Turning Redundancy Into Profit by Optimising Existing Site Utility Systems Figure 1: Systematic Procedure for Site Utility System Optimisation
Plant data collection
Modelling
Optimisation with software modelling
Case Study
Multi-scenario optimisation with practical constraints
Implementation
By combining these different aspects of modelling, a complete utility system model can be generated. However, before optimisation, the model must be validated against actual site operations. If the model fails to achieve accurate representation of site operations, it would need to be returned to step 1 to collect more data and repeat the modelling step, until the model can eventually be satisfactorily validated.
Step 3 – Optimisation with Mathematical Programming Once the model is established and validated, it can then be applied for optimisation scenario development. For a utility system with a fixed configuration, optimisation is a non-linear problem (NLP). There can be different targets for optimisation, including minimising total site operating cost, minimising fuel cost, meeting certain power demands (to avoid power import or export), etc.
The setting of the optimisation target should always be based on the actual site requirement. If the objective relates to economics, the latest price information for fuels and other materials must be provided to the model. Operational variables, or adjustable operations, need to be decided. Generally speaking, operations such as power import and export, fuel supply, steam generation in each boiler and steam load in each stage of each steam turbine, etc., are adjustable operations.
However, in some plants, power and fuel are often affected by the market or legislation constraints and are not always free to adjust. Moreover, the operation of boilers and steam turbines is sometimes related and adjusting operation in one unit could affect another indirectly. Therefore, it might not be as straightforward as it appears to decide independent operational variables.
Step 4 – Multi-scenario Optimisation with Practical Constraints
Multiple optimum scenarios for various operating cases can be produced directly from software, and must be fully integrated with practical constraints before implementation. Practical issues such as operating stability and security, facility reliability and emergency concerns could all affect the optimimum scenarios. This step can also be considered as the validation step for optimisation results.
Step 5 – Implementation
To implement the optimisation results, all operations must be adjusted with great caution. It is recommended that operations
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A utility system optimisation study in a Sinopec refinery is presented here as a case study. This project was carried out in 2009 by Process Integration Ltd (PIL) and Sinopec.
With certain simplifications, the basic structure of the utility system was modelled in SITE-int, which is a utility system modelling and optimisation package developed by PIL. Figure 2 shows the configuration of the utility system.
Next, important facilities such as steam turbines and boilers were also modelled for their part-load performances. These models were derived from mathematical regression based on actual operating data. Figure 3 shows the difference between measured and calculated power generation for three steam turbines. The average relative errors are 1.33, 1.75 and 0.82% for three turbines, which indicates that the model predictions are in good agreement with real measurements.
When modelling the utility system, different operating scenarios were considered based on seasonal operational changes.
be adjusted towards the optimal targets in many steps with small step sizes; only when the previous step is confirmed to be secure and stable should the next step be made. This aims to make the adjusting process more stable and well controlled. As addressed before, process sites usually will not operate equipment at their boundary conditions, hence there could be certain differences between the expected boundary conditions and practically achievable ones. Exceeding practical operating limits could cause severe problems to the whole refining system.
Since 2007, Sinopec has been collaborating with PIL on operational optimisation for site utility systems.
By providing power tariff and market prices for relevant materials, SITE-int gives a series of optimisation solutions for different operating conditions. These optimisation solutions are then integrated with practical plant constraints to produce final optimisation scenarios for implementations.
The on-site implementation was carried out within half a year after the project was initiated. After implementation, an operating cost reduction of 5.3% was immediately observed, which is equivalent to about US$7.5 million per year. It must be emphasised again that this is a net operating cost saving and no capital investment was made.
Furthermore, the optimisation of this utility system also helped to identify bottlenecks in the current steam distribution system. As a result, a simple medium pressure (MP) pipeline modification was identified to improve the current MP distribution. After this modification is implemented, the total operating cost could be reduced by 10.0% from the base case level.
HYDROCARBON WORLD – VOLUME 6 ISSUE 1
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