Network Architecture Considerations in Ovation Control Systems

Emerson’s Craig McDaniel provided an overview on the Ovation control system network architecture at the 2017 Ovation Users Group conference. He provided a basic overview of Ovation’s network architecture showing standard configurations, connectivity, redundancy, IP addressing schemes, port assignments, network hardware, and connections to third party equipment will be provided in this session. He also discussed the traffic flow through Ovation and provided a review of some common issues encountered on Ovation networks and how to avoid them.

Network components in an Ovation system include switches, layer 3 switches and routers. Non-Ovation components include printers, time servers and separated from Ovation network are components such as PLCs and human machine interfaces (HMIs).

In a network design, you need to consider the Ovation networks, field PLC networks, plant local area networks, etc. IP addresses must be suitable for the network they are on or clearly defined static route or default gateway paths to other networks. IP addresses cannot overlap between different networks. Continue Reading

Reducing Control System Hardware Footprint

Emerson’s Ben Skal presented on reducing the Ovation distributed control system hardware footprint at the 2017 Ovation Users Group conference. Virtualization technology is at the heart of this hardware footprint reduction and having less workstation and server hardware to maintain. Ben’s presentation focused on:

  • What is virtualization & how it works
  • Appropriate uses of virtual machines (VMs)
  • Benefits of VM environments in increased redundancy & reliability, reduced footprint and recovery from equipment failures
  • Requirements to move from traditional workstations & server to VM

Ben opened describing virtualization which separates the operating system from the physical hardware. Multiple virtual machines can run on physical services. Server host clusters have a management console that oversees the cluster of servers on which the VMs run. Continue Reading

Take Charge of Partial Discharge to Protect Plant Assets

Emerson's Jonathan MurrayEmerson’s Jonathan Murray discussed partial discharge solutions at the 2017 Ovation Users Group conference. Unplanned electrical asset failures can halt production and amount to millions of dollars of associated costs. The IEEE and NFPA organizations identify Partial Discharge (PD), a breakdown of the assets insulation, as a leading cause of failure. Manufacturers are looking for ways of transitioning away from traditional periodic testing and integrating continuous PD monitoring systems into the Ovation system and achieving predictive maintenance capabilities.

Jonathan opened with a story of a failure of a single switchgear for DeltaV airlines costing $150 million in economic loss. Typical methods of maintaining assets are reactive, preventive and predictive. Moving toward predictive maintenance often means identifying and solving potential failures before they lead to loss. Continue Reading

Model Predictive Control in Power Generation

Emerson's Ranjit RaoModel predictive control in power generation was the subject of a 2017 Ovation Users Group presentation by Emerson’s Ranjit Rao. Rajit opened comparing classical control with model-based control. In classical control, a proportional-derivative-integral loop is used with feedback. There is a setpoint, the actual process variable and the error or difference between the process variable and setpoint. Based on the dynamics of the process and load disturbances, the amount of proportional, derivative and integral gain is set to have to have the loop control the process effectively.

The PID approximates the process and does not handle higher order responses well. Model-based control is ideal for processes with long dead-times and higher order responses. A built-in optimizer provides the ability to focus on an outcome such as profitability. The model-based controllers can model dynamic disturbances. In the Ovation system, these model predictive control (MPC) algorithms run in the Ovation controller. Continue Reading

Simulation for Training and Engineering Applications

At the 2017 Ovation Users Group conference, Emerson’s Bob Kerestes and Sheldon Willis gave an update embedded simulation in the Ovation system. Sheldon opened the presentation describing types of uses for simulators for training and engineering. For training simulators, simulations can range from simple tie-back models to high-fidelity models which simulate the dynamics of the running process.

For high-fidelity simulation, engineers can use the model for full process design validation, controls validation, root analysis studies, optimization and more. In the Ovation system the simulators run in virtual controllers. As simulators move from simple tie-back models to high-fidelity models, formulas based on first principles are added to bring the model closer to how the actual process performs.

For training simulators, instructor stations are available to create scenarios to teach and test operator performance for various plant abnormal conditions. It has some controls to play, pause, select speed and take snapshots at different points in the simulation.

Simulators are being used more and more to test the DCS control strategy design during factory acceptance testing to make the configuration more robust before the commissioning process. A new area for simulator use is in microgrids. Sheldon described integrated simulators that help keep the simulator in sync with the running control system. Configuration changes can be targeted to the simulator and to the live control system.

Bob came up and described distributed generation (DG) and the role of simulation. DG spreads out the generation capability of the grid versus the traditional approach of producing electrical power centrally and distributing outward. DG can increase reliability, replace aged and deteriorated parts of the grid and mostly uses renewable sources of energy. DG is an enhancement to the grid to augment and make centralized power generation more reliable and resilient.

Microgrids are unique in that they may or may not have a generator, may or may not have renewable energy, may or may not be used to supply power back to the grid and can be very costly. Distributed Energy Resource Management System (DERMS) manages the economic dispatch problem as it applies to distributed generation or microgrids. DERMS require very accurate modeling of the electric power distribution system into which it is integrated. Much more research is underway to better understand how to model transient conditions and newer technologies such as flow batteries as part of a microgrid and distributed generation on the main grid.

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