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ENERGY MANAGEMENT POLICY SELECTION IN SMART GRIDS: A CRITIC-CoCoSo METHOD WITH Lq*q -rung ORTHOPAIR MULTI-FUZZY SOFT SETS
Authors:
Mahalakshmi Pethaperumal1
, Vimala Jayakumar1
, Dragan Pamucar2
, S Rajareega3
,
Tamil
Vizhi Mariappan1
1Department of Mathematics, Alagappa University, Karaikudi, Tamilnadu, India
2Széchenyi István University, Győr, Hungary
3Department of Basic Sciences and Humanities, GMR Institute of Technology, Rajam, India
Received: 7 January 2025
Revised: 26 February 2025
Accepted: 6 March 2025
Published: 31 March 2025
Abstract:
In response to the energy crisis and the global push for sustainability,
modern power grids are increasingly integrating renewable energy, plug-
in electric vehicles, and energy storage systems. This evolution demands
an advanced energy management system capable of handling the
variability of renewable resources, uncertainties in electric vehicle
performance, fluctuating electricity prices, and dynamic load conditions.
To address these challenges, our study introduces a novel decision-
making framework that leverages a new score function for comparing q-
rung orthopair multi-fuzzy soft numbers. This approach employs the
Criteria Importance Through Inter-criteria Correlation (CRITIC) method to
determine objective weights while simultaneously incorporating
subjective preferences through an integrated weighting scheme. The
framework is further enhanced by applying the Combined Compromise
Solution (CoCoSo) method within the Lq* q-rung orthopair multi-fuzzy
soft decision-making structure to select optimal energy management
policies. Extensive sensitivity analysis confirms the robustness and
effectiveness of the proposed methodology, offering a promising solution
for efficient energy management in modern power systems.
Keywords:
Energy management policy, Score function, Lq* q-ROMFSSs, CRITIC, CoCoSo
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© 2025 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 1
March 2025
Last Edition
Volume 10
Number 1
March 2025
How to Cite
M. Pethaperumal, V. Jayakumar, D. Pamucar, S. Rajareega, T.V. Mariappan, Energy Management Policy Selection in Smart Grids: A Critic-CoCoSo Method With Lq* q-rung Orthopair Multi-Fuzzy Soft Sets. Applied Engineering Letters, 10(1), 2025: 35-47.
https://doi.org/10.46793/aeletters.2025.10.1.4
More Citation Formats
Pethaperumal, M., Jayakumar, V., Pamucar, D., Rajareega, S., & Mariappan, T.V. (2025). Energy Management Policy Selection in Smart Grids: A Critic-CoCoSo Method With Lq* q-rung Orthopair Multi-Fuzzy Soft Sets. Applied Engineering Letters, 10(1), 35-47.
https://doi.org/10.46793/aeletters.2025.10.1.4
Pethaperumal, Mahalakshmi, et al. “Energy Management Policy Selection in Smart Grids: A Critic-CoCoSo Method With Lq* q-rung Orthopair Multi-Fuzzy Soft Sets.“ Applied Engineering Letters, vol. 10, no. 1, 2025, pp. 35-47.
https://doi.org/10.46793/aeletters.2025.10.1.4
Pethaperumal, Mahalakshmi, Vimala Jayakumar, Dragan Pamucar, S Rajareega, and Tamil Vizhi Mariappan. 2025. “Energy Management Policy Selection in Smart Grids: A Critic-CoCoSo Method With Lq* q-rung Orthopair Multi-Fuzzy Soft Sets.“ Applied Engineering Letters, 10 (1): 35-47.
https://doi.org/10.46793/aeletters.2025.10.1.4
Pethaperumal, M., Jayakumar, V., Pamucar, D., Rajareega, S. and Mariappan, T.V. (2025). Energy Management Policy Selection in Smart Grids: A Critic-CoCoSo Method With Lq* q-rung Orthopair Multi-Fuzzy Soft Sets. Applied Engineering Letters, 10(1), pp. 35-47.
doi: 10.46793/aeletters.2025.10.1.4.
Using lean manufacturing to improve process efficiency in a fabrication company
Authors:
Andra Maria Popa1
, Kapil Gupta1
1University of Johannesburg, Mechanical and Industrial Engineering Technology, Johannesburg, South Africa
Received: 29 June 2024
Revised: 20 September 2024
Accepted: 26 September 2024
Published: 30 September 2024
Abstract:
This article presents a case study on improving process efficiency in a mining equipment part fabrication company. The company was facing issues concerning communication, organisation, and workflow processes. This study investigated that ineffective communication among departments was the major weakness which was responsible for the long lead or idle time. This lead time was a waste that affected the company’s productivity. A great amount of time was spent on non-value-added processes. The Kanban Centralised Communication System was implemented. Time study and value stream mapping were also used. A significant improvement in process efficiency from 34% to 85% was achieved by reducing lead time from 4200 minutes to 1680 minutes after streamlining the communication in the company using Kanban.
Keywords:
Lean manufacturing, Kanban, Optimization, Process efficiency, Production lead time, Value stream mapping
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© 2024 by the author. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 1
March 2025
Last Edition
Volume 10
Number 1
March 2025
How to Cite
V.H. Quan, Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), 2024: 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
More Citation Formats
Quan, V.H. (2024). Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, Vu Hai, “Research and Optimization of Sport Utility Vehicle Aerodynamic Design.“ Applied Engineering Letters, vol. 9, no. 2, pp. 2024, 105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, Vu Hai, 2024. “Research and Optimization of Sport Utility Vehicle Aerodynamic Design.“ Applied Engineering Letters, 9 (2):105-115.
https://doi.org/10.46793/aeletters.2024.9.2.5
Quan, V.H. (2024). Research and Optimization of Sport Utility Vehicle Aerodynamic Design. Applied Engineering Letters, 9(2), pp. 105-115.
doi: 10.46793/aeletters.2024.9.2.5.