Abstract: Methods and apparatus for optimizing operation of a combined cycle power plant which combines the use of both gas and steam turbines in a single power generating plant. In one embodiment there is provided a closed-loop hybrid neural network-first principles optimizer for optimally allocating fuel across power generation plant blocks and sub systems to minimize fuel costs while meeting capacity and ramp-rate commitments. Embodiments of the methods and apparatus include a steady state plant optimization model and a dynamic plant optimization model.

Abstract: A controller determines and adjusts system parameters, including cleanliness levels or sootblower operating settings, that are useful for maintaining the cleanliness of a fossil fuel boiler at an efficient level. Some embodiments use a direct controller to determine cleanliness levels and/or sootblower operating settings. Some embodiments use an indirect controller, with a system model, to determine cleanliness levels and/or sootblower settings. The controller may use a model that is, for example, a neural network, or a mass energy balance, or a genetically programmed model. The controller uses input about the actual performance or state of the boiler for adaptation. The controller may operate in conjunction with a sootblower optimization system that controls the actual settings of the sootblowers. The controller may coordinate cleanliness settings for multiple sootblowers and/or across a plurality of heat zones in the boiler.

Abstract: A method and apparatus for estimating and/or controlling mercury emissions in a steam generating unit. A model of the steam generating unit is used to predict mercury emissions. In one embodiment of the invention, the model is a neural network (NN) model. An optimizer may be used in connection with the model to determine optimal setpoint values for manipulated variables associated with operation of the steam generating unit.

Abstract: A controller determines and adjusts system parameters, including cleanliness levels or sootblower operating settings, that are useful for maintaining the cleanliness of a fossil fuel boiler at an efficient level. Some embodiments use a direct controller to determine cleanliness levels and/or sootblower operating settings. Some embodiments use an indirect controller, with a system model, to determine cleanliness levels and/or sootblower settings. The controller may use a model that is, for example, a neural network, or a mass energy balance, or a genetically programmed model. The controller uses input about the actual performance or state of the boiler for adaptation. The controller may operate in conjunction with a sootblower optimization system that controls the actual settings of the sootblowers. The controller may coordinate cleanliness settings for multiple sootblowers and/or across a plurality of heat zones in the boiler.

Abstract: A method and apparatus for optimizing the operation of a single or multiple power generating units using advanced optimization, modeling, and control techniques. In one embodiment, a plurality of component optimization systems for optimizing power generating unit components are sequentially coordinated to allow optimized values determined by a first component optimization system to be fed forward for use as an input value to a subsequent component optimization system. A unit optimization system may be provided to determine goals and constraints for the plurality of component optimization systems in accordance with economic data. In one embodiment of the invention, a multi-unit optimization system is provided to determine goals and constraints for component optimization systems of different power generating units. Both steady state and dynamic models are used for optimization.

Abstract: A control system for controlling operation of a fossil fuel fired power generating unit. The control system including both a combustion optimization system and an oxygen optimization system. Both the combustion optimization system and oxygen optimization system each including a model for predicting values of controlled variables and an optimizer for determining optimal setpoint values.

Abstract: A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Abstract: A controller determines and adjusts system parameters, including cleanliness levels or sootblower operating settings, that are useful for maintaining the cleanliness of a fossil fuel boiler at an efficient level. Some embodiments use a direct controller to determine cleanliness levels and/or sootblower operating settings. Some embodiments use an indirect controller, with a system model, to determine cleanliness levels and/or sootblower settings. The controller may use a model that is, for example, a neural network, or a mass energy balance, or a genetically programmed model. The controller uses input about the actual performance or state of the boiler for adaptation. The controller may operate in conjunction with a sootblower optimization system that controls the actual settings of the sootblowers. The controller may coordinate cleanliness settings for multiple sootblowers and/or across a plurality of heat zones in the boiler.

Abstract: A method and apparatus for optimizing the operation of a single or multiple power generating units using advanced optimization, modeling, and control techniques. In one embodiment, a plurality of component optimization systems for optimizing power generating unit components are sequentially coordinated to allow optimized values determined by a first component optimization system to be fed forward for use as an input value to a subsequent component optimization system. A unit optimization system may be provided to determine goals and constraints for the plurality of component optimization systems in accordance with economic data. In one embodiment of the invention, a multi-unit optimization system is provided to determine goals and constraints for component optimization systems of different power generating units. Both steady state and dynamic models are used for optimization.

Abstract: A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

Abstract: A method and apparatus for optimizing the operation of a single or multiple power generating units using advanced optimization, modeling, and control techniques. In one embodiment, a plurality of component optimization systems for optimizing power generating unit components are sequentially coordinated to allow optimized values determined by a first component optimization system to be fed forward for use as an input value to a subsequent component optimization system. A unit optimization system may be provided to determine goals and constraints for the plurality of component optimization systems in accordance with economic data. In one embodiment of the invention, a multi-unit optimization system is provided to determine goals and constraints for component optimization systems of different power generating units. Both steady state and dynamic models are used for optimization.

