Open Access
Issue
E3S Web Conf.
Volume 511, 2024
International Conference on “Advanced Materials for Green Chemistry and Sustainable Environment” (AMGSE-2024)
Article Number 01013
Number of page(s) 14
DOI https://doi.org/10.1051/e3sconf/202451101013
Published online 10 April 2024
  1. S. A. Shezan et al., “Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller,” Energy Reports, vol. 10, pp. 3272–3288, (2023). doi: 10.1016/j.egyr.2023.10.016. [CrossRef] [Google Scholar]
  2. X. Nie, W. S. A. W. Mohamad Daud, and J. Pu, “A novel transactive integration system for solar renewable energy into smart homes and landscape design: A digital twin simulation case study,” Solar Energy, vol. 262, (2023). doi: 10.1016/j.solener.2023.111871. [Google Scholar]
  3. A. Kumar, M. Rizwan, and U. Nangia, “A hybrid optimization technique for proficient energy management in smart grid environment,” Int J Hydrogen Energy, vol. 47, no. 8, pp. 5564–5576, (2022). doi: 10.1016/j.ijhydene.2021.11.188. [CrossRef] [Google Scholar]
  4. M. A. Hartani et al., “Proposed frequency decoupling-based fuzzy logic control for power allocation and state-of-charge recovery of hybrid energy storage systems adopting multi-level energy management for multi-DCmicrogrids,” Energy, vol. 278, (2023). doi: 10.1016/j.energy.2023.127703. [CrossRef] [Google Scholar]
  5. S. Ayub et al., “Analysis of energy management schemes for renewableenergy-based smart homes against the backdrop of COVID-19,” Sustainable Energy Technologies and Assessments, vol. 52, (2022). doi: 10.1016/j.seta.2022.102136. [CrossRef] [Google Scholar]
  6. M. Wadi, A. Shobole, W. Elmasry, and I. Kucuk, “Load frequency control in smart grids: A review of recent developments,” Renewable and Sustainable Energy Reviews, vol. 189, (2024). doi: 10.1016/j.rser.2023.114013. [CrossRef] [Google Scholar]
  7. L. Tang, T. Kong, and N. Innab, “Eagle arithmetic optimization algorithm for renewable energy-based load frequency stabilization of power systems,” Sustainable Computing: Informatics and Systems, vol. 40, (2023). doi: 10.1016/j.suscom.2023.100925. [CrossRef] [Google Scholar]
  8. A. Nouri, A. Lachheb, and L. El Amraoui, “Optimizing efficiency of Vehicle-to-Grid system with intelligent management and ANN-PSO algorithm for battery electric vehicles,” Electric Power Systems Research, vol. 226, (2024). doi: 10.1016/j.epsr.2023.109936. [CrossRef] [Google Scholar]
  9. “Fuzzy Logic-Based Energy Management in Smart Grids for Renewable Integration Search | ScienceDirect.com.” Accessed: Jan. 19, 2024. [Online]. Available: https://www.sciencedirect.com/search?qs=Fuzzy%20Logic-Based%20Energy%20Management%20in%20Smart%20Grids%20for%20Renewable%20Integration [Google Scholar]
  10. A. Bolurian, H. Akbari, S. Mousavi, and M. Aslinezhad, “Bi-level energy management model for the smart grid considering customer behavior in the wireless sensor network platform,” Sustain Cities Soc, vol. 88, (2023).doi: 10.1016/j.scs.2022.104281. [CrossRef] [Google Scholar]
  11. A. Derrouazin, M. Aillerie, N. Mekkakia-Maaza, and J. P. Charles, “Multi input-output fuzzy logic smart controller for a residential hybrid solar-windstorage energy system,” Energy Convers Manag, vol. 148, pp. 238–250, (2017). doi: 10.1016/j.enconman.2017.05.046. [CrossRef] [Google Scholar]
  12. Q. Hassan et al., “Implications of a smart grid-integrated renewable distributed generation capacity expansion strategy: The case of Iraq,” Renew Energy, vol. 221, (2024). doi: 10.1016/j.renene.2023.119753. [Google Scholar]
  13. P. Siddhartha, T. Sujeeth, B. Shiva, and J. Ramprabhakar, “Integration of Renewable Energy Sources with Power Management Strategy for Effective Bidirectional Vehicle to Grid Power Transfer,” Procedia Comput Sci, vol. 218, pp. 9–23, (2022). doi: 10.1016/j.procs.2022.12.397. [Google Scholar]
  14. A. Keshtkar and S. Arzanpour, “An adaptive fuzzy logic system for residential energy management in smart grid environments,” Appl Energy, vol. 186, pp. 68–81, (2017). doi: 10.1016/j.apenergy.2016.11.028. [CrossRef] [Google Scholar]
  15. M. Alowaidi, “Fuzzy efficient energy algorithm in smart home environment using Internet of Things for renewable energy resources,” Energy Reports, vol. 8, pp. 2462–2471, (2022). doi: 10.1016/j.egyr.2022.01.177. [CrossRef] [Google Scholar]
  16. T. Castillo-Calzadilla, R. Garay-Martinez, and C. M. Andonegui, “Holistic fuzzy logic methodology to assess positive energy district (PathPED),” Sustain Cities Soc, vol. 89, (2023). doi: 10.1016/j.scs.2022.104375. [CrossRef] [Google Scholar]
  17. A. O. Ali, M. R. Elmarghany, M. M. Abdelsalam, M. N. Sabry, and A. M. Hamed, “Closed-loop home energy management system with renewable energy sources in a smart grid: A comprehensive review,” J Energy Storage, vol. 50, (2022). doi: 10.1016/j.est.2022.104609. [Google Scholar]
