| Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Decarbonizing Energy Systems: Smart Grid and Renewable Technologies
|
|
|---|---|---|
| Numéro d'article | 61 | |
| Nombre de pages | 12 | |
| DOI | https://doi.org/10.2516/stet/2024057 | |
| Publié en ligne | 2 septembre 2024 | |
- Hemmati M., Messadi T., Gu H., Seddelmeyer J., Hemmati M. (2024) Comparison of embodied carbon footprint of a mass timber building structure with a steel equivalent, Buildings 14, 5, 1276. https://doi.org/10.3390/buildings14051276. [CrossRef] [Google Scholar]
- Serajian S., Shamsabadi A.A., Gnani Peer Mohamed S.I., Nejati S., Bavarian M. (2024) MXenes in solid-state batteries: current status and outlook, J. Power Sources 610, 234721. https://doi.org/10.1016/j.jpowsour.2024.234721. [CrossRef] [Google Scholar]
- Ghorbani M., Wang H., Roberts N. (2024) Analytical and numerical modeling of phase change material and hybrid PCM-heat sinks for high-power wireless EV charging, Int. Commun. Heat Mass Transfer 154, 107460. https://doi.org/10.1016/j.icheatmasstransfer.2024.107460. [CrossRef] [Google Scholar]
- Ghorbani M., Wang H., Roberts N. (2023) Numerical study of thermal management systems using phase change materials integrated with heat sink for wireless super-fast charging stations of EVs in constant heat flux condition, in: ASME 2023 Heat Transfer Summer Conference, Washington, DC, USA, July 10–12, vol. 87165, ASME, p. V001T10A005. https://doi.org/10.1115/HT2023-107128. [Google Scholar]
- Mohaghegh S., Kondo S., Yemiscioglu G., Muhtaroglu A. (Dec. 2022) A novel multiplier hardware organization for finite fields defined by all-one polynomials, IEEE Trans. Circuits Syst. Express Briefs 69, 12, 5084–5088. https://doi.org/10.1109/TCSII.2022.3188567. [CrossRef] [Google Scholar]
- Kiani S., Salmanpour A., Hamzeh M., Kebriaei H. (2024) Learning robust model predictive control for voltage control of islanded microgrid, IEEE Trans. Autom. Sci. Eng. https://doi.org/10.1109/TASE.2024.3388018. [Google Scholar]
- Seifi N., Al-Mamun A. (2024) Optimizing memory access efficiency in CUDA Kernel via data layout technique, J. Comput. Commun. 12, 124–139. https://doi.org/10.4236/jcc.2024.125009. [CrossRef] [Google Scholar]
- Shokouhi S., Mu B., Thein M.W. (2023) September). Optimized path planning and control for autonomous surface vehicles using B-splines and nonlinear model predictive control, in: OCEANS 2023 – MTS/IEEE US Gulf Coast, Biloxi, MS, USA, 25–28 September, IEEE, pp. 1–9. https://doi.org/10.23919/OCEANS52994.2023.10337066. [Google Scholar]
- Atashpanjeh H., Behfar A., Haverkamp C., Verdoes M.M., Al-Ameen M.N. (2022) Intermediate help with using digital devices and online accounts: understanding the needs, expectations, and vulnerabilities of young adults, in: International Conference on Human-Computer Interaction, Springer International Publishing, Cham, pp. 3–5. https://doi.org/10.1007/978-3-031-05563-8_1. [Google Scholar]
- Nguyen V.D., Mirza S., Zakeri A., Gupta A., Khaldi K., Aloui R., Mantini P., Shah S.K., Merchant F., Merchant F. (2024) Tackling domain shifts in person re-identification: a survey and analysis, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 4149–4159. [Google Scholar]
- Hajrasouliha A., Ghahfarokhi B.S. (2021) Dynamic geo-based resource selection in LTE-V2V communications using vehicle trajectory prediction, Comput. Commun. 177, 239–254. [CrossRef] [Google Scholar]
- Monfaredi P., Emami S.M.M., Moghadam A.S. (2022) Seismic behavior of hollow-core infilled steel frames: an experimental and numerical study, J. Construct. Steel Res. 192, 107244. [CrossRef] [Google Scholar]
- Monfaredi P., Nazarpour M., Moghadam A.S. (2021) Influence of hollow-core wall panels on the cyclic behavior of different types of steel framing systems, PCI J. 66, 5, 39–53. [Google Scholar]
- Nazarpour M., Monfaredi P., Moghadam A.S. (2019) Experimental evaluation of hollow-core wall orientation in steel moment frame, PCI J. 64, 92–103. [CrossRef] [Google Scholar]
- Mozafarjazi M., Rabiee R. (2024) Experimental and numerical study on the load-bearing capacity, ductility and energy absorption of RC shear walls with opening containing zeolite and silica fume, Eng. Solid Mech. 12, 3, 237–246. [CrossRef] [Google Scholar]
