ELimination and Choice Expressing REality)-I methods.

KW - m-polar fuzzy sets

KW - Schweizer-Sklar

KW - aggregation operators

KW - wind power station.

KW - multi-criteria decisionmaking,

KW - multi-criteria decision-making

KW - wind power station

KW - m-Polar fuzzy sets

KW - Schweizer-Sklar t-norm

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DO - 10.1109/ACCESS.2024.3516825

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SP - 194030

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JO - IEEE Access

JF - IEEE Access

ER -

Novel Wind Power Station Site Selection Framework Based on Multipolar Fuzzy Schweizer-Sklar Aggregation Operators

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