  18. N. Mostafa, H. S. M. Ramadan, and O. Elfarouk, “Renewable energy management in smart grids by using big data analytics and machine learning,” Machine Learning with Applications, vol. 9, p. 100363, (2022). doi: 10.1016/j.mlwa.2022.100363. [CrossRef] [Google Scholar]
  19. N.I. Vatin, G.S. Negi, S.V. Yellanki, C. Mohan, N. Singla, “Sustainability Measures: An Experimental Analysis of AI and Big Data Insights in Industry 5.0” BIO Web of Conferences, vol. 86, pp 01072, (2024). doi : 10.1051/bioconf/20248601072 [CrossRef] [EDP Sciences] [Google Scholar]
  20. H. Khajeh, H. Laaksonen, and M. G. Simões, “A fuzzy logic control of a smart home with energy storage providing active and reactive power flexibility services,” Electric Power Systems Research, vol. 216, (2023).doi: 10.1016/j.epsr.2022.109067. [CrossRef] [Google Scholar]
  21. O. Ibrahim et al., “Development of fuzzy logic-based demand-side energy management system for hybrid energy sources,” Energy Conversion and Management: X, vol. 18, (2023).doi: 10.1016/j.ecmx.2023.100354. [CrossRef] [Google Scholar]
  22. T. Kataray et al., “Integration of smart grid with renewable energy sources: Opportunities and challenges – A comprehensive review,” Sustainable Energy Technologies and Assessments, vol. 58, (2023).doi: 10.1016/j.seta.2023.103363. [CrossRef] [Google Scholar]
  23. Z. Zheng, M. Shafique, X. Luo, and S. Wang, “A systematic review towards integrative energy management of smart grids and urban energy systems,” Renewable and Sustainable Energy Reviews, vol. 189, (2024). doi: 10.1016/j.rser.2023.114023. [CrossRef] [Google Scholar]
  24. M. Ali, M. Ahmad, M. A. Koondhar, M. S. Akram, A. Verma, and B. Khan, “Maximum power point tracking for grid-connected photovoltaic system using Adaptive Fuzzy Logic Controller,” Computers and Electrical Engineering, vol. 110, (2023).doi: 10.1016/j.compeleceng.2023.108879. [Google Scholar]
  25. A. Beheshtikhoo, M. Pourgholi, and I. Khazaee, “Design of type-2 fuzzy logic controller in a smart home energy management system with a combination of renewable energy and an electric vehicle,” Journal of Building Engineering, vol. 68, (2023).doi: 10.1016/j.jobe.2023.106097. [CrossRef] [Google Scholar]
  26. S. Deep, S. Banerjee, S. Dixit, and N. I. Vatin, “Critical Factors Influencing the Performance of Highway Projects: Empirical Evaluation of Indian Projects,” Buildings, vol. 12, no. 6, (2022). doi: 10.3390/BUILDINGS12060849. [CrossRef] [Google Scholar]
  27. C. Shyamlal et al., “Corrosion Behavior of Friction Stir Welded AA8090T87 Aluminum Alloy,” Materials, vol. 15, no. 15, (2022). doi: 10.3390/MA15155165. [CrossRef] [PubMed] [Google Scholar]
  28. G. Upadhyay et al., “Development of Carbon Nanotube (CNT)-Reinforced Mg Alloys: Fabrication Routes and Mechanical Properties,” Metals (Basel), vol. 12, no. 8, (2022). doi: 10.3390/MET12081392. [CrossRef] [Google Scholar]
  29. P. Singh et al., “Development of performance-based models for green concrete using multiple linear regression and artificial neural network,” International Journal on Interactive Design and Manufacturing, (2023). doi: 10.1007/S12008-023-01386-6. [Google Scholar]
  30. M. Makwana et al., “Effect of Mass on the Dynamic Characteristics of Singleand Double-Layered Graphene-Based Nano Resonators,” Materials, vol. 15, no. 16, (2022). doi: 10.3390/MA15165551. [CrossRef] [PubMed] [Google Scholar]
  31. Md.Z. U. Haq, H. Sood, R. Kumar, and I. Merta, “Taguchi-optimized triple-aluminosilicate geopolymer bricks with recycled sand: A sustainable construction solution,” Case Studies in Construction Materials, vol. 20, p. e02780, (2024). doi: https://doi.org/10.1016/j.cscm.2023.e02780. [CrossRef] [Google Scholar]
  32. P. B. Joshi, N. C. Durve1 and C. Mohan, “Full blown green metrics”, Elsevier Publishing, pp 109–129, (2024). doi : 10.1016/B978-0-443-189593.00013-6 [Google Scholar]
  33. M. Z. ul Haq, H. Sood, and R. Kumar, “SEM-Assisted Mechanistic Study: pH-Driven Compressive Strength and Setting Time Behavior in Geopolymer Concrete,” (2023). [Google Scholar]
  34. K. Kumar et al., “From Homogeneity to Heterogeneity: Designing Functionally Graded Materials for Advanced Engineering Applications,” in E3S Web of Conferences, EDP Sciences, p. 01198 (2023). [CrossRef] [EDP Sciences] [Google Scholar]
  35. M. Z. ul Haq et al., “Waste Upcycling in Construction: Geopolymer Bricks at the Vanguard of Polymer Waste Renaissance,” in E3S Web of Conferences, EDP Sciences, p. 01205 (2023). [CrossRef] [EDP Sciences] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.