Leveraging process simulation throughout the plant lifecycle
Digital transformation is rapidly influencing the hydrocarbon processing industry. Up to 60% of refining operations are spending more on digital technologies in 2018 and 67% believe a lack of digital solutions would reduce their competitive edge, according to a research report by Accenture. While new software and hardware are being developed to address this demand, established strategies also stand to play an important role in the digital revolution. The change will be in how these tools, such as operator training simulators, are implemented, deployed, and used to achieve optimal plant performance.
Process simulation has been a key tool in the hydrocarbon industry for decades. Historically, simulators have been used in two key phases of the plant lifecycle. During the initial design phase, steady-state models enable engineers to design and size key equipment and ensure that heat and material balances are satisfied.
Much later in the lifecycle, when the plant is online, the operations staff uses dynamic operator training simulators (OTS) to train new personnel and refresh the skills of experienced workers. These activities occur in phase 3 and only part of phase 5 of the plant lifecycle shown in Figure 1. This leaves many phases of engineering and operations without simulator interaction.
Management can use high-fidelity simulation throughout the plant lifecycle to yield the greatest return on investment by treating the simulator as a digital copy of the physical plant not limited to narrow use-cases. Advancements in computational technology have filled the gap between design and operations so a full plant model of the highest fidelity can be used simultaneously for engineering studies and operator training.
In bridging this gap, a much larger percentage of the plant lifecycle comes into scope and unlocks the potential of the process simulator as a tool that covers the plant from design to operation.
Static and dynamic simulation models
Static process simulation software is heavily relied upon during the front-end engineering and design (FEED) phase of brownfield and greenfield projects. Comprehensive plant models provide engineers with a complete view of heat and material balances for limiting design cases and other operating conditions. Additionally, simulation software is used to perform feasibility studies, assess different process configurations, and identify risks. Engineers can leverage this information to ensure designs are safe, meet environmental regulations, and maximize the operational and business performance of the asset (see Figure 1).
Generally, static simulation is a tool used most often during this stage of the plant lifecycle. However, dynamic models can be useful for feasibility studies. Mature simulation software allows the end user to seamlessly migrate from a static to a dynamic model. In this case, services required to build the initial model are performed upfront, during the FEED phase. This means that the benefits of the simulator can be realized in the downstream lifecycle phases with minimal services investment.
Using simulation for plant design and process automation system validation
While static models ensure operation at defined steady-state conditions, a dynamic simulator allows engineers to validate that the plant can successfully operate at every point from black start to full capacity. Once the plant design has been finalized, engineers can use the simulator to ensure the design is fit for purpose and all equipment can meet the demands of the startup procedures and operational sequences.
By adhering to process and mechanical datasheets during the model development phase, end users can be confident all equipment in the simulation matches that of its physical counterpart in the field. With this knowledge, engineers can scrutinize every piece of equipment in plant from individual piping segments to complex, multi-pass heat exchangers. Additionally, with the ability to pre-program model scenarios, engineers can continuously run the plant through defined operational procedures and examine the process responses using incremental changes in the plant design.
While the benefits of examining the plant process with a simulator are immense, much of the value is realized upon integration with the control system. After the design and testing the controls, the simulator can provide an additional layer of process automation insight. Most modern control systems have the ability to simulate values so rudimentary testing can be performed on control loops. However, a high-fidelity simulator provides realistic process responses that are almost impossible to replicate with empirical correlations.
Sophisticated modeling software is based on first principles, thus providing meaningful insight into countless “what if” scenarios. The controls will be exposed to more advanced testing that is more closely aligned with the actual plant response. This allows engineers to identify potential problems early in the design phase before they become expensive and time-consuming to correct.
The safety system’s validation and design is a vital part in the commissioning of any new facility. All production companies aim to minimize the number of safety incidents that occur onsite. However, the reality is that safety systems are exercised so infrequently it may take years for a flawed design or procedure to be recognized.
A simulator provides real-time process responses to allow users to scrutinize and dissect safety schemes during abnormal operating conditions. Using defined operating scenarios, users can run the plant through various upset conditions such as: compressor surge, depressurization/flaring events, and total plant shutdown. This allows for an iterative process wherein safety systems are constantly tested and upgraded to ensure all possible outcomes are accounted for. Once changes have been proposed, the hazard and operability (HAZOP) team can use the simulator to support studies and investigate the integrity of planned designs.
