Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Emerging Advances in Hybrid Renewable Energy Systems and Integration
|
|
---|---|---|
Numéro d'article | 81 | |
Nombre de pages | 12 | |
DOI | https://doi.org/10.2516/stet/2024070 | |
Publié en ligne | 15 octobre 2024 |
- Spichartz B., Günther K., Sourkounis C. (2022) New stability concept for primary controlled variable speed wind turbines considering wind fluctuations and power smoothing, IEEE Trans. Ind. Appl. 58, 2, 2378–2388. [CrossRef] [Google Scholar]
- Jia X., Zhang Y., Tan R.R., Li Z.W., Wang S.Q., Wang F., Fang K. (2022) Multi-objective energy planning for China’s dual carbon goals, Sustain. Prod. Consum. 34, 552–564. [CrossRef] [Google Scholar]
- Wei X., Xiangning X., Pengwei C. (2018) Overview of key microgrid technologies, Int. Trans. Electr. Energy Syst. 28, 7, 2566. [Google Scholar]
- Hafez O., Bhattacharya K. (2021) Optimal planning and design of a renewable energy based supply for micro-grids, Renew. Energy 165, 127. [CrossRef] [Google Scholar]
- Cheng H., Hu X., Wang L., Liu Y., Yu Q. (2019) Review on research of regional integrated energy system planning, Autom. Electr. Power Syst. 43, 7, 2–13 [Google Scholar]
- Gautam K.R., Andresen G.B., Victoria M. (2022) Review and techno-economic analysis of emerging thermo-mechanical energy storage technologies, Energies 15, 17, 6328. [CrossRef] [Google Scholar]
- Xu P., Wang G.C., Cai X., Shen H.Y., Jiang W.X. (2022) Design and optimization of high-efficiency meta-devices based on the equivalent circuit model and theory of electromagnetic power energy storage, J. Phys. D Appl. Phys. 55, 19, 195303. [CrossRef] [Google Scholar]
- Mathis T.S., Kurra N., Wang X., Pinto D., Simon P., Gogotsi Y. (2019) Energy storage data reporting in perspective – guidelines for interpreting the performance of electrochemical energy storage system, Adv. Energy Mater. 9, 39, 1902007. [CrossRef] [Google Scholar]
- Qingcheng Y.A.O., Xiaoling Y. (2020) Optimal configuration of independent microgrid based on Monte Carlo processing of source and load uncertainty, Energy Storage Sci. Technol. 9, 1, 186. [Google Scholar]
- Xin L., Yu H., Jing Z., Jia L. (2024) Optimal allocation of hybrid energy storage capacity based on ISSA-optimized VMD parameters. Electronics 13, 13, 2597. [CrossRef] [Google Scholar]
- Silva D.P., Salles J.L.F., Fardin J.F., Pereira M.R., Ottz V.C., Silva F.B., Pignaton E.G. (2021) Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid, Data Brief 39, 107513. [CrossRef] [PubMed] [Google Scholar]
- Barbon A., Ayuso P.F., Bayon L., Silva C.A. (2021) A comparative study between racking systems for photovoltaic power systems, Renew. Energy 180, 424–437. [CrossRef] [Google Scholar]
- Blomgren G.E. (2016) The development and future of lithium ion batteries, J. Electrochem. Soc. 164, 1, 5010–5019. [Google Scholar]
- Rahman M.M., Oni A.O., Gemechu E., Kumar A. (2020) Assessment of energy storage technologies: A review, Energy Convers. Manage. 223, 113295. [CrossRef] [Google Scholar]
- Niu P., Niu S., Chang L. (2019) The defect of the Grey Wolf optimization algorithm and its verification method. Knowl. Based Syst. 171, 37–43. [CrossRef] [Google Scholar]
- Igiri C.P., Singh Y., Poonia R.C. (2020) A review study of modified swarm intelligence: particle swarm optimization, firefly, bat and gray wolf optimizer algorithms, Recent Adv. Comput. Sci. Commun. 13, 1, 5–12. [CrossRef] [Google Scholar]
- Teng Z., Lv J., Guo L. (2019) An improved hybrid grey wolf optimization algorithm, Soft Comput. 23, 6617–6631. [CrossRef] [Google Scholar]
- Zhang Y., Li Z., Han Z.Y. (2024) Optimal configuration of energy storage capacity of micro-grid with wind and solar energy based on NSWOA, Electric. Technol. 6, 36–40. [Google Scholar]
- Li Z.W., Fan D.F., Zeng C., He L. (2024) Study on optimal configuration and Operation Strategy of energy storage system considering wind and solar absorption. Sci. Technol. Energy Storage, 1–13. https://doi.org/10.19799/j.cnki.2095-4239.2024.0165 [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.