- Keivanimehr M., Chamorro H.R., Zareian-Jahromi M., Segundo-Sevilla F.R., Guerrero J.M., Konstantinou C. (2021) Load shedding frequency management of microgrids using hierarchical fuzzy control, in: 2021 World Automation Congress (WAC), Taipei, Taiwan, 01–05 August, IEEE, pp. 216–221. [Google Scholar]
- Jahromi M.H.M., Tafti H.D., Hosseini S.M., Jalali A., Keivanimehr M. (2020) Maximum power point tracking of a network-connected photovoltaic system based on gravity search algorithm and fuzzy logic controller, J. Solar Energy Res. Updates 7, 52–63. [CrossRef] [Google Scholar]
- Rostam-Alilou A.A., Zhang C., Salboukh F., Gunes O. (2022) Potential use of bayesian networks for estimating relationship among rotational dynamics of floating offshore wind turbine tower in extreme environmental conditions, Ocean Eng. 244, 110230. [CrossRef] [Google Scholar]
- Rouhi K., Motlagh M.S., Dalir F., Perez J., Golzary A. (2024) Towards sustainable electricity generation: Evaluating carbon footprint in waste-to-energy plants for environmental mitigation in Iran, Energy Rep. 11, 2623–2632. [CrossRef] [Google Scholar]
- Rouhi K., Shafiepour Motlagh M., Dalir F. (2023) Developing a carbon footprint model and environmental impact analysis of municipal solid waste transportation: a case study of Tehran, Iran, J. Air Waste Manag. Assoc. 73, 12, 890–901. [CrossRef] [PubMed] [Google Scholar]
- Jasim A.M., Jasim B.H., Neagu B.-C., Alhasnawi B.N. (2023) Coordination control of a hybrid AC/DC smart microgrid with online fault detection, diagnostics, and localization using artificial neural networks, Electronics 12, 1, 187. https://doi.org/10.3390/electronics12010187. [Google Scholar]
- Alhasnawi B.N., Jasim B.H., Sedhom B.E. (2021) Distributed secondary consensus fault tolerant control method for voltage and frequency restoration and power sharing control in multi-agent microgrid, Int. J. Electr. Power Energy Syst. 133, 107251. [CrossRef] [Google Scholar]
- Alhasnawi B.N., Jasim B.H., Issa W., Esteban M.D. (2020) A novel cooperative controller for inverters of smart hybrid AC/DC microgrids, Appl. Sci. 10, 17, 6120. https://doi.org/10.3390/app10176120. [CrossRef] [Google Scholar]
- Li Q., Cui Z., Cai Y., Su Y., Wang B. (2023) Renewable-based microgrids’ energy management using smart deep learning techniques: Realistic digital twin case, Solar Energy 250, 128–138. https://doi.org/10.1016/j.solener.2022.12.030. [CrossRef] [Google Scholar]
- Tostado-Véliz M., Arévalo P., Kamel S., Zawbaa H.M., Jurado F. (2022) Home energy management system considering effective demand response strategies and uncertainties, Energy Rep. 8, 5256–5271. https://doi.org/10.1016/j.egyr.2022.04.006. [CrossRef] [Google Scholar]
- Alhasnawi B., Jasim B., Rahman Z.-A., Guerrero J., Esteban M. (2021) A novel internet of energy based optimal multi-agent control scheme for microgrid including renewable energy resources, Int. J. Environ. Res. Public Health 18, 8146. https://doi.org/10.3390/ijerph18158146. [CrossRef] [Google Scholar]
- Alhasnawi B.N., Jasim B.H. (2020) Internet of Things (IoT) for smart grids: a comprehensive review, J. Xi’an Univ. Archit. 63, 1006–7930. [Google Scholar]
- Rahman Z.-A.S.A., Jasim B.H., Al-Yasir Y.I.A., Hu Y.-F., Abd-Alhameed R.A., Alhasnawi B.N. (2021) A new fractional-order chaotic system with its analysis, synchronization, and circuit realization for secure communication applications, Mathematics 9, 20, 2593. https://doi.org/10.3390/math9202593. [CrossRef] [Google Scholar]
- Zhang W., Qiao H., Xu X., Chen J., Xiao J., Zhang K., Long Y., Zuo Y. (2022) Energy management in microgrid based on deep reinforcement learning with expert knowledge, in: Proceedings of SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), Wuhan, China, 9 December, p. 124920Z. https://doi.org/10.1117/12.2662727. [Google Scholar]
- Alhasnawi B.N., Jasim B.H., Mansoor R., Alhasnawi A.N., Rahman Z.-A.S.A., Haes Alhelou H., Guerrero J.M., Dakhil A.M., Siano P. (2022) A new Internet of Things based optimization scheme of residential demand side management system, IET Re-new. Power Gener. 16, 1992–2006. https://doi.org/10.1049/rpg2.12466. [CrossRef] [Google Scholar]
- Rahman Z.-A.S.A., Jasim B.H., Al-Yasir Y.I.A., Abd-Alhameed R.A., Alhasnawi B.N. (2021) A new no equilibrium fractional order chaotic system, dynamical investigation, synchronization, and its digital implementation, Inventions 6, 3, 49. https://doi.org/10.3390/inventions6030049. [CrossRef] [Google Scholar]
