, "A simplified model based supercritical power plant controller", . December 1996. A simplified model based supercritical power plant controller AbstractWe present a simplified state-space model of a once-through supercritical boiler turbine power plant. This phenomenological model has been developed from a greatly simplified application of the first principles of physical laws. When we fit our model to a far more complex and physically accurate simulation model commissioned by EPRI for operator training, we find that the input-output responses are surprisingly close.Encouraged by this initial success, we describe some initial steps toward a design method for supercritical boiler control suggested by the geometric structure arising from the simplified model. Preliminary simulation results suggest that this approach may offer a closed loop response considerably improved relative to that achieved by the linear controllers presently in place in typical industrial settings. Volume 4, 1996, pages 4486-4491. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. NOTE: At the time of publication, author Daniel Koditschek was affiliated with the University of Michigan. Currently, he is a faculty member in the Department of Electrical and Systems Engineering at the University of Pennsylvania. Comments Copyright 1996 IEEE. Reprinted from Proceedings of the 35th IEEE Conference on Decision and Control,This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/ese_papers/375 AbstractWe present a simplified state-space model of a oncethrough supercritical boiler turbine power plant" This pheonomenological model has been developed from a greatly simplified application of first principles physical laws borrowing from (and further simplifying) the assumptions of some previous authors. When we fit our model to a far more complex and physically accurate simulation model commissioned by EPRI for operator training, we find that the input-output responses are surprisingly close.Encouraged by this initial success, we describe some initial steps toward a design method for supercritical boiler control suggested by the geometric structure arising from the simplified model. Very preliminary simulation results suggest that this approach may offer a closed loop response considerably improved relative to that achieved by the linear controllers presently in place in typical industrial settings.
This paper reports on our present achievement toward the intelligent control of a boiler-turbine power-plant based on switching control scheme, recently revived by some active reports. To overcome strong nonlinearity emerging in load following operations of boiler-turbine power plants, which is not efficiently compensated by the conventional PI-based gain scheduling control, a neural-based nonlinear feed-forward switching control scheme is employed. Owing to its 2-degree freedom type installment in the control system and proper switching of nonlinear feed-forward control by monitoring contribution of inverse dynamics error to control error, effective suppression of nonlinearity is achieved. Decision and Control, 1995., Volume 2, pages 1762-1763 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. NOTE: At the time of publication, author Daniel Koditschek was affiliated with the University of Michigan. Currently, he is a faculty member in the Department of Electrical and Systems Engineering at the University of Pennsylvania. Comments Copyright 1995 IEEE. Reprinted from Proceedings of the IEEE Conference on AbstractThis paper reports on our present achievement toward the intelligent control of a boiler-turbine power-plant based on switching control scheme, recently revived by some active reports. To overcome strong nonlinearity emerging in load following operations of boiler-turbine power plants, which is not efficiently compensated by the conventional PI-based gain scheduling control, neural-based nonlinear feedforward Switching control scheme is employed. Owing to its 2-degree freedom type installment in the control system and proper switching of nonlinear feedforward control by monitoring contribution of inverse dynamics error to control error, effective suppression of nonlinearity is achieved.
Power system stabilizers (PSS) are designed to reduce oscillations in power systems. Since PSS cannot absorb energy by itself, surplus energy is consumed by damper windings and loads. On the other hand, if turbine governor which can absorb surplus energy directly is operated pertinently, it will be considered to be effective in recovery of energy balance. We have proposed the Governor-PSS Co-Operative control method, which utilizes mechanical torque supplied by turbines in addition to electrical torque handled by PSS.However, since operation of governor has influence on turbine wings, it cannot be operated by the same frequency band as PSS. In order to take in such complicated specification, the H2 control theory in which delicate adjustment is possible was adopted.This paper shows a H2 controller design procedure consulting conventional PSS properties and the performance of this me-thod through simulation results with widely varied power systems.
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