Consider Dynamic Simulation for Steam System Design

Models can provide crucial insights for dealing with upsets and transient conditions.

By Ian Willetts, Abhilash Nair and Charles Rewoldt, Invensys Operations Management

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While dynamic simulation has become more prevalent due to software and processor advancements, it involves far more than simply entering numbers into a form. Experience has shown that certain considerations and pre-planning strategies significantly contribute to the success of steam-system simulation projects. Here are some tips:

Make conservative assumptions. This is one of the most critical aspects of design. It's inevitable that the model won't capture every possible nuance or feature of the process, so the model's response won't fully replicate actual system response. However, if the model is designed to the highest possible rigor and all assumptions and modeling approaches err on the side of safety and over-design, you can have confidence in the results.

For example, Gandhi et al. [1] discuss the modeling of steam systems (specifically boilers following a trip) and the phenomenon of self-boiling in which residual heat in the boiler continues to generate steam long after fuel is cut off. While it might be possible to rigorously model the boiler to the level of detail to capture the self-boiling phenomenon, it may be more prudent instead to take a more conservative approach — assuming steam generation stops shortly after fuel is cut off. A control system that can handle a rapid loss of steam certainly can deal with the situation where the steam supply decays more slowly.

On the other side of the coin is modeling the ramp-up of boilers when more steam is needed. The boiler manufacturer will supply the design maximum rate of change of steam production up to the maximum continuous rating. The vendor may give a 20% per minute ramp but what if it's actually only 10% or 15% due to unforeseen issues. The dynamic simulation platform provides a perfect environment to run multiple cases to test the sensitivity to key parameters.

Employ strict quality-assurance procedures. The accuracy of simulation results depends upon many factors, including the modeling approach, assumptions, data mining and data input. Experts follow strict procedures when executing a project to ensure the model is built to the highest possible standard and model inputs are correct. It's crucial to establish quality-assurance procedures that will certain results obtained are meaningful and trustworthy.

The main focus should be on checking the data input into the model. Discuss assumptions made and confirm they're conservative enough that the results won't compromise any objectives of the study. For instance, using a larger steam header volume than actual in the model could yield a slower response than actual; this could lead to inaccurate results and conclusions for the design of pressure controls.

In addition, have experts from operations review scenarios that are tested on the model to ensure the worst case is considered.

Such a quality-assurance process guarantees the model developed includes all the right inputs and assumptions, making the results more reliable and credible.

With a high-quality steam system model, engineering and operating companies can begin to reap the benefits of dynamic simulation in different aspects and phases of the design process.

Validate steam-network piping design. The piping network often is designed for the flows and pressure profile at steady-state conditions. In the event of process upsets and the transients that may follow, these parameters undergo rapid changes that normal hydraulic analysis can't discern.

Some pipes within acceptable limits at normal conditions could exceed design limits during transients and become potential bottlenecks to the steady operation or startup of the facility. Identifying such bottlenecks during startup, commissioning or after an incident could lead to expensive field changes that impact the project schedule for new plants or operation of an existing facility.

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