To effectively operate a refinery and make it competitive, efficient short-term scheduling techniques that utilize commercial software tools for practical applications need to be developed. However, cumbersome details make it difficult to solve the short-term scheduling problem (STSP) of crudeoil operations, and mathematical programming models fail to meet the industrial needs. This article proposes an innovative control-theoretic and formal model-based method to tackle this long-standing issue. This method first models the STSP as a hybrid Petri net (PN) and then derives critically important schedulability conditions. The conditions are used to decompose a complex problem into several tractable subproblems. In each subproblem, there are either continuous variables or discrete variables. For subproblems with continuous variables, this work proposes a linear programming-based method to solve them; while, for subproblems with discrete variables, this work adopts efficient heuristics. Consequently, the STSP is efficiently resolved, and the application of the proposed method is well illustrated via industrial case studies.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering