Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems
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| Language: | English |
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The Ohio State University / OhioLINK
2013
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=osu1385085547 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-osu1385085547 |
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NDLTD |
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English |
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Electrical Engineering |
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Electrical Engineering Khayyer, Pardis Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
| author |
Khayyer, Pardis |
| author_facet |
Khayyer, Pardis |
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Khayyer, Pardis |
| title |
Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
| title_short |
Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
| title_full |
Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
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Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
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Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems |
| title_sort |
multiple model based estimation and control in large-scale interconnected systems |
| publisher |
The Ohio State University / OhioLINK |
| publishDate |
2013 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=osu1385085547 |
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AT khayyerpardis multiplemodelbasedestimationandcontrolinlargescaleinterconnectedsystems |
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1719435032854003712 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-osu13850855472021-08-03T06:20:37Z Multiple Model Based Estimation and Control in Large-Scale Interconnected Systems Khayyer, Pardis Electrical Engineering Large-scale interconnected systems are subject to system and measurement noise. While small perturbations can be handled by control systems using modern linear time invariant (LTI) theories, larger perturbations and system uncertainties require control methods that take the magnitude of errors and variations into account. Large perturbations are mainly the result of varying operating conditions, system dynamics and failures. In addition, parameter variations due to fault and noise in large-scale interconnected systems significantly affect their dynamic behavior. State estimation and high performance control of the integrated systems requires an effective, real-time and computationally efficient technique. When the system parameters change as a result of fault or effect of noise, the dynamic behavior can be represented as a new model. A Multiple of these models can configure a set of possible scenarios. This research develops both estimation and control theories utilizing the existence of multiple models to represent the varying dynamics. Kalman filters are used for modeling of noise and parameter variations, and adaptive estimation is used in a hypothetical probability evaluation center to determine the individual state estimating probabilities. The decentralized estimation technique is formulated for large-scale interconnected systems and appropriate probability density functions are obtained within the overlapping decomposition context. It is proven that the multiple model adaptive estimation of an extended system is asymptotically stable.In Multiple Model Adaptive Control (MMAC) framework, multiple controllers are designed offline based on the most feasible perturbation/uncertainty criteria. During operation, based on real time measurements, a controller, or combination of controllers is chosen to determine the final control law. Two benchmark problems are resolved by the proposed estimation and control techniques. Plug-in hybrid electric vehicles (PHEVs), as intermittent loads, create frequency disturbances in power systems. The system needs to balance the power generation and demand. However, in regional smart grid systems fed by renewable energy sources and influenced by moveable loads, the power transfer through tie line interconnections is strongly coupled with system dynamics. This makes the frequency stability and control process very slow. An overlapping decomposition technique is used to decouple the regions of renewable energy penetrated power system. A decentralized controller is then designed to maintain the frequency in a short time. Micro-hydro simulation results demonstrate a fast frequency control process to regulate the system under input power variation from wind turbines, and load variation from PHEVs. Renewable energy systems exhibit intermittent behavior that negatively influences the power system transient stability. An energy storage will reduce these oscillations but introduces dependable state variables. A Large-scale system controller can decentralize the system and stabilize the oscillations. This dissertation introduces the application of decentralized overlapping decomposition control in transient stability of renewable energy penetrated storage-based power systems. The controller shows a reduced effect of battery storage unit while maintaining higher performance operation. The storage included a variable droop in power electronics and the state of charge. The overlapping decomposition decentralized controller enhanced the transient stability performance under all state of charge and reduced size battery storage units. 2013 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1385085547 http://rave.ohiolink.edu/etdc/view?acc_num=osu1385085547 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |