Credit to Author: Ben Chang| Date: Thu, 19 Mar 2020 17:30:40 +0000
Across the globe, process industry firms, including those serving downstream oil & gas industry supply chains, are actively seeking opportunities to modernize and optimize their operations. In Taiwan, stakeholders managing a leading refinery have made it a priority to focus on two areas for reducing operational expenses and increasing profits: energy consumption reduction and increases in throughput. They are deploying a unique combination of advanced process control (APC) and artificial intelligence (AI) technologies across critical application areas (like crude oil distillation) in order to cut costs.
Because crude oil is extracted from the ground, the salt content within the crude can be high which can quickly erode pipelines. Therefore, the first desalination process removes salt. Then, in devices called fractionating columns, end products like liquefied natural gas, light oil, aviation fuel, diesel, and heavy oil are vaporized at different points, extracted from the crude, and then distributed to global markets.
Petrochemical processing operations are complex and require a high level of precise control over temperatures, chemical blending and refinement sequencing procedures. The processing of the raw materials is complicated. The crude oil components from the supplier oil wells are completely different from each other, and the production process is required to output multiple products simultaneously. The number of process variables is very high and the potential for cost-generating delays and errors are always present. For these reasons, the refinery invested in a team focused on the use of AI and APC technologies for reducing costs and generating higher profits.
Experts converge to improve operational predictability
Although technology plays a critical role managing the complexities, human expertise is required to properly design such systems and to make them operate in a predictable, efficient manner. This is where companies like Schneider Electric and AVEVA, equipped with a rich portfolio of high precision control hardware and software and a local team of experienced software and chemical engineers provided support.
To help the refinery decrease energy costs, our local Taiwan team delivered an advanced process control system to reduce process variability and stabilize unit operations. The net result was the ability to process materials closer to their operating constraint limits within distillation tanks (a standard deviation improvement of approximately 50%) which has translated into lower net energy consumption per unit of throughput,
This system also helps to determine the processing scenarios required to achieve the desired production rate of products at maximum profit, or minimum cost, while satisfying the refinery’s fuel supply obligations. The result is greater operating flexibility in response to changing market and plant conditions, and improved reliability. In fact, plant operators are reporting throughput improvements and energy savings of approximately $4.2 Million US per year.
New AI technologies further support cost reduction initiatives
Recently, new AI tools have been deployed to collect data from plant machines, use that data to build performance models, and make predictions based on the model. Comparisons are made between the “to be” model and a database of “as is” real-time information. A machine learning engine in the AVEVA software provides early warning notification and diagnosis of equipment behavior anomalies days, weeks and even months prior to an actual failure occurring.
As a result, the system can provide early warning indications of equipment failure or deteriorated performance. This provides valuable insights to Engineering & Operations teams to support their decision-making process and to reduce the unexpectable production loss.
Working in tandem with the local Schneider Electric/AVEVA teams, refinery operators enjoy the benefits of a consultative relationship. The collective talent pool of local experts aligns with the refinery’s process control technology base, which makes it easier to overcome operational and production cost challenges.
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