Crude-Oil Scheduling Network in Smart Field Under Cyber-Physical System

• Main Authors: Hang Qin, Zhu Han
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Cyber-physical system (CPS); smart field; crude-oil scheduling; fractional programming; Dinkelbach method; tailored outer approximation
• Online Access: https://ieeexplore.ieee.org/document/8758138/

The smart field has drawn much attention for the field business functions to be tied into a smoothly operating system. However, its operation decisions still cannot meet the ever-increasing multiple data source requirements. This paper proposes a novel smart field cyber-physical system (SF-CPS), which comprises some sensors transmitting real-time sensed information between the marine terminals and the petroleum refinery, and an asset optimization-based decision maker using the pumping schedule to determine the best configuration. From a unique functional unit perspective, the resource allocation of volumes and qualities is implemented with the Dinkelbach method to address this enterprise-wide optimization. Taking advantage of the unloading flows at a low cost, we settle the state variables to the steady process of refinery planning, and then, the next multi-operations sequence follows the tailored outer approximation approach for decomposition to achieve high-cost efficiency. Moreover, the two-phase stochastic scheduling decisions coupled with inventory levels hosted on the SF-CPS platform can cope well with uncertainty in the process between the oil supply and maritime conditions. The experimental results validate the proposed techniques for typical oil and gas resources.