Abstract:
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.
Abstract:
Various embodiments include a system having: at least one computing device configured to perform actions including: measuring at least one of the following parameters: a steam pressure within a steam drum, a load on a GT, a position of a bypass valve bypassing an HRSG, and a steam flow rate through the steam drum; defining a threshold range for each of: a steam pressure within the steam drum, a load on the GT, a position of the bypass valve bypassing the HRSG and a steam flow rate through the steam drum based upon the measured data and a target steam level; and adjusting the steam flow rate through the steam drum in response to at least one of the measured parameters deviating from the corresponding threshold range.
Abstract:
The present subject matter is directed to a system and method for optimizing wind turbine operation. For example, the present disclosure is configured to generate operating data for at least one operational parameter of the wind turbine for a predetermined time period. The system can then determine a robustness measurement of at least a portion of the operating data. In general, the robustness measurement indicates the tendency of the operating data to be affected by outliers present in the operating data. In addition, the robustness measurement is typically a function of a distribution of the operating data. The present disclosure is then configured to determine at least one optimal set point for the operational parameter as a function of the robustness measurement and a power production of the wind turbine. The wind turbine can then be operated based on the optimal set point.
Abstract:
A method for optimizing a fleet of generating assets in which groupings include remotely located power blocks that operate so to collectively generate a fleet output level. The method may include: receiving real-time and historical measured values of operating parameters; for each of the generating assets, deriving a relational expression between the measured values of the process inputs and the measured values of the process outputs; defining a selected operating period; selecting competing operating modes for the fleet; based on the relational expressions and a generating configuration of the competing operating modes, calculating a result set for the operation of the fleet proposed during the selected operating period; defining a cost function; and evaluating each of the result sets pursuant to the cost function and, based thereupon, designating one of the competing operating modes as an optimized operating mode. The optimized operating mode may include a power sharing recommendation between the power blocks of the fleet.
Abstract:
A method for optimizing a generation of an output level over a selected operating period by a power block, wherein the power block comprises multiple gas turbines for collectively generating the output level. The control method may include: receiving current state data regarding measured operating parameters for each of the gas turbines of the power block; based on the current state data, defining competing operating modes for the power block; based on each of the competing operating modes, deriving a predicted value for a performance parameter regarding the operation of the power block over the selected operating period; determining a cost function and, pursuant thereto, evaluating the operation of the power block based on the predicted value of the performance parameter so to determine a projected cost; and comparing the projected costs from each of the optimized operating modes so to select therefrom an optimized operating mode.
Abstract:
Embodiments of the disclosure can relate to providing an integrated power plant advisor. In one embodiment, a method for providing an integrated power plant advisor can include receiving a signal associated with a failure of a power plant or a power plant component. The method can further include determining one or more root causes associated with the failure of the power plant or the power plant component. Based at least in part on operational data and training data from one or more power plants, a ranking of the one or more root causes associated with the failure of the power plant or the power plant component can be determined. The method can further include outputting the ranking via a client device. Based at least in part on the ranking, a repair or replacement strategy for the power plant or the power plant component can be identified.
Abstract:
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.
Abstract:
A device receives sensed operation parameters related to the operation of a machine. The device utilizes the sensed operation parameters in a first analyzer that generates first characteristics related to degradation of the machine and utilizes the sensed operation parameters in a second analyzer configured to generate second characteristics related to thermal characteristics of the machine, wherein the thermal characteristics include thermal stresses present in the machine. The device also utilizes the first and second characteristics and a third characteristic related to operator behaviors related to the current operation of the machine to generate remaining useful life characteristics of components of the machine and generates operational set points for control of the machine based in part on the remaining useful life characteristics, desired machine performance characteristics based on the operator behaviors, and maintenance characteristics of the machine.
Abstract:
A method of controlling a water level in a steam drum includes predicting a transient in the steam drum based on plant characteristics including steam flow from the steam drum, drum pressure in the steam drum, and one or both of a gas turbine load and a position of a bypass valve configured to control the steam flow from the steam drum to two or more steam flow conduits. The method further includes generating a sliding setpoint to control the water level based on predicting the transient in the steam drum.
Abstract:
A combined cycle power plant system that includes: a gas turbine operably connected to a heat recovery steam generator; a first controller for optimizing a shutdown operation defined between an initiating shutdown command and a terminating event, wherein the first is controller configured to execute the steps of: receiving the shutdown initiating command; receiving operating parameters measured by sensors for each of a first component and a second component of the combined cycle power plant, and, based thereupon, determining a current state for each of the first and the second component; based on the current state, deriving an optimized shutdown operating mode for transitioning the first component and the second component from the current state to a shutdown state. A second controller may be configured to: transform the optimized shutdown operating mode into commands configured to actuate mechanical control devices of the first component and the second component so that the shutdown operation proceeds according to the optimized shutdown operating mode.