Open Access
| Issue |
E3S Web Conf.
Volume 441, 2023
2023 International Conference on Clean Energy and Low Carbon Technologies (CELCT 2023)
|
|
|---|---|---|
| Article Number | 01008 | |
| Number of page(s) | 8 | |
| Section | Clean Energy Utilization and Energy Storage Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202344101008 | |
| Published online | 07 November 2023 | |
- Aguero J. L., Beroqui M., Achilles S. Aluminum plant load modeling for stability studies[C]. IEEE Power Engineering Society Summer Meeting, Alberta, Canada, 1999: 1–6. [Google Scholar]
- Xu J., Liao S., Sun Y., et al. An isolated industrial power system driven by wind-coal power for aluminum productions: a case study of frequency control[J]. Power Systems, IEEE Transactions on, 2015, 30 (1): 471–483. [CrossRef] [Google Scholar]
- Paulus M., Borggrefe F. The potential of demandside management in energy-intensive industries for electricity markets in Germany[J]. Applied Energy, 2011, 88 (2): 432–441. [CrossRef] [Google Scholar]
- Jiang H., Lin J., Song Y. Demand side frequency control scheme in an isolated wind power system for industrial aluminum smelting production[J]. IEEE Transactions on Power Systems, 2014, 29 (2): 844853. [Google Scholar]
- Li Duo. “Study on Integrated Load Modeling of Distribution Networks in Industrial Parks withDistributed Generation from Multiple Energy Sources” [D]. North China University of Water Resources and Electric Power, 2018. [Google Scholar]
- Song Yuexin. “Research on the Key Technology for Precise Management of Electricity Demand under Industrial Load” [D]. University of Jinan, 2020. [Google Scholar]
- Guo Cheng, Zhu Runlin, Meng Xian, Xie Hao, He Peng, Ye Zhuang, and Yang Lei. “Modeling Method of Electrolytic Aluminum Impact Load Based on Gray Wolf Optimization Algorithm” [J]. Electric Engineering, 2021 (11): 65–70. [Google Scholar]
- Chen Yuanfeng. “Research on Frequency Control Strategy of Isolated Grids with High-Permeability Wind Power Based on Poly-Silicon Load Control” [D]. Wuhan: Wuhan University, 2018. [Google Scholar]
- Tu Xiazhe. “Research on Frequency Control of Local Area Network in the Iron and Steel Industry Based on Load Regulation of Submerged Arc Furnace” [D]. Wuhan University, 2018. [Google Scholar]
- Ruan Wenjun, Liu Sha, and Li Yang. “A Review of Demand Response in the United States” [J]. Power Demand Side Management, 2013 (2): 61–64. [Google Scholar]
- Wang Haibo and Zhang Li. “Supply-Demand Interactive Scheduling Model Considering Short Production Process of Steel Enterprises” [J]. Automation of Electric Power Systems, 2021, 45 (15): 64–76. DOI: 10.7500/AEPS20201002004. [Google Scholar]
- Liao S., Xu J., Sun Y., et al. Control of EnergyIntensive Load for Power Smoothing in Wind Power Plants[J]. Power Systems IEEE Transactions on, 2018, 33 (6): 6142–6154. [CrossRef] [Google Scholar]
- Nosratabadi S. M., Hooshmand R. A., Gholipour E. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy[J]. Applied Energy, 2016, 164:590–606. [CrossRef] [Google Scholar]
- Ji Jin. “Research on the Chance Constrained Model on the Participation of Energy-Intensive Enterprises in Wind Power Consumption” [D]. Lanzhou University of Technology, 2014. [Google Scholar]
- X. Zhang, G. Hug, J. Z. Kolter and I. Harjunkoski, “Demand Response of Ancillary Service From Industrial Loads Coordinated With Energy Storage”, in IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 951–961, Jan. 2018, DOI: 10.1109/TPWRS.2017.2704524. [CrossRef] [Google Scholar]
- Liao S., Xu J., Sun Y., Bao Y. Control of EnergyIntensive Load for Power Smoothing in Wind Power Plants. IEEE Transactions on Power Systems 2018; 33(6): 6142–6154. [CrossRef] [Google Scholar]
- Bao Yi. “Research on the Participation of EnergyIntensive Electrolytic Aluminum Load in the Frequency Regulation of the Power System and Auxiliary Service Strategy” [D]. Wuhan University, 2019. [Google Scholar]
- Xu J., Liao S., Sun Y. An isolated industrial power system driven by wind-coal power for aluminum production: a case study of frequency control[J]. IEEE Transactions on Power Systems, 2015, 30 (1): 471–483. [CrossRef] [Google Scholar]
- Huang C., Yue D., Xie J. Economic dispatch of power systems with virtual power plant based interval optimization method[J]. CSEE Journal of Power and Energy Systems, 2016, 2 (1): 74–80. [CrossRef] [Google Scholar]
- Samimi A., Nikzad M., Kazemi A. Coupled active and reactive market in smart distribution system considering renewable distributed energy resources and demand response programs[J]. International Transactions on Electrical Energy Systems, 2017, 27 (4): 2268–2280. [Google Scholar]
- Muller F. L., Szabo J., Sundstrom, O. Aggregation and disaggregation of energetic flexibility from distributed energy resources[J]. IEEE Transactions on Smart Grid, 2019, 10 (2): 1205–1214. [CrossRef] [Google Scholar]
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