Modelling the future of ethylene

Louise Smyth

Optimising assets from design through production can result in a quick payback of capital investment. Luc Chantepy reports

Predicting the future of the petrochemicals industry is challenging in an uncertain marketplace. Yet, many chemical leaders are adopting a model-based culture to predict plant behaviour and manage the design-to-production lifecycle to reap enormous rewards.

Olefins products are manufactured in highly energy intensive processes. In particular, ethylene plants are inherently complex, flexible processing systems that have the ability to adjust raw material availability in response to market demand. Advanced technologies along with best practice methodologies used in olefins plants today can dramatically improve plant performance and result in best in class production, consistent product quality and swift return on investment. For Middle East manufacturers, optimising assets plant-wide will reinforce the region’s standing as a global leader in the petrochemicals industry.

The capacity for change

Ethylene is one of the most versatile and widely used petrochemicals in the world today. It is widely used in the production of goods, such as plastics or polymers, solvents, fibres for apparel, cosmetics, detergents, paints, packaging and many other products.

According to the Gulf Petrochemicals and Chemicals Association (Dubai), Saudi Arabia accounts for 64% of the Gulf Cooperation Council states’ ethylene capacity of 24.1 million m.t./year, Saudi Arabia’s chemical producers are assessing the impact of the energy, feedstock and utility price hikes announced by the Saudi government in its state budget on 29th December 2015. The increases include 133% for ethane, 67% for methane, 40% for electricity and water, and 50% for gasoline. The government has also reduced the discount on LPG and naphtha feedstock from 28% to 20% and will track to the respective price in Japan. Sabic, by far the largest producer of ethylene in Saudi Arabia, estimates that the price hikes will increase its annualised costs by about 5% before minority interests.

The petrochemicals game has clearly changed for the Middle East. Optimisation is no longer an option; it is now a commercial necessity. Having a comprehensive overview of strategic plant operations provides decision-makers with the opportunity to respond quickly to changes in product demand and feedstock availability. Adopting a model-based approach delivers a design-to-plan-to execution methodology that allows companies to quickly scale their operations in accordance with the dynamics of business objectives and ensures production aligns to plan.

Energy, economics and efficiency form the bond to operational excellence. Using a full-lifecycle modelling environment, engineers can design plants through integrated processes and rigorous and scalable designs to predict physical plant behaviours like pressure, fluid flow and operating constraints. This approach can also be used for pressure safety-valve sizing and heat exchanger performance analysis.

The model for plant operations

The separation of ethylene from ethane is an expensive process both in capital and operating costs. The increasing production trend has been to build larger plant units and consequently the ethylene splitter (C2 splitter) has also increased in size. In the olefin business reducing energy consumption is, therefore, an important incentive for companies. Advanced technology can help Middle East companies differentiate themselves to optimise process design, plant design and manufacturing production.

The design of an ethylene splitter is determined by several factors, including process requirements, economics and safety. Through robust models integrated with plant data, engineers can gain greater visibility into operational constraints. The process model drives value in plant operations and by being detailed enough can robustly predict real plant behaviour over an expected range of conditions linked to process data. The data itself is conditioned to smooth out measurement errors with an execution environment to run the model whether on-demand, scheduled or event-driven.

The C2 Splitter separates ethylene as a high purity overhead product from ethane, which is combined with propane and recycled for cracking. The C2 splitter (ethylene and ethane) separation often requires large distillation columns (splitters), including a heat exchanger and compressor, and is a critical system in all ethylene plants, although it can be difficult to operate. This is because there is a limit on full system capability due to the lack of visibility on operating constraints. Also, longer plant disruptions can occur due to manual troubleshooting. Building a simulation to model the C2 splitter section using an advanced process simulation tool and matching variables with actual plant data means that engineers can predict the feed composition to the C2 splitter, tray efficiency and compressor efficiency. The use of a powerful rate-based distillation column modelling tools ensures more accurate simulations and maximises production over a wider range of operating conditions whilst calculating the flooding factor and compressor loading based on actual plant data.

Monitoring these key inferential variables gives an operator valuable insight into equipment performance and areas of concern. This decreases the likelihood of unplanned downtime to save the plant production time and money. Using a rigorous process model optimises the unit operation. Basing the C2 splitter process decisions around a detailed process simulation model enables better asset utilisation and provides multiple evaluation options to quickly return to normal operation. Therefore, operating the column and auxiliary equipment based on general rough principles is inaccurate, whereas a model-based approach allows engineers and operators to make more accurate and better decisions and explore multiple operating scenarios to adjust plant operations and optimise performance where necessary.

Using AspenTech’s integrated aspenONE suite of tools, the process engineer can build a model of the unit and validate it against plant data from the production engineer and the plant data historian. Building an Aspen Simulation Workbook (ASW) interface to the plant model and linking it with plant data tags in Excel, the chemical production engineer can use the model to identify alternate operating conditions. The next step is to reconcile the model as the model runs online. Data is then saved in the data historian, so the production engineer can see immediately how the model changes over time. After using Real-Time Optimisation (RTO) to deploy the model 24/7, the model calibrates itself daily and provides optimised set points to the process control system. The plant is then able to reach and maintain capacities higher than ever previously seen and frees up significant time for the unit engineer. Using Aspen Custom Modeler makes it quick and easy to create unique process and equipment simulations that can be customised with accuracy and ease. The software helps to build custom forms and plots for customised models, so it is easy to lay out data in a way that makes sense to the engineer.

Using robust models, chemical companies can:

* Predict plant behaviour based upon reliable data

* Increase yield of ethylene or olefins per pound of feed

* Reduce energy consumption per pound of product

* Ensure safe, consistent and efficient operations

* Achieve smoother operation with continuous coordination of plant-wide changes

* Automatically detect, control and correct operating conditions quickly that may lead to costly shutdowns

* Produce consistent quality products to meet customer demands

Improve overall plant profitability

Transforming the future

To maximise ethylene production whilst minimising operating costs requires a constant focus on efficiency measures. Improvements in asset efficiencies can result in up to 15% savings in energy costs through the adoption of integrated state-of-the-art technologies. A model-based approach allows engineers to conduct a gap analysis between current performance and plan to identify the bottlenecks and also understand where issues are impacting business performance.

Best practice transforms production. Optimising the full design to production lifecycle enables olefin plants to maximise profitability and builds the foundation for future generations of engineers to lead the Middle East’s competitive advantage in the petrochemical industry.

Luc Chantepy is Regional Sales Vice President, MENA, AspenTech.

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