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.

An electrolyzer plant comprising a plurality of electrolyzer modules includes a system having a processing unit that determines, for each of the plurality of electrolyzer modules, an electrolyzer module set point at which the electrolyzer module is to be operated, and controls operation of each of the plurality of electrolyzer modules at the respective electrolyzer module set point. The determining comprises inputting data representative of operation characteristics of each of the plurality of electrolyzer modules into the processing unit and the processing unit performing an optimization procedure that outputs the electrolyzer module set points, the optimization procedure comprising an optimization for one or more of overall electrolyzer plant efficiency, overall plant lifetime, lifetime of each of the electrolyzer modules, operational safety, and maintenance patterns.

A method of compact-form model-free adaptive disturbance compensation control in the presence of measurable disturbances includes establishing a dynamic data model of a controlled plant subject to measurable disturbances, wherein the dynamic data model is described by a pseudo Jacobian input matrix and a pseudo Jacobian disturbance matrix; constructing cost functions and solving their optimization problems to find optimal values of the pseudo Jacobian input matrix and the pseudo Jacobian disturbance matrix; designing a compact-form model-free adaptive disturbance compensation control law in the presence of measurable disturbances; constructing an energy function and solving it by using a momentum gradient descent method to find optimal values of the compact-form adaptive input matrix and the compact-form adaptive disturbance matrix; controlling the controlled plant by using the control law. The control method of the present invention provides significant improvements in disturbance compensation control performance and achieves effective tracking of desired system outputs.

A method of partial-form model-free adaptive disturbance compensation control in the presence of unmeasurable disturbances includes establishing a dynamic data model of a controlled plant subject to unmeasurable disturbances, wherein the dynamic data model is described by a pseudo Jacobian input matrix and a pseudo Jacobian disturbance matrix; constructing cost functions and solving their optimization problems to find optimal values of the pseudo Jacobian input matrix and the pseudo Jacobian disturbance matrix; designing a partial-form model-free adaptive disturbance compensation control law in the presence of unmeasurable disturbances; constructing an energy function and solving it by using a momentum gradient descent method to find optimal values of the partial-form adaptive input matrix and the partial-form adaptive disturbance matrix; controlling the controlled plant by using the control law. The control method of the present invention provides significant improvements in disturbance compensation control performance and achieves effective tracking of desired system outputs.

A method of full-form model-free adaptive disturbance compensation control in the presence of measurable disturbances, includes establishing a dynamic data model of a controlled plant subject to measurable disturbances, wherein the dynamic data model is described by a pseudo Jacobian input matrix and a pseudo Jacobian disturbance matrix; constructing cost functions and solving their optimization problems to find optimal values of the pseudo Jacobian input matrix and the pseudo Jacobian disturbance matrix; designing a full-form model-free adaptive disturbance compensation control law in the presence of measurable disturbances; constructing an energy function and solving it by using a momentum gradient descent method to find optimal values of the full-form adaptive input matrix and the full-form adaptive disturbance matrix; controlling the controlled plant by using the control law. The control method of the present invention provides significant improvements in disturbance compensation control performance and achieves effective tracking of desired system outputs.

Systems and methods for providing intelligent management of balance of plant are provided. According to one embodiment of the disclosure, a system for determining a malfunction of a feedwater pump includes one or more processors and a database communicatively coupled to the one or more processors. The one or more processors can be configured to receive plant parameters. The one or more processors can be further configured to correlate the plant parameters to historical operational values. Based at least partially on the correlating, the one or more processors may be operable to identify a malfunction in a feedwater pump. Based at least partially on the identifying, the one or more processors may be operable to provide an advisory action concerning an operation of the feedwater pump.

A method for visually representing temporally aggregated measurement values includes generating image information over a period of time from temporally aggregated measurement values of a measurement variable associated with a technical object of a technical plant by an operator station server of a control system of the technical plant, adding information to the image information concerning fuzziness of the temporal aggregation of a specific temporally aggregated measurement value by comparison with the non-aggregated measurement values taken into consideration for the temporal aggregation of the specific measurement value, transmitting the image information to an operator station client, visually presenting the time profile of the temporally aggregated measurement values and the information concerning the fuzziness of the specific temporal aggregation of the temporally aggregated measurement points to an operator of the technical plant.

Embodiments of the present disclosure provide a method and system for digital plant system model creation and simulation and a storage medium. The method includes: receiving a digital model created by a user based on a modeling library: in the modeling library, a digital plant system is divided into multiple subsystems, and motion joints in each subsystem are set with at least one option of at least one solution parameter of dynamics, kinematics and articulation; for each motion joint in the digital model, associating a corresponding algorithm engine in a simulation engine with the motion joint according to a solution parameter of the motion joint: the simulation engine comprises a kinematics algorithm engine, a dynamics algorithm engine and an articulation algorithm engine: using the corresponding algorithm engine to solve the motion joint associated with the algorithm engine. The technical scheme in embodiments of the present disclosure can improve the performance, stability and accuracy of the virtual digital plant.

The invention refers to an edge computing device 120 for processing data 112 acquired with respect to a production process of an industrial plant comprising a plant control system 110, wherein the control system comprises a server 111. The device comprises a first unit 125 configured to be communicatively coupled to the server for receiving the data from the system. A second unit 121 is configured to provide a container runtime environment 122 configured to run a container on the second unit. A process container 123 is configured to run on the environment, wherein the process container comprises a program configured to process data acquired with respect to a production process of the industrial plant when running inside the process container. The first unit is communicatively coupled to the second unit for providing the received data to the environment, wherein the program is configured to process the provided data.

Techniques for reconciling discrepancies between the runtime operation of a process plant and the configuration for the process plant allow for the process plant to be operated in a predictable and consistent manner. Additionally, techniques for reconciling discrepancies in the process plant enable inappropriate parameter values to be detected and reconciled efficiently and before such inappropriate values are included into configuration. Such techniques reduce the risk of downtime for online operation of the process plant to troubleshoot object configuration. A configuration engineer may provide one or more reconciliation instructions to reconcile the discrepancy. A configuration application then updates the process control environment of the process plant in accordance with the one or more reconciliation instructions. In some cases, the discrepancy is resolved by updating a configuration file for the object. In other cases, the discrepancy is resolved by updating the runtime instantiation of the object.