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Oct-2009

Real-time refinery energy management

An online model installed at Repsol Cartagena refinery enables optimal balance between internal energy production and demand

Diego Ruiz, Carlos Ruiz and Fernán Serralunga
Soteica
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Article Summary
Repsol Cartagena was the first oil refinery to be built on the Iberian Peninsula. It has an annual crude distillation capacity of 5.5 million tonnes, with two main areas of production: fuels; and lube oils, asphalts and paraffinic and aromatic oils. Repsol Cartagena is currently involved in an ambitious expansion project, whereby 22 new units will be built, increasing its refining capacity to an annual 11 million tonnes.

An online model has been installed to monitor and optimise the energy system, using technology that has been applied successfully by Repsol in similar projects.1-4 A detailed model of the steam, fuels, electricity, boiler feed water and condensate systems has been assembled, including all interactions between these systems, as well as real plant constraints and degrees of freedom of operation. The model is scheduled to perform automatic executions to optimise the entire system, and it is continually populated with validated live data obtained from the process.

A calculation of equipment efficiencies is carried out as part of the performance-monitoring activity of the model. Other monitoring aspects include continuous auditing of the energy system so that data can be relied on for evaluating the value of energy production and usage to reduce or eliminate waste.

Recommendations supplied by the model can be taken into account by operations on a daily basis. The same model used for online, real-time optimisation can also be used in standalone mode, populated either with current or historical data, to perform case studies for planning or to evaluate alternatives for better operation of the energy system. As a result of the project, information relating to the refinery’s energy system has been organised into one model and a single environment, to which everyone has access.

Furthermore, the project has enabled an understanding of all of the decision variables and their associated constraints, which are sometimes hidden or ignored. Additionally, the centralisation of responsibility for optimal operation of the energy system has been established. A proactive support programme with the aim of ensuring that the benefits of the project are sustained and that the health of the model is kept in check over time is also under way.

Refinery energy system

The energy system is based around five steam pressure levels, with four fired boilers producing high-pressure steam, a cogeneration plant producing steam and electricity, and a set of steam turbo-generators producing electricity. Different economic trade-offs provide many challenges to site-wide operation of the energy system at minimum cost, such as the trade-offs among electrical power, steam and fuels networks. In addition, the Kyoto protocol has introduced new motivation to calculate and reduce CO2 emissions.

Figure 1 shows a main view of the Visual MESA model graphical user interface. By double-clicking on the respective icons of each plant area, operators can navigate through the model and inspect the details of each piece of equipment, sensor, header 
or line.

Project stages
The main stages of the project are:
•  Data collection and control system review
•  Software installation
•  Model building and configuration for optimisation
•  Midpoint review and user training
•  Burn-in period.

Data collection consists basically of preparing system diagrams, real-time database tags and equipment information, as well as price-related information.

The control system review’s main goals are to develop a good understanding of how Visual MESA’s optimisation handles and process constraints are related throughout the site control system, and to identify any new control strategies or changes to existing strategies that are needed to implement the optimisation. This is to ensure that suggestions for optimisation can be properly implemented using the site’s operating procedures, control strategies and control structure.

Software installation is carried out on a server accessing the real-time database (plant information system) via a standard OPC DA/HDA interface. Software installation on PC clients is also carried out to enable client-server access to the model and to work with the model in standalone mode.

Model building and optimisation configuration involves a detailed model of steam, fuels, electricity, boiler feed water and condensate systems, including all of the interactions between these systems, real plant constraints and degrees of freedom of operation.

Figure 2 shows a representation of the cogeneration plant. Such a model is scheduled to perform automatic executions of the optimisation of the entire system and is continually populated with validated live plant data. In this implementation, the main optimisation handles of the energy system are:
•  Fuels to fired boilers, such as fuel oil and fuel gas
•  Reposition fuel-to-fuel gas network, such as LPG and natural gas
•  Fuel gas flaring
•  Fuels to post-combustion (after-burning) at the cogeneration unit
•  Steam generation at fired boilers
•  Steam letdown
•  Steam vents
•  Steam turbo-generator manage-ment and corresponding electricity generation
•  Heat recovery steam generator in the cogeneration unit
•  Gas turbine load in cogeneration and corresponding electricity generation
•  Steam injection to the gas turbine
•  Pump swaps (steam turbine and electrical motor drives options).
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