KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 6 of 6

Some of the metrics are blocked by your
consent settings
Optimal tuning of power system stabilizers by probability method
(2016-09-06)
Thanpisit, Korakot
;
Ngamroo, Issarachai
;
Nakawiro, Worawat
It is well known that the power system stabilizer (PSS) which is designed at one operating point cannot guarantee the stabilizing effect of PSS over a wide range of operating conditions. To achieve the PSS with high stabilizing performance against various conditions, this paper focuses on the new parameters optimization of PSS by the probability method. The PSS structure is the practical 2<sup>nd</sup>-order lead-lag compensator with the local input signal. The optimal tuning of PSS parameters is carried out under random operating conditions generated by Monte Carlo method so that the probability of the occurrence of desired damping ratio for target oscillation modes are maximized. The particle swarm optimization is used to solve for optimal PSS parameters. Study results in the IEEE-39 bus New England system confirm that the proposed PSS yields better damping effect than the conventional PSS under various operating conditions and severe faults.
Some of the metrics are blocked by your
consent settings
Improved H2/H∞ control-based robust PI controller design of SMES for suppression of power fluctuation in microgrid
(2014-10-15)
Vachirasricirikul, Sitthidet
;
Ngamroo, Issarachai
In the microgrid integrated with the renewable energy sources such as wind power and photovoltaic, the random power productions from such renewable sources may cause the severe power fluctuation problem. This paper focuses on a robust controller design of a superconducting magnetic energy storage (SMES) for stabilizing the power fluctuation in a microgrid. The proportional-integral (PI)-based damping controllers for active and reactive power control of SMES are optimally tuned based on the improved H<inf>2</inf>/H<inf>∞</inf> control with the automatic selection of the reference input. The particle swarm optimization is applied to achieve the optimal PI parameters automatically. Simulation results show that the power fluctuation from the renewable sources is greatly damped by robust SMES controller.
Some of the metrics are blocked by your
consent settings
Robust LFC in a smart grid with wind power penetration by coordinated V2G control and frequency controller
(2014-01-01)
Vachirasricirikul, Sitthidet
;
Ngamroo, Issarachai
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 H<inf>2</inf>/H<inf>\infty</inf> control. Simulation results show the superior robustness and control effect of the proposed coordinated controllers over the compared controllers. © 2013 IEEE.
Some of the metrics are blocked by your
consent settings
Optimal fuzzy logic-based adaptive controller equipped with DFIG wind turbine for frequency control in stand alone power system
(2013-12-01)
Sa-Ngawong, Nattapol
;
Ngamroo, Issarachai
This paper deals with an adaptive controller design by an optimal fuzzy logic of doubly fed induction generator (DFIG) wind turbine for frequency control in the stand alone power system. Since the DFIG wind turbine has the ability of active power control, this makes the possibility of system frequency control contribution by DFIG. The optimal fuzzy logic adapts the control parameters of the supplement controller equipped with the DFIG wind turbine so that the active power output can be controlled to alleviate the frequency deviation due to load changes. In the fuzzy logic design, the membership function and the control rules are automatically optimized by the particle swarm optimization. Simulation study confirms that the control effect and robustness of the proposed adaptive controller is superior to that of the conventional controller with fixed parameters against various random load changes and system parameters variation. © 2013 IEEE.
Some of the metrics are blocked by your
consent settings
PSO-based Sugeno fuzzy logic controller of photovoltaic generator for frequency stabilization in stand-alone power system
(2013-01-01)
Sa-Ngawong, Nattapol
;
Ngamroo, Issarachai
This paper proposes a particle swarm optimization-based Sugeno fuzzy logic controller (PSO-SFLC) of photovoltaic (PV) generator for frequency stabilization in a stand-alone power system. The PSO-SFLC is used to adjust the modulation ratio of the PV inverter so that the PV output power can be swiftly controlled to follow the load change and stabilize the system frequency fluctuation. The PSO is used to automatically tune membership functions and control rules of SFLC. The input signals of SFLC are solar insolation and frequency deviation signals while the output signal is the modulation ratio of the inverter. In the simulation study, the frequency stabilizing effect of PV with PSO-SFLC is compared with the PV with SFLC and the PV with maximum power point tracking under random load and solar insolation change. Simulation results show the superior effect of the PV with proposed PSO-SFLC over the PV with SFLC and the PV with maximum power point tracking. © 2013 IEEE.
Some of the metrics are blocked by your
consent settings
Optimal least squares support vector machines for SMES controller design using wide area phasor measurements
(2012-07-01)
Pahasa, Jonglak
;
Ngamroo, Issarachai
In this paper, the least squares support vector machines (LS-SVMs) based design of superconducting magnetic energy storage (SMES) controller is proposed for wide area stability control. The LS-SVMs for SMES controllers are trained by local and inter-area data based on synchronized phasor measurements considering time delay. A large amount of training data set of a multi-machine power system is reduced by the measurement of similarity among samples. The LS-SVM parameters and the similarity threshold are optimized by a particle swarm optimization. Subsequently, the redundant data in the training set can be discarded while the reduced data are the optimal support vectors in the LS-SVM model. The LS-SVM control signals can be adapted by various operating conditions and different disturbances. Simulation results in a six-area West Japan interconnected power system demonstrate that the proposed LS-SVM for SMES controller is robust to various disturbances under wide range of operating conditions in comparison to the conventional SMES. Copyright © 2011 John Wiley & Sons, Ltd.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results