Higher participation levels of wind power in power systems will increase the need for flexible back-up generation to balance the differences between predicted and realized wind power production. This is often an expen...
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Higher participation levels of wind power in power systems will increase the need for flexible back-up generation to balance the differences between predicted and realized wind power production. This is often an expensive solution. With distributed energy resources and more ICT at the demand side, novel, and possibly cheaper, ways for imbalance minimization arise. Micro combined heat-and-power (micro-CHP) is a novel domestic-level generation technology, producing heat and power simultaneously. Clusters of micro-CHPs can function as flexible virtual power plants (VPPs). This paper presents the design of an online coordination scheme that can substantially reduce the imbalance volumes and the associated costs for wind power traders by actively controlling a VPP comprising micro-CHP systems. It is shown that the imbalance volume and associated cost can be reduced by 73 % and 38 %, respectively.
Iterative learning control (ILC) is one application area for the class of 2D linear systems known as repetitive processes where recently experimental evidence to support the performance possible by this approach has b...
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Iterative learning control (ILC) is one application area for the class of 2D linear systems known as repetitive processes where recently experimental evidence to support the performance possible by this approach has been reported. In this paper, we extend the ILC approach to the class of 2D linear systems that often arise from discretization of partial differential equations and, in particular, spatio-temporal dynamics. Application of ILC scheme to a system with such dynamics adds, in effect, one extra indeterminate (the trial number) to the process description and results in the need to analyze a 3D system. The results developed in this paper are the first on ILC control law design and the performance possible is illustrated by numerical simulations.
In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts ...
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In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based on the health state, the failure rate of the equipment can be estimated. We propose to use this predictive health model to predict the effects of different maintenance actions. The effects of maintenance actions over a future time window are evaluated by a cost function. The maintenance actions are optimized using this cost function. The proposed framework is applied in the optimization of the loading of transformers based on the thermal degradation of the paper insulation.
Repetitive processes are a distinct class of two-dimensional (2D) systems (i.e. information propagation in two independent directions occurs) of both systems theoretic and applications interest. They cannot be control...
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ISBN:
(纸本)9781424427994
Repetitive processes are a distinct class of two-dimensional (2D) systems (i.e. information propagation in two independent directions occurs) of both systems theoretic and applications interest. They cannot be controlled by direct extension of existing techniques from either standard (termed 1D here) or (often) 2D systems theory. In this paper we begin the development a systems theory for a model of these processes necessary to represent terms which arise in some applications areas but are not included in the currently used models.
Abstract Problem of scheduling n preemptive jobs on a single processor is studied, in which for each job a distinct due window is given in advance. If a job is completed within its due window, then it incurs no penalt...
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Abstract Problem of scheduling n preemptive jobs on a single processor is studied, in which for each job a distinct due window is given in advance. If a job is completed within its due window, then it incurs no penalty. Otherwise, it incurs a job-independent earliness or tardiness cost. The objective is to find a job schedule such that a maximum of weighted costs associated with earliness and tardiness is minimized. Properties of optimal solutions of this problem are established and an algorithm based on them is presented. It is proved that the analysed problem is solvable in O ( n 2 ) time.
This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for aniso...
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This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for anisotropic and inhomogeneous 3D domains using ten Tusscher's and Nygen's cardiac cell models. During propagation of depolarization wave, the kinetic, compositional and rotational anisotropy is included in the tissue, organ and torso model. The applied patient specific parameters were determined by an evolutionary computation method. An intensive parameter reduction was performed using the abstract formulation of the searching space. This patient specific parameter representation enables the adjustment of deformable model parameters in real-time. The validation process was performed using measured ECG and ultrasound image records that were compared with simulated signals and shapes using an abstract, parameterized evaluation criterion.
The paper presents an optimization based algorithm for stabilizing retarded systems using a state derivative feedback controller. It is shown that an application of such a controller results in neutral dynamics of the...
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The paper presents an optimization based algorithm for stabilizing retarded systems using a state derivative feedback controller. It is shown that an application of such a controller results in neutral dynamics of the closed loop system if small feedback delays occur. Therefore, the strong stability theory of neutral systems needs to be considered in the controller synthesis problem. The stabilization approach is based on minimizing the spectral abscissa of the closed loop system over the controller parameter space, subject to a strong stability constraint.
A method for quasi-direct pole placement is presented for a class of retarded time delay systems with a single control input. The pole placement is done in two steps. First, a number of dominant poles, smaller than th...
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A method for quasi-direct pole placement is presented for a class of retarded time delay systems with a single control input. The pole placement is done in two steps. First, a number of dominant poles, smaller than the number of controller parameters, are directly assigned. This leads to constraints on the controller parameters. By using the singular value decomposition a simple parameterization of all controllers satisfying these constraints is obtained. In the second step, the remaining degrees of freedom in the parameter space are used to shift the remaining part of the system spectrum as far to the left as possible. It is done using an optimization procedure for nonsmooth, nonconvex functions. An extensive real-plant example is presented to demonstrate the application of the novel pole placement procedure.
Experimental data reveal that attenuation is an important phenomenon in medical ultrasound. The phenomenon is of particular importance for applications based on nonlinear propagation, as the higher frequency component...
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Experimental data reveal that attenuation is an important phenomenon in medical ultrasound. The phenomenon is of particular importance for applications based on nonlinear propagation, as the higher frequency components of the pressure field generally experience greater attenuation. Therefore a method that is capable of modeling attenuation accurately is essential. In this paper we present a method to model attenuation via a contrast source formulation. We compare the obtained results with a version of the INCS method in which the attenuation is included in the Green's function. Both results are in excellent agreement with each other.
This paper is concerned with the ∞ model reduction for linear parameter-varying (LPV) systems with both discrete and distributed delays. For a given stable system, our attention is focused on the construction of redu...
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This paper is concerned with the ∞ model reduction for linear parameter-varying (LPV) systems with both discrete and distributed delays. For a given stable system, our attention is focused on the construction of reduced-order models, which approximate the original system well in an ∞ norm sense. First, a sufficient condition is proposed for the asymptotic stability with an ∞ performance of the error system by using the parameter-dependent Lyapunov functional method. Then, the decoupling technique is applied, such that there does not exist any product term between the Lyapunov matrices and the system matrices in the parametrised linear matrix inequality (PLMI) constraints; thus a new sufficient condition is obtained. Based on the new condition, two different approaches are developed to solve the model reduction problem. One is the convex linearisation approach and the other is the projection approach. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed design method
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