Apr-2014

Real time online energy management

Creating a model of a refinery energy system validated with real time data increased energy efficiency and reduced total energy costs

MOHAMMAD ERSHAID, KNPC Mina Al-Ahmadi Refinery
CARLOS RUIZ, DIEGO RUIZ and NICOLÁS VISUARA, Soteica Visual MESA
DHANASEKAR PERIYASAMI, EBS

Article Summary

It is Kuwait Petroleum Company’s (KPC) and its subsidiaries’ policy to ensure that all energy should be managed in accordance with best engineering environmental practices and within regulatory compliance at all times.^₁ All operations must be committed to institute an energy efficiency programme and minimise emissions of pollutants including global warming gases. As part of the activities to follow those premises, energy management cells (EMC) have been formed at each of the Kuwait National Petroleum Company (KNPC) refineries: Mina Al-Ahmadi (MAA), Shuaiba (SHU) and Mina Abdulla (MAB). Such cells implemented an energy management programme based on best international practices and on real time, online optimisation.

This article describes the tasks performed to develop and implement a real time, online model for energy cost minimisation and energy management at KNPC’s MAA refinery.

After a description of the main project implementation tasks, the Real Time Energy Management System’s (RTEMS) functionalities are described and the optimisation implementation procedures are commented on. Finally, several obtained results are presented.

Project implementation tasks
The main stages of the project have been:
• Define and installation stage
• Model building and configuration stage
• Training stage
• Site acceptance stage
• Commissioning stage.

Define and installation stage
The first stage of the project includes the tasks of data collection, control system review, software installation and detailed definition of the model scope. Data collection consists basically of gathering system diagrams, real time database tags and equipment information, plus price related information.

The control system review’s main goals are: to develop a good understanding of how model optimisation handles and process constraints are related through the site control system; and to identify any new control strategies or changes to existing strategies that are needed to implement the optimisation. As a result of such a review, there is an alignment of the model with the real plant, making sure that suggestions for optimisation can be properly implemented using the site’s operating procedures, control strategies and control structure.

Software installation is done on a computer server, accessing the historian data via a standard OPC DA/HDA interface. Software installation at PC clients is also designed for client server access to the model and to facilitate working with the model in standalone mode.
During this stage, a document is prepared and approved with a detailed scope of the model to be implemented.

Model building and configuration stage
A detailed model of the steam, fuels, electricity, emissions, boiler feed water and condensate systems has been built, including all interactions among these systems, real plant constraints and degrees of freedom of their operation. Other utility systems have also been modelled for monitoring purposes such as air, nitrogen, flaring system, cooling water, sea water and hydrogen networks.

Such a model is scheduled to perform automatic executions for the optimisation of the entire system and is continually populated with validated, live plant data. Figure 1 shows a screenshot general view of MAA refinery’s RTEMS model graphical user interface.

The main optimisation handles of the energy system are:
• Steam production at boilers
• Fuel gas/fuel oil to the fired boilers
• Pump swaps (steam turbines/ electrical motors switches)
    ν    81 T-M possible switches above 100 HP; the steam turbines take and discharge steam at different pressure levels
    ν    17 T-M possible switches below 100 HP; the steam turbines work from UMP/MP to LP steam pressure levels
• Condensing turbines
• Extraction-condensing turbines, UHP (ultra high pressure) to UMP (ultra medium pressure) and/or condensate
• Electricity importation
• Natural gas make-up to the fuel gas system
• Steam letdown, excess condensing and vents
•  Deaerator water make-up preheating with low pressure (LP) steam.

The main constraints to be met are:
• Process energy demand
• Burners capacities
• Emissions limits (NOx/SO2)
• Contractual constraints (for instance, natural gas and electricity supply contracts)
• Maximum and minimum operating limits for boilers.

Overall optimisation problem figures are:
• 180 optimisation variables
• 44 continuous variables
• 136 discrete variables
• 64 constraints.

Recommendations given by the model are taken into account by operations on a daily basis. The same model used for the online, real time optimisation is also 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.

Training stage
A mid-point review is carried out to review the model and optimisation with users; at this time, the users’ training takes place. A burn-in period corresponds to a fine tuning of the model, operating report and optimisation based on operations feedback in order to achieve day-to-day use of the application.