Power systems and methods of controlling power systems are disclosed. The system may include a power plant system (PPS) including a component and at least one computing device in communication with the PPS. The computing device(s) may be configured to control the PPS by performing processes including determining if an operational anomaly for the component occurred during operation of the PPS. In response to determining that the operational anomaly did not occurr, the computing device(s) may also perform processes including determining a first operational reliability of the component. In response to determining the operational anomaly occurred, the computing device(s) may also perform processes including determining a second operational reliability of the component based on the determined operational anomaly. Additionally, the computing device(s) may perform processes including adjusting operation of the PPS in response to the first operational reliability or the second operational reliability exceeding a predetermined operational reliability threshold.

A control system for a technical plant, in particular a process or manufacturing plant, includes an operator station server and an operator station client, wherein the operator station server includes a computer implemented visualization service that transmits a plant mimic diagram to the operator station client that visually presents the plant mimic diagram to an operator of the control system, where a digital process image of the technical plant is implemented on the operator station server, the operator station server additionally enables the operator to continuously monitor a runtime operator specifiable state of an operator-specifiable measuring device of the technical plant, where the operator station server additionally notifies the operator of a state change of the measuring device, independently of a visual presentation of the plant mimic diagram, and where the measuring device state is obtainable from the digital process image of the technical plant implemented on the operator station server.

The purpose of the present invention is to provide a plant operation optimization assistance device, a plant operation optimization control device, and a method, which enable a reduction in computational load. The plant operation optimization assistance device is characterized by comprising: an input unit for inputting, as an input signal, an operation amount signal assigned to a plant and a process signal detected at the plant; a sensitivity estimation unit for taking, as a sensitivity signal, a time change amount of the process signal with respect to the operation amount signal; and a signal classification unit for sorting operational states of the plant from the input signal and giving an operational state signal, and also extracting, as a state-specific high-sensitivity signal, a sensitivity signal indicating high-sensitivity, from among sensitivity signals, for each of the sorted operational states.

A method for testing a plant control system of an inverter-based resource (IBR) coupled to an electric power grid, the method comprising: using a power systems modeling environment implemented in an information system, generating an IBR model, the IBR model including an inverter control model, a generator model, a network solution model, and a model power meter; using a hardware-in-the-loop (HIL) simulation environment including the IBR model, a phasor data concentrator (PDC), a test automation server, and the plant control system, performing a test of the plant control system by iteratively: receiving measurements from the PDC and setpoints from the test automation server and sending the measurements and the setpoints to the plant control system; generating and sending an active power command and a reactive power command from the plant control system to the inverter control model; generating and sending desired active current and desired reactive current from the inverter control model to the generator model; generating and sending active and reactive currents from the generator model to the network solution model, the network solution model generating and sending a terminal voltage measurement to the generator model and the inverter control model, the network solution model generating and sending POI measurements to the model power meter; generating synchrophasors including electrical property information and sending the synchrophasors from the model power meter to the PDC; generating the measurements from the synchrophasors at the PDC; and, storing the synchrophasors as results of the test in the test automation server.

A control parameter optimizing system and an operation optimizing apparatus equipped therewith are provided, the system being applicable to an existing plant without modifying the control panel or equipment of the plant, the system further being capable of optimizing the operation control of the plant in accordance with diverse operational requirements. The system includes an objective function setting section, a plant model, and a control parameter optimizing section. The control parameter optimizing section includes an optimization control parameter selecting section and an optimization control parameter adjusting section. The optimization control parameter selecting section selects as an optimization control parameter the control parameter for optimizing an objective function based on control logic information extracted from a power plant. The optimization control parameter adjusting section adjusts the value of the optimization control parameter using the plant model in such a manner as to optimize the objective function.

A plant operation assistance system includes: a risk calculation unit which calculates a risk of failure in a measure against an event against which the measure should be taken; an operation influencing factor determination unit which determines an operation influencing factor on the basis of a performance situation and an environment situation respectively determined on the basis of information indicating an internal characteristic of an operator and information indicating an external characteristic of the operator; and a step importance degree determination unit which determines, on the basis of the operation influencing factor and each of step importance indexes calculated from the risk, a step importance degree of a corresponding one of steps in a case of performing the step by the operator.

This plant control support system is provided with an acquisition unit, a generation unit, and an output unit, in order to provide a technique for appropriately supporting plant control without relying on the know-how and knowledge of experts and manuals. The acquisition unit acquires state information regarding the state of a plant. The generation unit uses a control model, and on the basis of the state information, generates control contents according to the state of the plant as proposed control contents. The control model is a model obtained by training the relationship between the control contents for controlling the plant and the control result obtained by executing the control of the control contents on the plant. The output unit outputs the proposed control contents.

Embodiments of the present disclosure relate improved asset performance monitoring and plantwide optimization improvement. Performance data for a set of assets may be generated by performing analytics on plant data associated with the set of assets. The set of assets may include at least a plantwide optimizer (PWO) controller and one or more advanced process control (APC) controllers associated with the PWO controller. A first performance metric for the PWO controller that fails to satisfy a first performance threshold may be identified by comparing the performance data to one or more PWO performance thresholds. Performance insight data may be generated in response to identifying the first performance metric at least in part by applying the performance data to one or more analytical models comprising one more asset performance dependency graphs. Performance of one or more plantwide optimization implementation actions may be initiated based on the performance insight data.