| Patent application number | Description | Published |
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| 20080288198 | Method and Apparatus for Generalized Performance Evaluation of Equipment Using Achievable Performance Derived from Statistics and Real-Time Data - A statistical performance evaluation system for a thermodynamic device and process uses the achievable performance derived from statistics and real-time data for the device or process to evaluate the current performance of the device or process, and to adjust the operations of the device or process accordingly, or provide feedback to an operator or other monitoring system for taking corrective actions to obtain performance approaching the optimum achievable performance. The achievable performance of the device or process is derived from data collected during operational periods when the best achievable performance is anticipated, such as after maintenance is performed, and supersedes the ideal or design performance specified by the manufacturer, which typically does not represent the actual operating conditions in the field, as the basis for evaluating the real-time performance of the device. The statistical performance evaluation system may set desired upper and lower limits for performance parameters, and compare desired limits to the actual performance parameter values to determine the readjustment to be made to the operation of the device or process. | 11-20-2008 |
| 20080302102 | Steam Temperature Control in a Boiler System Using Reheater Variables - A technique of controlling a boiler system such as that used in a power generation plant includes using manipulated variables associated with or control inputs to a reheater section of the boiler system to control the operation of the furnace, and in particular to control the fuel/air mixture provided to the furnace or the fuel to feedwater ratio used in the furnace or boiler. In the case of a once-through boiler type of boiler system, using the burner tilt position, damper position or reheater spray amount to control the fuel/air mixture or the fuel to feedwater flow ratio of the system provides better unit operational efficiency. | 12-11-2008 |
| 20090012653 | USE OF STATISTICAL ANALYSIS IN POWER PLANT PERFORMANCE MONITORING - A technique of implementing performance monitoring in a power plant is appropriate to control operating parameters and factors connected with the efficiency of the energy production process in an energy marketplace that is more complex than in the past, and that takes into account more than just the cost of fuel. In particular, this method works well when the real costs of production are dependent on other variable costs besides the cost of fuel, such as environmental credits, equipment degradation and repair costs, as well as electrical energy trade market factors like ramp rate, LMP factors, and the ability to deliver contracted power levels and spot transactions. The power plant performance monitoring technique applies a statistical analysis to collected power plant data to determine the factors that are best controlled or changed to affect (increase) the efficiency or other primary performance indication of the plant, in whatever state or operating level the plant is run. Because heat rate calculation applications are typically performed on-line, it is possible to analyze collected plant data in detail and to apply for example, principal component analysis (PCA) and linear and nonlinear regression analysis to the data, which enables the performance method to obtain a more accurate detection of the influence of the principal process parameters that affect heat rate deviation (efficiency), as well as to establish baseline or best-possible operational constraints to be used to control the plant in the future. This performance based control methodology will allow for near optimum performance of power plants by constantly allowing for refinement and best practices and control to be realized. | 01-08-2009 |
| 20090063113 | Dual Model Approach for Boiler Section Cleanliness Calculation - A method of controlling soot blowers near a heat exchange section includes generating models of both the ideal clean operating condition of the section and the dirty operating condition. The current operating condition of the section is used to calculate a reliability parameter that provides an indication of the reliability of the ideal and dirty models. If the reliability parameter indicates that the models are reliable, the models are used to help evaluate the cleanliness status of a particular heat exchange section and assist in making decisions on whether to blow the section or not, and whether to make any necessary adjustments to the operating sequence of the soot blowers. If the reliability parameter indicates that the models are unreliable, the models are regenerated using additional process data. | 03-05-2009 |
| 20090118873 | VARIABLE RATE FEEDFORWARD CONTROL BASED ON SET POINT RATE OF CHANGE - A method of controlling a power generating unit or other process equipment with a slow reaction time includes creating a feedforward control signal to selectively include a fast response rate component or a slow response rate component based on the average rate at which a load demand set point signal has changed during a particular previous period of time. The method then uses the developed feedforward control signal to control the power generating equipment or other slowly reacting process equipment. In particular, a control method switches between introducing a fast or a slow response component within a feedforward control signal based on whether the change in the load demand set point over a particular period of time in the past (e.g., an average rate of change of the load demand set point signal) is greater than or less than a predetermined threshold. This method is capable of providing a relatively fast control action even if the expected load demand set point change is in a small range. In addition, this method does not require knowledge of the final or target load demand set point during the time in which the load demand set point is ramping up to a final target value and is not dependent on the ramp size, i.e., the ultimate difference between the load demand set point at the beginning of the load demand set point change and the final or target value of the load demand set point, making it more versatile than prior art systems. | 05-07-2009 |
| 20100087933 | TWO-STAGE MODEL PREDICTIVE CONTROL TECHNIQUE - A two-stage model predictive control (MPC) controller uses a process model and two separate MPC control modules, including a feedfoward MPC control module and a feedback MPC control module, to determine a set of control signals for use in controlling a process. The feedforward MPC control module uses the process model to determine a feedforward control component for each of a set of control signals and the feedback MPC control module uses the process model and one or more measured process outputs to determine a feedback control component for each of the set of control signals. The two-stage MPC controller combines the feedforward control components with the feedback control components to form the final control signals used to control the process. The two different control modules may receive separate and different inputs from the process to determine the feedforward control components and the feedback control components and may be tuned separately, to thereby enable a control operator or other user to perform more standardized and stabilized tuning within an MPC controller environment. | 04-08-2010 |
| 20110010138 | METHODS AND APPARATUS TO COMPENSATE FIRST PRINCIPLE-BASED SIMULATION MODELS - Methods and apparatus to compensate first principle-based simulation models are disclosed. An example method to compensate a first-principle based simulation model includes applying one or more first test inputs to a process system to generate first output data, applying one or more second test inputs to a first principle model to generate second output data, generating an error model based on the first and second output data, applying input data to the first principle model to generate simulation model output data, and compensating the model data via the error model to generate compensated model output data. | 01-13-2011 |
| 20110131017 | DECENTRALIZED INDUSTRIAL PROCESS SIMULATION SYSTEM - A high fidelity distributed plant simulation technique includes a plurality of separate simulation modules that may be stored and executed separately in different drops or computing devices. The simulation modules communicate directly with one another to perform accurate simulation of a plant, without requiring a centralized coordinator to coordinate the operation of the simulation system. In particular, numerous simulation modules are created, with each simulation module including a model of an associated plant element and these simulation modules are stored in different drops of a computer network to perform distributed simulation of a plant or a portion of a plant. At least some of the simulation modules, when executing, perform mass flow balances taking into account process variables associated with adjacent simulation modules to thereby assure pressure, temperature and flow balancing (i.e., conservation of mass flow) through the entire simulation system. In a dynamic situation, a transient mass storage relay technique is used to account for transient changes in mass flow through any non-storage devices being simulated by the simulation modules. Moreover, adjacent simulation modules located in different drops communicate directly with one another using a background processing task, which simplifies communications between adjacent simulation modules without the need for a central coordinator. | 06-02-2011 |
