Refining and petrochemical

Our research made contributions by developing an integrated optimization model for ethylene production and a rescheduling framework for crude-oil operations. The models improved operational planning and dynamic optimization, demonstrating their feasibility and effectiveness in real-world scenarios.

Relevant publications:

S. Yang, J. Moreira, Z. Li. Bio-Inspired Encoder-Decoder Recurrent Neural Network with Attention for Hydroprocessing Unit Modeling. Industrial & Engineering Chemistry Research. 2023, 62, 18526-18540.

Z. Wang, Z. Li, Y. Feng, G. Rong. Crude Oil Operations under Uncertainty: A Continuous-time Rescheduling Framework and a Simulation Environment for Validation. Industrial & Engineering Chemistry Research. 2016, 55, 11383-11401.

Z. Wang, Z. Li, Y. Feng, G. Rong. Integrated short-term scheduling and production planning in an ethylene plant based on Lagrangean decomposition. Canadian Journal of Chemical Engineering. 2016, 94, 1723-1739.

N. Shah, Z. Li, M.G. Ierapetritou. Petroleum refining operations: key issues, advances and opportunities. Industrial & Engineering Chemistry Research, 2010, 50, 1161-1170.

M. Xue, Z. Li, G. Wu, D. Sun. Solving the oil blend scheduling optimization problem with a multi-step strategy. Journal of University of Science and Technology of China, 2006, 36, 834-839.