Abstract: A real-time control system includes a faulty variable identification technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The faulty variable identification technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.

Abstract: A process characteristic parameter determination system uses a process model and a tuning module to accurately determine a value for a process characteristic parameter within a plant without measuring the process characteristic parameter directly, and may operate on-line or while the process is running to automatically determine a correct value of the process characteristic parameter at any time during on-going operation of the process. The process characteristic parameter value, which may be a heat transfer coefficient value for a heat exchanger, can then be used to enable the determination of a more accurate simulation result and/or to make other on-line process decisions, such as process control decisions, process operational mode decisions, process maintenance decisions such as implementing a soot blowing operation, etc.

Abstract: A real-time control system includes a simulation system to implement a predictive, look-ahead function that provides an operator with information that enables a higher level of situational awareness of the expected transitional events of future steps within the control program or sequence logic. The simulation system enables future steps and transitions to be monitored before they actually occur, which enables the operator to recognize and potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a sequence stall of the control program.

Abstract: Testable, redundant pneumatic control assemblies and related systems and methods are described herein. An example pneumatic control assembly described herein includes first, second, and third parallel supply channels between a compressed air supply and valve header, first, second, and third parallel vent channels between a vent and the valve header, and first, second, third, fourth, fifth, and sixth logic valves. The first and sixth logic valves are disposed in the first parallel supply channel and the first parallel vent channel, the second and third logic valves are disposed in the second parallel supply channel and second parallel vent channel, and the fourth and fifth logic valves are disposed in the third parallel supply channel and third parallel vent channel. The pneumatic control assembly also includes a first, second, and third solenoid valves to control certain ones of the logic valves.

Abstract: A real-time control system includes a fault detection training technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The fault detection training technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.

Abstract: Methods and apparatus to optimize ramp rates in combined cycle power plants are disclosed herein. An example method disclosed herein includes predicting a first setpoint for a gas turbine in a combined cycle power plant over a prediction horizon and predicting a second setpoint for a steam generator over the prediction horizon. The example method includes identifying a first steam property of steam generated by the steam generator in the combined cycle power plant based on the second setpoint. The example method includes comparing the first steam property to a second steam property of steam associated with a steam turbine in the combined cycle power plant and dynamically adjusting at least one of the first setpoint or the second setpoint based on the comparison.

Abstract: A U-I/O card improves on traditional I/O cards by enabling configuration of each I/O channel on each U-I/O card to operate according to a desired signal type (e.g., AI, AO, DI, or DO). Thus, each I/O channel of a given U-I/O card may be coupled to any type of field device. The U-I/O card thus simplifies I/O network design, wiring, configuration, commissioning, redesign, and rewiring. The U-I/O card also improves space efficiency in marshalling cabinets and eliminates inefficient use of I/O cards relative to traditional I/O cards.

Abstract: A process characteristic parameter determination system uses a process model and a tuning module to accurately determine a value for a process characteristic parameter within a plant without measuring the process characteristic parameter directly, and may operate on-line or while the process is running to automatically determine a correct value of the process characteristic parameter at any time during on-going operation of the process. The process characteristic parameter value, which may be a heat transfer coefficient value for a heat exchanger, can then be used to enable the determination of a more accurate simulation result and/or to make other on-line process decisions, such as process control decisions, process operational mode decisions, process maintenance decisions such as implementing a soot blowing operation, etc.

Abstract: The described methods and systems enable iterative plant design. These methods and systems may be utilized to test multiple P&ID designs and control strategies before a plant is constructed, enabling engineers to test physical layouts and control strategies for the particular unit, facilitating optimal design of the plant and control scheme for controlling the process. The described methods and system thus facilitate optimal design of optimal physical layouts and control strategies.

Abstract: Methods and apparatus to optimize ramp rates in combined cycle power plants are disclosed herein. An example method disclosed herein includes predicting a first setpoint for a gas turbine in a combined cycle power plant over a prediction horizon and predicting a second setpoint for a steam generator over the prediction horizon. The example method includes identifying a first steam property of steam generated by the steam generator in the combined cycle power plant based on the second setpoint. The example method includes comparing the first steam property to a second steam property of steam associated with a steam turbine in the combined cycle power plant and dynamically adjusting at least one of the first setpoint or the second setpoint based on the comparison.

Abstract: Systems and approaches for error detection detect discrepancies in industrial equipment by comparing a particular asset to similar industrial assets running in parallel to the particular asset. An error detection unit detects a difference between an estimated and actual output of the asset. Based on the magnitude of the difference, the error detection unit determines whether an input value of the particular asset is similar to input values of the plurality of industrial assets and whether an output value of the particular asset is similar to output values of the plurality of industrial assets. If the input value of the particular asset is similar to the input values of the plurality of industrial assets and the output value of the particular asset is not similar to the output values of the plurality of industrial assets, then the error detection system sets an alarm.

