Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 7108023 |
| Pages (from-to) | 64-76 |
| Number of pages | 13 |
| Journal | IEEE Robotics and Automation Magazine |
| Volume | 22 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 1 2015 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering