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Phayao, Thailand

Vachirasricirikul S.,University of Phayao | Ngamroo I.,King Mongkuts University of Technology Thonburi
IEEE Transactions on Smart Grid

In the smart grid, the large scale wind power penetration tends to expand vastly. Nevertheless, due to the intermittent power generation from wind, this may cause a problem of large frequency fluctuation when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. Also, in the future transport sector, the plug-in hybrid electric vehicle (PHEV) is widely expected for driving in the customer side. Generally, the power of PHEV is charged by plugging into the home outlets as the dispersed battery energy storages. Therefore, the vehicle-to-grid (V2G) power control can be applied to compensate for the inadequate LFC capacity. This paper focuses on the new coordinated V2G control and conventional frequency controller for robust LFC in the smart grid with large wind farms. The battery state-of-charge (SOC) is controlled by the optimized SOC deviation control. The structure of frequency controller is a proportional integral (PI) with a single input. To enhance the robust performance and robust stability against the system uncertainties, the PI controller parameters and the SOC deviation are optimized simultaneously by the particle swarm optimization based on the fixed structure mixed H2/H\infty control. Simulation results show the superior robustness and control effect of the proposed coordinated controllers over the compared controllers. © 2013 IEEE. Source

Pahasa J.,University of Phayao | Ngamroo I.,King Mongkuts University of Technology Thonburi
Expert Systems with Applications

This paper presents the application of least squares support vector machines (LS-SVMs) to design of an adaptive damping controller for superconducting magnetic energy storage (SMES). To accelerate LS-SVMs training and testing, a large amount of training data set of a multi-machine power system is reduced by the measurement of similarity among samples. In addition, the redundant data in the training set can be significantly discarded. The LS-SVM for SMES controllers are trained using the optimal LS-SVM parameters optimized by a particle swarm optimization and the reduced data. The LS-SVM control signals can be adapted by various operating conditions and different disturbances. Simulation results in a two-area four-machine power system demonstrate that the proposed LS-SVM for SMES controller is robust to various disturbances under a wide range of operating conditions in comparison to the conventional SMES. © 2011 Elsevier Ltd. All rights reserved. Source

Rakpenthai C.,University of Phayao | Uatrongjit S.,Chiang Mai University | Premrudeeprechacharn S.,Chiang Mai University
IEEE Transactions on Power Systems

This paper addresses the state estimation of a power system whose network parameters are known to be within certain tolerance bounds. The power system is assumed to be fully observable by having enough phasor measurement units installed. Using synchronized phasor measurement data and state variables expressed in rectangular forms, the state estimation under the transmission line parameter uncertainties is formulated based on the weight least square criterion as a parametric interval linear system of equations. The solutions are obtained as interval numbers representing the outer bound of state variables. The proposed method is also extended to a power system with mixed phasor and conventional power measurements. A technique based on affine arithmetic for converting state variable into polar form is also presented. The proposed method has been implemented using MATLAB and INTLAB toolbox and applied to some IEEE test systems. The numerical experiment results indicate that, in shorter computation time, the proposed algorithm can find the outer bounds that are close to those computed by performing Monte Carlo simulations or by solving constrained nonlinear optimization problems. © 2006 IEEE. Source

Pimanmas A.,Thammasat University | Chaimahawan P.,University of Phayao
Engineering Structures

This paper presents planar joint enlargement for increasing the shear strength of sub-standard beam-column joint. Five beam-column specimens were tested under quasi-static cyclic loads. Two control specimens were tested. One was the beam-column joint without joint enlargement and the other was the beam-column joint strengthened by monolithically cast square enlargement. The other three specimens were strengthened by joint enlargements with various sizes. Test results indicated a brittle joint shear failure in the first control specimen and a beam flexural failure in the second control specimen. Depending on the size of enlargement, the failure types of strengthened specimens ranged from flexural failure in the beam to crushing failure in joint panel and enlarged areas. The joint enlargement can increase the strength, stiffness and energy dissipation. The experimental results indicated the decrease in joint shear stress in strengthened specimens. However, the distribution of horizontal shear stress is not uniform, with larger value in the joint panel than in the beam sections within the enlarged areas. Finite element analysis has been conducted to examine the flow of stresses in the joint and enlarged areas. The finite element analysis illustrates the principal diagonal strut in the joint panel and additional struts along the edge of enlargements and in beam sections within the enlargement zone. Based on principal stress pattern obtained from finite element analysis, strut-and-tie model is constructed to analyze the strengthened specimens. The proposed strut-and-tie model can predict the failure mode, column shear force and tension forces in longitudinal steel bars and dowels. It can also predict the distribution of horizontal shear stress in the joint panel and beam sections within the enlarged areas. © 2010 Elsevier Ltd. Source

Vachirasricirikul S.,University of Phayao | Ngamroo I.,King Mongkuts University of Technology Thonburi
International Journal of Electrical Power and Energy Systems

This paper proposes a new robust controller design of microturbine (MT) and electrolyzer (ES) in a control and monitoring system (CMS) for frequency stabilization in a microgrid system with plug-in hybrid electric vehicles (PHEVs). In the studied microgrid, the MT is normally used to provide the main power to the loads while the ES absorbs the power from the system to produce the hydrogen as the fuel input for the power generation of the fuel cell. On the other hand, the large numbers of PHEVs are utilized in the consumer side. The concurrent charging powers of PHEVs cause a problem of severe frequency fluctuation in the microgrid. To solve this problem, the frequency stabilization of CMS is performed by controlling the power output of MT and ES. The controller structure of MT and ES is a proportional integral with a single input. To enhance the tracking performance and the robustness against system uncertainties of the designed MT and ES controllers, the control parameters are optimized by shuffled frog leaping algorithm based on specified-structure mixed H 2/H ∞ control technique. Simulation results not only show the frequency stabilization effect against the random charging power of PHEVs but also the high robustness of the proposed robust MT and ES controllers against the system parameters variation. © 2012 Elsevier Ltd. All rights reserved. Source

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