Abstract: A system and method for operating a remote plant simulation system is disclosed. The system and method uses a light application at the plant to collect relevant data and communicate it to a remote plant simulation. The remote plant simulation uses the relevant data, including data from the actual process, to create a process simulation and communicate the display data to the light application operating at the plant where it is displayed to a user. The remote system offers the advantage of offering decreased cost and improved simulation as the equipment cost, operator cost and set up cost is shared by a plurality of users. Further, the data may be stored remotely and subject to data analytics which may identify additional areas for efficiency in the plant.

Abstract: A control system uses a feedforward neural network model to perform control of a steam turbine power system in sliding pressure mode in a more efficient and accurate manner than a control scheme that uses only a multivariate linear regression model or a manufacturer-supplied correction function. Turbine inlet steam pressure of a steam turbine power generation system in sliding pressure control mode has a direct one-to-one relationship with the electrical energy load (output) of the steam turbine power system. This new control system provides a more accurate representation of the turbine inlet steam pressure, such that the power generated by a power plant is more closely controlled to the target (demand). More particularly, the feedforward neural network model prediction of the turbine inlet steam pressure more closely fits with the actual turbine inlet steam pressure with very little error, and thereby providing better control over the electrical energy load.

Abstract: Methods and apparatus to optimize turbine ramp rates are disclosed herein. An example method includes predicting a setpoint for a turbine rotor over a prediction horizon. The example method includes predicting a surface temperature profile of the turbine rotor for the prediction horizon based on the predicted setpoint via an empirical data model. The example method also includes predicting a first stress profile for the turbine rotor based on the surface temperature profile. The example method includes performing a comparison of the first stress value to a second stress value and dynamically adjusting the setpoint based on the comparison.

Abstract: A control system for controlling a steam turbine power plant having multiple steam flow paths that converge to a combined steam path controls the final steam temperature of the steam input into the turbine by controlling one or more temperature control devices in each of the steam flow paths. The control system includes a multivariable controller, such as a multi-input/multi-output (MIMO) controller, that produces two control signals that control each of a set of downstream control valves in the split steam flow paths. The controller receives two inputs in the form of measured or calculated process variables including the final steam temperature and the inter-stage temperature difference between the steam being produced in each of the two split steam paths and performs multi-objective control based on these inputs.

Abstract: A process characteristic parameter determination system uses a process model and a tuning module to accurately determine a value for a process characteristic parameter within a plant without measuring the process characteristic parameter directly, and may operate on-line or while the process is running to automatically determine a correct value of the process characteristic parameter at any time during on-going operation of the process. The process characteristic parameter value, which may be a heat transfer coefficient value for a heat exchanger, can then be used to enable the determination of a more accurate simulation result and/or to make other on-line process decisions, such as process control decisions, process operational mode decisions, process maintenance decisions such as implementing a soot blowing operation, etc.

Abstract: Embodiments of methods and systems for controlling a load generated by a power generating system may include controlling at least a portion of the system using model-based control techniques. The model-based control techniques may include a dynamic matrix controller (DMC) that receives a load demand and a process variable as inputs and generates a control signal based on the inputs and a stored model. The model may be configured based on parametric testing, and may be modifiable. Other inputs may also be used to determine the control signal. In an embodiment, a turbine is controlled by a first DMC and a boiler is controlled by a second DMC, and the control signals generated by the first and the second DMCs are used in conjunction to control the generated load. Techniques to move the power generating system from Proportional-Integral-Derivative based control to model-based control are also disclosed.

Abstract: Methods, systems, and non-transitory, computer-readable medium are disclosed to enable a user to configure a process control system. A graphical programming user interface is described for generating coded native control components instantiated from typical and adapter components selected from a library of templates including respective control functions and associated logical expressions. In various embodiments, typical components represent a common core control process or function that is used among one or more other plant equipment devices in the process control system. In addition, various embodiments of the adapter components include one or more parameters that may be changed by a user in conjunction with the logical expressions and/or defined in terms of natural language expressions. As a result, the typical component and the adapter component are instantiated to provide a native control component that provides functionality with respect to one or more control loops within a process control system.

Abstract: An optimal feedforward control design for controlling equipment performs intermittent re-initialization based on estimated state information. A model-based constrained optimization is explicitly performed during the feedforward calculation. During the course of operation of the equipment, state estimation is continuously performed. When a load target change is detected, the estimated state may serve as the new signal baseline.

Abstract: A trip control system for use with, for example, turbines, includes a porting manifold that supports and provides fluid to two or more trip manifolds, each of which includes a bleed circuit having two or more bleed valves connected in parallel between a trip header line and a return or dump line to bleed the hydraulic fluid pressure from the trip header line to thereby cause a trip. The trip control system includes redundant trip manifolds operating in parallel, wherein each trip manifold is able to independently engage a trip of the turbine and each of the trip manifolds includes redundant sets of valves and other trip components that enable the trip manifold to operate to engage a trip of the turbine in the presence of a failure of one of the sets of components on a trip manifold, or while various components of the trip manifold are being tested.