Plant commissioning and startup in a virtual environment
While a simulator will not aid in constructing a new facility, the engineering staff can continue to use the simulator during this time to ensure commissioning and startup (CSU) is as smooth as possible. Many pieces of the plant, from process equipment to controls and alarming, are being exercised to their full functionality for the first time. Consequently, many unforeseen issues are uncovered during this time that require immediate attention to avoid lengthy and expensive delays.
However, the issues faced during the CSU can be addressed much earlier by performing the CSU in a virtual environment. A virtual commissioning and startup (vCSU) that involves all key stakeholders will expose many flaws and allow them to be rectified in a timely and controlled manner. For example, vCSU provides engineers an opportunity to test the detailed startup procedure, fully exercise the distributed control system (DCS) human-machine interface (HMI), validate alarm suppression, and tune vital control loops. Many of these activities are often crowded into an already tight startup schedule leaving little room for error. This second layer of validation ensures the assets handed off to operations have been validated and tested in an environment that mirrors real life.
Plant operation and maintenance
The traditional role of custom-built plant simulators is in operator training. Many plants implement programs that require their employees to follow extensive, simulator-based training regiments to maintain a certain level of training. The best practice in this area is tracking and recording the performance of board operators using training scenarios to evaluate key performance indicators (KPIs) against plant standards. Additionally, management can track their plant performance and see the efficacy of their hands-on training program in real-time (see Figure 2).
Recent improvements to augmented reality (AR) and virtual reality (VR) technologies have extended simulator-based training to field operators. Workers can practice non-routine tasks in the safety of a virtualized or mixed reality environment where instructors can guide and teach along the way. This hands-on training approach leads to a safer and more competent workforce.
For plants at a more mature stage of the lifecycle, a process simulator can benefit not only operations, but the engineering department as well. In addition to serving as a platform for operator training, this is a time for the simulator to shine as a predictive analytical tool.
Assuming management supports an evergreen approach towards simulator maintenance, the model should continue to provide an accurate representation of plant dynamics and responses, making it an appealing platform to propose and test process upgrades. Some of the activities may include identifying facility bottlenecks, enhancing operating procedures, and testing plant performance during novel grade transitions or other transient scenarios.
A change that may require weeks to implement in the field can be accomplished almost instantly, reducing the time between an idea’s genesis and it being tested and validated. This accelerated cycle allows for more upgrades to be proposed and refined prior to implementation in the field. Additionally, updated DCS, programmable logic controller (PLC) and safety instrumented system (SIS) control logic may be loaded into the simulator system to test the response of proposed upgrades.
Virtualization and cloud-based project execution
Due to the complexity and extensive breadth of simulation systems, they have historically required a large software installation coupled with a sizeable hardware footprint. The workload associated with maintaining such a system can cause simulators to fall out of date and thus, lose their one-to-one match with the physical plant. When this happens, the simulator loses credibility in all the aforementioned activities.
To lower the burden of maintenance, simulation suppliers have trended towards virtualization. This means the OTS network runs on virtual machines, which are hosted on either local or off-premise servers. This approach eases system maintenance by allowing users to easily backup and quickly restore systems in the event of hardware or software failure. Virtualization also reduces the hardware footprint as entire networks can be hosted on one server.
The next logical step in this trend is to move the host servers off-premise and into a cloud environment. There is growing interest in using public and private cloud infrastructure as a platform for implementing simulation. In this scenario, customers would be able to access their plant model from anywhere in the world, with only limited hardware required to do so. Additionally, suppliers would be able to easily provide remote support and be more efficient overall.
As industrial digitization continues to revolutionize the hydrocarbon processing industry, leveraging new and existing technologies to advance plant performance is critical. Although process simulation is not a novel technology, progress in how simulators are implemented and deployed can unlock new benefits to support a plant throughout its lifecycle.
By viewing a process simulator as the digital clone to the physical plant, users can explore new avenues to leverage this technology and support all stages of the plant lifecycle.
KEYWORDS: Operation training simulators (OTS), augmented reality (AR)
- Enhancing personnel and plant operator training with simulators
- Extending the plant lifecycle with training simulation environments
- Supporting all the stages in the plant lifecycle with simulation.
How can you use training simulation software to improve your plant’s lifecycle?