How do you expand operations, migrate to a new control platform, and correct some emerging maintenance problems during a relatively short planned shutdown?
How do you get the job done despite limited documentation and the risk of introducing human error?
How do you do all that without interrupting the routine tasks already scheduled to take place at the same time?
For the Keadby Power Station along the River Trent at Scunthorpe in the United Kingdom, the answer to these questions is by modeling and simulating control systems ahead of time.
Keadby is a 720-MW power plant with 53 employees operated by SSE plc, a vertically integrated energy utility based in Perth, Scotland. As is happening at a growing number of facilities, Keadby engineers and technicians discovered that the current generation of modeling and simulation software is much easier to use and more powerful than older empirical packages of the past. Hence, many users are finding that this new breed of software is becoming indispensible for completing difficult projects.
Keadby engineers reduced the time needed for commissioning a new Foxboro I/A Series distributed control system (DSC) by using the SimSci-Esscor Dynamic Simulation Suite from Invensys Operations Management (iom.invensys.com) of Plano, Texas. The software provides both model-based plant simulation and dynamic emulation of the control system, which allowed the installation team to improve operations, validate the control scheme and train operators.
“Since the plant was already built, it was possible to build a high-fidelity process model based on existing plant drawings and historical data using dynamic-simulation software while the controls were being developed,” explains Janet Parker, P.E. product manager for control system simulations at Invensys. “Since the controls were still being built, function controls were built within the simulator.”
Migration two-step
This phase of the migration project unfolded in two steps. The first was the simultaneous development of the DCS software and an OTS (operator training simulator) process model—tasks that were undertaken by separate Invensys teams. The DCS team developed the migration tools and analyzed the code, breaking the application down into human-machine interface (HMI) components, interlock-protection logic, and sequences. The OTS team constructed the model after it marked up the plant’s piping and instrumentation diagrams to clarify the scope and topology of the process model.
Once the Invensys teams tested their designs, they joined forces and took the second step, which entailed combining their designs and ensuring that they worked together. The simulation model was connected to the DCS, a FoxView human-machine interface (HMI), and an InFusion configurator. “The actual I/A Series CP270 controllers were replaced with FSIM Plus simulation, and the gas turbine controls were replaced with a link to the GE Mark VIe virtual controller,” notes Parker. After loading the controls, the Invensys engineers built and verified the input/output (I/O) cross-references between them and the process model.
Because the simulator was able to mimic actual plant operations, Invensys and Keadby engineers could then use the model to simulate the plant and streamline the software migration. “It allowed us to catch a number of software integration issues before the system was accepted for installation on site,” says Hugh Ferguson, a control and instrumentation engineer at Keadby and the project manager for the DCS upgrade. “Simulation is also proving particularly useful at resolving hard-to-replicate problems, and was invaluable in leveraging the experience of plant operators during migration of the application software.”
Not only was the migration completed with minimal impact on routine plant operations, he adds, “It has been possible to retain much of the look and feel of the previous system, but at the same time make improvements to consistency, operability, and system configurability. Furthermore, we now have a number of new tools in our toolbox.”
Upgrades on autopilot
Developing and proving control strategies before implementation are not the only uses of controls modeling and simulation. ENI SpA, a Rome-based oil and gas company, is also using multivariable models in its advanced process control (APC) software to perform predictive control in some of its refineries. This software from Aspen Technology Inc. (www.aspentech.com) of Burlington, Mass. sits on top of Aspen Technology DMCplus controllers, which constitute the backbone of the plant's DCS
“APC collects sensory information about the plant from instruments and the DCS, and uses that information as inputs to the model, which generates a plan of future moves for the process along with predicting how the plant will behave,” explains Robert Golightly, APC industry marketing manager at AspenTech. “If you can predict what it’s going to do, you can change the outcome by manipulating the parameters that you can control.”
So, once every control cycle, the APC software determines optimal operating settings and tells the DCS the new settings that will move the plant continually toward optimality.