- Alhasnawi B.N., Jasim B.H., Sedhom B.E., Hossain E., Guerrero J.M. (2021) A new decentralized control strategy of microgrids in the internet of energy paradigm, Energies 14, 2183. https://doi.org/10.3390/en14082183. [CrossRef] [Google Scholar]
- Vardakas J.S., Zorba N., Verikoukis C.V. (2016) Power demand control scenarios for smart grid applications with finite number of appliances, Appl. Energy 162, 83–98. https://doi.org/10.1016/j.apenergy.2015.10.008. [CrossRef] [Google Scholar]
- Li C., Yu X., Yu W., Chen G., Wang J. (2017) Efficient computation for sparse load shifting in demand side management, IEEE Trans. Smart Grid 8, 250–261. [CrossRef] [MathSciNet] [Google Scholar]
- Alhasnawi B.N., Jasim B.H., Siano P., Alhelou H.H., Al-Hinai A. (2022) A novel solution for day-ahead scheduling problems using the IoT-based bald eagle search optimization algorithm, Inventions 7, 3, 48. https://doi.org/10.3390/inventions7030048. [CrossRef] [Google Scholar]
- Vagdoda J., Makwana D., Adhikaree A., Faika T., Kim T. (2018) A cloud-based multiagent system platform for residential microgrids towards smart grid community, in: IEEE Power & Energy Society General Meeting (PESGM), Portland, OR, USA, 24 December. [Google Scholar]
- Bahmanyar D., Razmjooy N., Mirjalili S. (2022) Multi-objective scheduling of IoT-enabled smart homes for energy management based on Arithmetic Optimization Algorithm: A Node-RED and NodeMCU module-based technique, Knowledge-Based Syst. 247, 108762. https://doi.org/10.1016/j.knosys.2022.108762. [CrossRef] [Google Scholar]
- Wang Y., Nguyen T.-L., Xu Y., Tran Q.-T., Caire R. (2020) Peer-to-peer control for networked microgrids: multi-layer and multi-agent architecture design, IEEE Trans. Smart Grid. https://doi.org/10.1109/TSG.2020.3006883. [Google Scholar]
- Wang K., Li H., Maharjan S., Zhang Y., Guo S. (2018) Green energy scheduling for demand side management in the smart grid, IEEE Trans. Green Commun. Netw. 2, 2, 596–611. [CrossRef] [Google Scholar]
- Golmohamadi H., Keypour R., Bak-Jensen B., Pillai J.R. (2019) A multi-agent based optimization of residential and industrial demand response aggregators, Int. J. Electr. Power Energy Syst. 107, 472–485. [CrossRef] [Google Scholar]
- Saremi S., Mirjalili S., Lewis A. (2017) Grasshopper optimisation algorithm: theory and application, Adv. Eng. Software 105, 30–47. [CrossRef] [Google Scholar]
- Aljarah M., Faris I., Hammouri H., Ala’M A.Z., Mirjalili S. (2019) Binary grasshopper optimisation algorithm approaches for feature selection problems, Expert Syst. Appl. 117, 267–286. [CrossRef] [Google Scholar]
- Qin P., Hu H., Yang Z. (2021) The improved grasshopper optimization algorithm and its applications, Sci. Rep. 11, 1, 23733. [Google Scholar]
- Luna A.C., Diaz N.L., Graells M., Vasquez J.C., Guerrero J.M. (2017) Mixed-integer-linear-programming-based energy management system for hybrid PV-wind-battery microgrids: modeling, design, and experimental verification, IEEE Trans. Power Electron. 32, 4, 2769–2783. https://doi.org/10.1109/TPEL.2016.2581021. [CrossRef] [Google Scholar]
- Chamandoust H., Hashemi A., Derakhshan G., Abdi B. (2017) Optimal hybrid system design based on renewable energy resources, In: 2017 Smart Grid Conference (SGC), Tehran, Iran, 20–21 December, IEEE, pp. 1–5. [Google Scholar]
- Chamandoust H., Bahramara S., Derakhshan G. (2020) Multi-objective operation of smart stand-alone microgrid with the optimal performance of customers to improve economic and technical indices, J. Energy Stor. 31, 101738. [CrossRef] [Google Scholar]
- Dashtaki A.A., Khaki M., Zand M., Nasab M.A., Sanjeevikumar P., Samavat T., Nasab M.A., Khan B. (2022) A day ahead electrical appliance planning of residential units in a smart home network using ITS-BF algorithm, Int. Trans. Electr. Energy Syst. 2022, 2549887. https://doi.org/10.1155/2022/2549887. [CrossRef] [Google Scholar]
- Song Z., Guan X., Cheng M. (2022) Multi-objective optimization strategy for home energy management system including PV and battery energy storage, Energy Rep. 8, 5396–5411. https://doi.org/10.1016/j.egyr.2022.04.023. [CrossRef] [Google Scholar]
Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.
Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.
Le chargement des statistiques peut être long.