3 years ago

Robust Engineering Strategy for Scheduling Optimization of Refinery Fuel Gas System

Robust Engineering Strategy for Scheduling Optimization
of Refinery Fuel Gas System
Jiandong Zhang, Gang Rong, Zuwei Liao, Hao Zhao, Yi Zhang
As a byproduct of the oil refining process, fuel gas is the primary energy source of refineries. Considering self-generated and purchased fuel gas simultaneously in an optimization model will cut down energy cost and reduce carbon emissions in oil refineries. A mixed-integer linear program (MILP) has been built in our previous work. However, due to the fluctuation in the fuel gas generation and consumption, theoretical scheduling solutions may become infeasible or inaccurate. This article presents a robust engineering strategy for validating the model to variable conditions in four aspects: model precision, solving performance, optimization effect, and execution. The proposed strategy has been applied to a fuel gas system in one of the largest oil refineries (LRF) in China to ensure model feasibility, necessity, and effectiveness. The implementation results show that the proposed method reduces costs up to 5.63% through the single-period operational optimization and up to 7.76% in the multiperiod scheduling.

Publisher URL: http://dx.doi.org/10.1021/acs.iecr.7b02894

DOI: 10.1021/acs.iecr.7b02894

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.