| Issue |
Sci. Tech. Energ. Transition
Volume 79, 2024
Decarbonizing Energy Systems: Smart Grid and Renewable Technologies
|
|
|---|---|---|
| Article Number | 67 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.2516/stet/2024071 | |
| Published online | 24 September 2024 | |
- Mayhorn E., Xie L., Butler-Purry K. (2016) Multi-time scale coordination of distributed energy resources in isolated power systems, IEEE Trans. Smart Grid 8, 2, 998–1005. [Google Scholar]
- Yang M., Cui Y., Huang D., Su X., Wu G. (2022) Multi-time-scale coordinated optimal scheduling of integrated energy system considering frequency out-of-limit interval, Int. J. Electr. Power Energy Syst. 141, 108268. [CrossRef] [Google Scholar]
- Yang H., Li M., Jiang Z., Zhang P. (2020) Multi-time scale optimal scheduling of regional integrated energy systems considering integrated demand response, IEEE Access 8, 5080–5090. [CrossRef] [Google Scholar]
- Tian Y., Fan L., Tang Y., Wang K., Li G., Wang H. (2018) A coordinated multi-time scale robust scheduling framework for isolated power system with ESU under high RES penetration, IEEE Access 6, 9774–9784. [CrossRef] [Google Scholar]
- Wang L.X., Zheng J.H., Li M.S., Lin X., Jing Z.X., Wu P.Z., Wu Q.H., Zhou X.X. (2019) Multi-time scale dynamic analysis of integrated energy systems: An individual-based model, Appl. Energy 237, 848–861. [CrossRef] [Google Scholar]
- Chen Y., Liu Y. (2005) Summary of singular perturbation modeling of multi-time scale power systems, in: 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific, Dalian, China, 18 August, IEEE, pp. 1–4. [Google Scholar]
- Li P., Wang Z., Wang J., Guo T., Yin Y. (2021) A multi-time-space scale optimal operation strategy for a distributed integrated energy system, Appl. Energy 289, 116698. [CrossRef] [Google Scholar]
- Liu J., Huang X., Li Z. (2019) Multi-time scale optimal power flow strategy for medium-voltage DC power grid considering different operation modes, J. Mod. Power Syst. Clean Energy 8, 1, 46–54. [Google Scholar]
- Boroojeni K.G., Amini M.H., Bahrami S., Iyengar S.S., Sarwat A.I., Karabasoglu O. (2017) A novel multi-time-scale modeling for electric power demand forecasting: From short-term to medium-term horizon, Electr. Power Syst. Res. 142, 58–73. [CrossRef] [Google Scholar]
- Cheng S., Wang R., Xu J., Wei Z. (2021) Multi-time scale coordinated optimization of an energy hub in the integrated energy system with multi-type energy storage systems, Sustain. Energy Technol. Assess. 47, 101327. [Google Scholar]
- Zhu J., Liu Q., Xiong X., Ouyang J., Xuan P., Xie P., Zou J. (2019) Multi-time-scale robust economic dispatching method for the power system with clean energy, J. Eng. 2019, 16, 1377–1381. [Google Scholar]
- Xia Y., Wei W., Yu M., Peng Y., Tang J. (2017) Decentralized multi-time scale power control for a hybrid AC/DC microgrid with multiple subgrids, IEEE Trans. Power Electron. 33, 5, 4061–4072. [Google Scholar]
- Li S., Gu C., Zeng X., Zhao P., Pei X., Cheng S. (2021) Vehicle-to-grid management for multi-time scale grid power balancing, Energy 234, 121201. [CrossRef] [Google Scholar]
- Hou T., Fang R., Yang D., Zhang W., Tang J. (2022) Energy storage system optimization based on a multi-time scale decomposition-coordination algorithm for wind-ESS systems, Sustain. Energy Technol. Assess. 49, 101645. [Google Scholar]
- Hu K., Wang B., Cao S., Li W., Wang L. (2022) A novel model predictive control strategy for multi-time scale optimal scheduling of integrated energy system, Energy Rep. 8, 7420–7433. [CrossRef] [Google Scholar]
- Chen M., Cheng Z., Liu Y., Cheng Y., Tian Z. (2020) Multitime-scale optimal dispatch of railway FTPSS based on model predictive control, IEEE Trans. Transp. Electrif. 6, 2, 808–820. [CrossRef] [Google Scholar]
- Zhang H., Wang K., Dong W. (2024) Research on multi-time scale optimal scheduling of integrated energy system based on digital twinning, J. Phys. Conf. Ser. 2728, 1, 012018. [CrossRef] [Google Scholar]
- Fang X., Dong W., Wang Y., Yang Q. (2024) Multi-stage and multi-timescale optimal energy management for hydrogen-based integrated energy systems, Energy 286, 129576. [CrossRef] [Google Scholar]
- Liu Z., Fan G., Meng X., Hu Y., Wu D., Jin G., Li G. (2024) Multi-time scale operation optimization for a near-zero energy community energy system combined with electricity-heat-hydrogen storage, Energy 291, 130397. [CrossRef] [Google Scholar]
- Li X., Ma R., Yan S., Wang S., Yang D., Xu S., Wang L. (2020) Multi-timescale cooperated optimal dispatch strategy for ultra-large-scale storage system, Energy Rep. 6, 1–8. [CrossRef] [Google Scholar]
- Wang Y., Tang B. (2024) A multi-timescale optimization method for integrated energy systems with carbon capture and accounting, J. Comput. Methods Sci. Eng. 24, 1, 69–86. [CrossRef] [Google Scholar]
- Li X., Wang H. (2024) Integrated energy system model with multi-time scale optimal dispatch method based on a demand response mechanism, J. Clean. Prod. 445, 141321. [CrossRef] [Google Scholar]
- Zhou Y., Guo S., Xu F., Cui D., Ge W., Chen X., Gu B. (2020) Multi-time scale optimization scheduling strategy for combined heat and power system based on scenario method, Energies 13, 7, 1599. [CrossRef] [Google Scholar]
- Sun Y., Hui H., Qi T., Chen L. (2024) Multitime scale optimization of urban micro-grids considering high penetration of PVS and heterogeneous energy storage systems, IEEE Internet Things J., 11, 14, 24428–24438. https://doi.org/10.1109/JIOT.2024.3354803. [CrossRef] [Google Scholar]
- Wang G., Pan C., Wu W., Fang J., Hou X., Liu W. (2024) Multi-time scale optimization study of integrated energy system considering dynamic energy hub and dual demand response, Sustain. Energy, Grids Netw. 38, 101286. [CrossRef] [Google Scholar]
- Ma T., Li M.J., Xu H., Jiang R., Ni J.W. (2024) Study on multi-time scale frequency hierarchical control method and dynamic response characteristics of the generation-grid-load-storage type integrated system under double-side randomization conditions, Appl. Energy 367, 123436. [CrossRef] [Google Scholar]
- Yang M., Cui Y., Huang D., Su X., Wu G. (2022) Multi-time-scale coordinated optimal scheduling of integrated energy system considering frequency out-of-limit interval, Int. J. Electr. Power Energy Syst. 141, 108268. [CrossRef] [Google Scholar]
- Tian Y., Fan L., Tang Y., Wang K., Li G., Wang H. (2018) A coordinated multi-time scale robust scheduling framework for isolated power system with ESU under high RES penetration, IEEE Access 6, 9774–9784. [CrossRef] [Google Scholar]
- Qin Y., Liu P., Li Z. (2022) Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia, Renew. Sustain. Energy Rev. 169, 112911. [CrossRef] [Google Scholar]
- Hou T., Fang R., Yang D., Zhang W., Tang J. (2022) Energy storage system optimization based on a multi-time scale decomposition-coordination algorithm for wind-ESS systems, Sustain. Energy Technol. Assess. 49, 101645. [Google Scholar]
- Huang Y., Sun Q., Li Y., Gao W., Gao D.W. (2022) A multi-rate dynamic energy flow analysis method for integrated electricity-gas-heat system with different time-scale, IEEE Trans. Power Deliv. 38, 1, 231–243. [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.