A method includes obtaining closed-loop data associated with operation of an industrial process controller, where the industrial process controller is configured to control at least part of an industrial process using at least one model. The method also includes generating at least one noise model associated with the industrial process controller using at least some of the closed-loop data. The method further includes filtering the closed-loop data based on the at least one noise model. In addition, the method includes generating one or more model parameters for the industrial process controller using the filtered closed-loop data.

A controller has improved closed-loop step testing of a dynamic process of an industrial processing plant. The controller performs economic optimization relaxation on process variables, such that operating range of the variables (MVs and CVs) during the testing are not skewed by variations in optimization cost factors. The controller employs computer-implemented methods and systems that receive a user-defined giveaway tolerance representing an allowable range between a current process variable value and a target process variable value. In response to the variables not meeting the giveaway tolerance, the methods and systems adjust the MPC controller configuration to drive the variables inside the tolerance, while relaxing optimization of the variables already meeting the giveaway tolerance. Using the adjusted configuration, the methods and systems calculate a new set of targets and generate a dynamic move plan from the new target. The methods and systems add perturbation signals for the testing to the move plan in accordance with the adjusted configuration.

Estimating energy generated by a solar system in a predetermined geographic area comprises, at each predetermined time instant: retrieving measured values of at least one weather parameter and of solar irradiance in the geographic area, the values related to a time slot before the predetermined time instant; performing auto-regression analysis of the measured values; estimating, based on the auto-regression analysis, a relationship between the at least one weather parameter and the solar irradiance; retrieving forecasted values of the at least one weather parameter in the geographic area, the forecasted values being forecasted for a second time slot after the predetermined time instant; performing regression analysis of the relationship between the at least one weather parameter and the solar irradiance of the forecasted values; forecasting solar irradiance in the second time slot based on the regression analysis, and estimating energy generated by the solar system in the second time slot.

A controller has improved closed-loop step testing of a dynamic process of an industrial processing plant. The controller performs economic optimization relaxation on process variables, such that operating range of the variables (MVs and CVs) during the testing are not skewed by variations in optimization cost factors. The controller employs computer-implemented methods and systems that receive a user-defined giveaway tolerance representing an allowable range between a current process variable value and a target process variable value. In response to the variables not meeting the giveaway tolerance, embodiments adjust the MPC controller configuration to drive the variables inside the tolerance, while relaxing optimization of the variables already meeting the giveaway tolerance. Using the adjusted configuration, embodiments calculate a new set of targets and generate a dynamic move plan from the new target. Embodiments add perturbation signals for the testing to the move plan in accordance with the adjusted configuration.

Provided are an electric power facilities identification number management apparatus and method for generating and managing standard identification numbers for respective electric power facilities by connecting the standard identification numbers with existing identification numbers that are differently set for each operating system. The apparatus generates a standard identification number for an electric power facility associated with an operating system when an existing identification number of the electric power facility is a non-standard identification number, generates a control command for collection of the standard identification number generated and collects the standard identification number generated on the basis of the control command generated, verifies the collected standard identification number.

Techniques to facilitate generation of controller application code that emulates functionality of an industrial controller are disclosed herein. In at least one implementation, a computing system interfaces with the industrial controller and monitors input and output states of the industrial controller while the industrial controller operates a machine system. The input and output states of the industrial controller used to operate the machine system are analyzed to generate a functional design specification for the industrial controller. The controller application code that emulates the functionality of the industrial controller is generated based on the functional design specification.

A method includes obtaining closed-loop data associated with operation of an industrial process controller, where the industrial process controller is configured to control at least part of an industrial process using at least one model. The method also includes generating at least one noise model associated with the industrial process controller using at least some of the closed-loop data. The method further includes filtering the closed-loop data based on the at least one noise model. In addition, the method includes generating one or more model parameters for the industrial process controller using the filtered closed-loop data.

A method includes repeatedly identifying one or more values for one or more model parameters of at least one model associated with a process. The one or more values for the one or more model parameters are identified using data associated with the process. The method also includes clustering the values of the one or more model parameters into one or more clusters. The method further includes identifying one or more additional values for the one or more model parameters using additional data associated with the process. In addition, the method includes detecting a mismatch between the at least one model and the process in response to determining that at least some of the one or more additional values fall outside of the one or more clusters. The values could be clustered using a support vector machine.

A method includes obtaining operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller. The method also includes, during a training period, performing closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying clusters associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period, performing closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters. In addition, the method includes, in response to such a determination, detecting that a mismatch exists between actual and modeled behaviors of the industrial process.

Provided are an electric power facilities identification number management apparatus and method for generating and managing standard identification numbers for respective electric power facilities by connecting the standard identification numbers with existing identification numbers that are differently set for each operating system. The apparatus generates a standard identification number for an electric power facility associated with an operating system when an existing identification number of the electric power facility is a non-standard identification number, generates a control command for collection of the standard identification number generated and collects the standard identification number generated on the basis of the control command generated, verifies the collected standard identification number.