Cite
Real-time optimization of large-scale hydrogen production systems using off-grid renewable energy: Scheduling strategy based on deep reinforcement learning.
MLA
Liang, Tao, et al. “Real-Time Optimization of Large-Scale Hydrogen Production Systems Using off-Grid Renewable Energy: Scheduling Strategy Based on Deep Reinforcement Learning.” Renewable Energy: An International Journal, vol. 224, Apr. 2024, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.renene.2024.120177.
APA
Liang, T., Chai, L., Cao, X., Tan, J., Jing, Y., & Lv, L. (2024). Real-time optimization of large-scale hydrogen production systems using off-grid renewable energy: Scheduling strategy based on deep reinforcement learning. Renewable Energy: An International Journal, 224, N.PAG. https://doi.org/10.1016/j.renene.2024.120177
Chicago
Liang, Tao, Lulu Chai, Xin Cao, Jianxin Tan, Yanwei Jing, and Liangnian Lv. 2024. “Real-Time Optimization of Large-Scale Hydrogen Production Systems Using off-Grid Renewable Energy: Scheduling Strategy Based on Deep Reinforcement Learning.” Renewable Energy: An International Journal 224 (April): N.PAG. doi:10.1016/j.renene.2024.120177.