Abstract: Various embodiments of the invention are directed to methods and systems for assigning credit to the external and intermediate inputs of an enterprise-level system or other aggregate process with one or more global outputs that is composed of a number of interconnected local processes. Assigning credit is a mechanism for evaluating the impact of a particular variable, e.g., an input to one of the local processes, on the final output of the aggregate process. In certain embodiments of the invention, credit is assigned to the local inputs of each local process in two steps. First, for each local input, a local credit assignment is obtained. For chained outputs, credit assignment data is provided as calculated for the later stage processes to which the outputs are chained. Second, a global credit assignment is derived for the local inputs from the local credit assignment and the credit assignment information from later stage processes.

Abstract: A method and apparatus for optimizing the operation of a single or multiple power generating units using advanced optimization, modeling, and control techniques. In one embodiment, a plurality of component optimization systems for optimizing power generating unit components are sequentially coordinated to allow optimized values determined by a first component optimization system to be fed forward for use as an input value to a subsequent component optimization system. A unit optimization system may be provided to determine goals and constraints for the plurality of component optimization systems in accordance with economic data. In one embodiment of the invention, a multi-unit optimization system is provided to determine goals and constraints for component optimization systems of different power generating units. Both steady state and dynamic models are used for optimization.

Abstract: Methods and systems are provided for controlling SCR performance in a boiler. The boiler includes one or more generally cross sectional areas. Each cross sectional area can be characterized by one or more profiles of one or more conditions affecting SCR performance and be associated with one or more adjustable desired profiles of the one or more conditions during the operation of the boiler. The performance of the boiler can be characterized by boiler performance parameters. A system in accordance with one or more embodiments of the invention can include a controller input for receiving a performance goal for the boiler corresponding to at least one of the boiler performance parameters and for receiving data values corresponding to boiler control variables and to the boiler performance parameters. The boiler control variables include one or more current profiles of the one or more conditions.

Abstract: A controller determines and adjusts system parameters, including cleanliness levels or sootblower operating settings, that are useful for maintaining the cleanliness of a fossil fuel boiler at an efficient level. Some embodiments use a direct controller to determine cleanliness levels and/or sootblower operating settings. Some embodiments use an indirect controller, with a system model, to determine cleanliness levels and/or sootblower settings. The controller may use a model that is, for example, a neural network, or a mass energy balance, or a genetically programmed model. The controller uses input about the actual performance or state of the boiler for adaptation. The controller may operate in conjunction with a sootblower optimization system that controls the actual settings of the sootblowers. The controller may coordinate cleanliness settings for multiple sootblowers and/or across a plurality of heat zones in the boiler.

Abstract: A system and method for implementing an indirect controller for a plant. A plant can be provided with both a direct controller and an indirect controller with a system model or a committee of system models. When the system model has sufficient integrity to satisfy the plant requirements, i.e., when the system model has been sufficiently trained, the indirect controller with the system model is automatically enabled to replace the direct controller. When the performance falls, the direct controller can automatically assume operation of the plant, preferably maintaining operation in a control region suitable for generating additional training data for the system model. Alternatively, the system model incorporates a committee of models. Various types of sources for errors in the committee of models can be detected and used to implement strategies to improve the quality of the committee.

Abstract: A method and system are provided for calculating a marginal cost curve for a plant at a plant load range comprising a plurality of specified plant loads. The method includes providing a model used for controlling the plant. The model relates plant load and one or more given cost contributing factors. The marginal value for each of the one or more given cost contributing factors at each of the plurality of specified plant loads is determined using the model. A variable cost at each of the plurality of specified plant loads is determined by: (i) multiplying the marginal value of each of the one or more given cost contributing factors at each of the plurality of specified plant loads by a respective unit cost of each of the one or more given cost contributing factors, and (ii) if there are a plurality of given cost contributing factors, summing the results of (i) at each of the plurality of specified plant loads.

Abstract: A system and method for implementing an indirect controller for a plant. A plant can be provided with both a direct controller and an indirect controller with a system model or a committee of system models. When the system model has sufficient integrity to satisfy the plant requirements, i.e., when the system model has been sufficiently trained, the indirect controller with the system model is automatically enabled to replace the direct controller. When the performance falls, the direct controller can automatically assume operation of the plant, preferably maintaining operation in a control region suitable for generating additional training data for the system model. Alternatively, the system model incorporates a committee of models. Various types of sources for errors in the committee of models can be detected and used to implement strategies to improve the quality of the committee.

Abstract: A system and method for implementing an indirect controller for a plant. A plant can be provided with both a direct controller and an indirect controller with a system model or a committee of system models. When the system model has sufficient integrity to satisfy the plant requirements, i.e., when the system model has been sufficiently trained, the indirect controller with the system model is automatically enabled to replace the direct controller. When the performance falls, the direct controller can automatically assume operation of the plant, preferably maintaining operation in a control region suitable for generating additional training data for the system model. Alternatively, the system model incorporates a committee of models. Various types of sources for errors in the committee of models can be detected and used to implement strategies to improve the quality of the committee.

Abstract: A method and system are provided for determining operating settings for an FGD unit in a boiler. The method includes receiving a performance objective for the FGD unit, receiving data indicating a current state of the FGD unit, using a controller to determine operating settings for the FGD unit to satisfy the performance objective for the FGD unit, and outputting the operating settings to the FGD unit.