To boost the efficiency of the more than 50 APC controllers in its refineries, ENI tested AspenTech’s new adaptive modeling tools at its Livorno Refinery. The company was changing oil types frequently to capitalize on supply chain opportunities and needed an efficient way to update their APC models. Because the technology was able to reduce the maintenance time significantly, management has decided to deploy it at other plants.
Training, not a game
The need to train the next generation of operators is another reason that modeling and simulation technology has been enjoying a measure of popularity among some users. Demographics are such that the current generation of experienced operators is getting ready to retire. So far, the next generation of operators tends to lack the technical fundamentals in processes, but knows much more about computers.
“On top of that, the level of automation is just much higher in new and re-instrumented plants,” observes Martin Berutti, president of Mynah Technologies LLC (www.mynah.com) of Chesterfield, Mo., a maker of simulation software for process automation systems. For this reason, some companies are seeing virtual plants as the logical way to train the next generation.
Although the looming retirement of baby boomers has many companies incorporating control models and simulation into their succession planning, Toronto-based Barrick Gold Corp. had a more immediate need. Last year in the Dominican Republic, it built what it claims to be the largest plant in the world for extracting gold and copper from ores and concentrating the metals for further refining. Because the local population lacked the skills to operate the plant, management sent a team from the North American mainland to start and operate the plant until a local crew could be trained.
This training is beginning to occur now on the Mimic dynamic simulator from Mynah. The Barrick engineering staff had used Mimic in the development and startup phases to troubleshoot and optimize operations, which included such tasks as grinding, acid washing, leaching, curing, and cyanide handling. The expatriates also used the simulator to develop standard operating procedures, and are continuing to use it to identify and train locals who have the aptitude to be board operators.
What’s better today?
Berutti attributes success with new modeling and simulation technology to several enabling technologies. First, automation vendors have released simulation versions of their control platforms for development and training. Because these simulation packages eliminate the need to develop an emulated control system in the dynamic simulator, the cost and upkeep of development and training systems has become much more reasonable. “These simulation packages allow running the same control strategies, HMI, alarms and operator controls that would be in the control system in the plant in a virtual PC environment,” Berutti adds.
This advancement “saves users the trouble of converting their process models into control algorithms just because the algorithm needs to run on a different processing platform,” concurs Gary Kirckof, an application engineer at PC-based controls maker Beckhoff Automation LLC (www.beckhoff.com) in Burnsville, Minn. “Users can realize considerable savings in conversion time and eliminate conversion errors,” he says. Having both abilities on the same platform also captures real-time data in the format the model prefers, which streamlines improvements later.
According to Berutti, another enabling technology has been dynamic, real-time process simulators built for control system development and operator training. These dynamic simulators feature first principles unit operations models, implemented in intuitive, easy-to-use objects. “The time required to develop, tune and update the process models in the virtual plant is much less than for older simulation technology,” says Berutti. “This flexibility allows the operations manager to use this technology as an integral part of the strategy to optimize the plant and support operational excellence initiatives.”
“Without a doubt,” Beckhoff’s Kirckof adds, “the biggest technological advancement permitting the combining of modeling, simulation and control software is PC-based controls. This approach to automation makes it much easier to adapt standard software technologies from the IT world to industrial settings.” It also gives industrial users access to more features.
Not only do PC-based hardware and software enhance function, but they also make the technology more accessible, and foster collaboration. “Virtual machines and Web-based training move those tools onto engineer’s desktops, where they are used to teach best practices, facilitate loop tuning, assess alarm strategies, or analyze the root cause of an unplanned event,” says Parker at Invensys.
“Our control system simulation tools are evolving to more closely replicate all aspects of the control system,” adds Parker. “Not just the block algorithms, but peer-to-peer connections, control processor loading limits, and communication protocols.” That means investing in modeling and simulating your control systems is not only a proven approach, it’s one that will continue to be a good idea.
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