A bi-level model integrating planning and scheduling for the optimization of process operation and energy consumption of a PVC plant under uncertainty. (December 2022)

• Record Type: Journal Article
• Authors: Su, Jian; Wang, Yuhong
• Is Part Of: Computers & chemical engineering. Volume 168(2023)
• Publication Date: 2022-12
• Subjects: Uncertainty -- Bi-level model -- PVC scheduling -- Data-driven robust optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2022.108033
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: A data-driven bi-level model integrating planning and scheduling for PVC production is proposed. Scheduling of a mixed batch/continue process with the variable production rate under uncertainty is investigated. The practical results show the effectiveness and advantages of energy-efficient scheduling measures. Abstract: PVC production by the calcium carbide method is a typical hybrid system consisting of continuous and intermittent processing, and the optimization of the whole process scheduling is of practical significance. Still, the existence of uncertain factors in the external environment and production process makes it challenging to continue to implement deterministic scheduling. This paper, therefore, proposes an integration model, the discrete-time method applied in the planning layer, and the chance-constrained programming used to deal with external uncertainties. The continuous-time modeling method based on event points is adopted in the scheduling layer, and the optimization of equipment-level operations with variable production rates is performed. Then, the data-driven robust optimization method is applied to deal with endogenous uncertainty based on the data-driven flexible uncertainty set. Finally, the results provide valuable guidance to improve the robustness and stability of the production system under uncertainty. The comparative results verify the effectiveness and superiority of the proposed model in total cost and energy consumption.