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Simultaneous control of frequency fluctuation and battery SOC in a smart grid using LFC and EV controllers based on optimal MIMO-MPC
(2017-03-01)
Pahasa, Jonglak
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Ngamroo, Issarachai
This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model- based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.
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Intelligent photovoltaic farms for robust frequency stabilization in multi-area interconnected power system based on PSO-based optimal Sugeno fuzzy logic control
(2015-02-01)
Sa-ngawong, Nattapol
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Ngamroo, Issarachai
Currently, the grid-connected large PV farms are extensively installed in power systems. Nevertheless, in addition to the load change, the intermittent power output of PV farms may lead to the serious problem of the system frequency fluctuation. To handle this problem, this paper proposes a new design of Sugeno fuzzy logic controller based on particle swarm optimization (PSO-SFLC) of intelligent PV farms for the frequency stabilization in a multi-area interconnected power system. To handle various scenarios, the frequency deviations and solar insolations are used as input signals of the PSO-SFLC. The output signal of the PSO-SFLC is a command signal for adjusting PV output power. The output power of PV is controlled by the PSO-SFLC to meet the load demand so that the system frequency fluctuation can be suppressed. Without the difficulty of trial and error, the optimal input and output membership functions, and control rules of PSO-SFLC are automatically achieved by PSO. Simulation study in a three-area loop interconnected power system with large PV farms elucidates that the frequency stabilizing performance and robustness of the PV equipped with the PSO-SFLC is much superior to that of the PV with the SFLC and the PV with the maximum power point tracking control in scenarios with various solar insolations and loading conditions.
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Wide area robust centralized PSO-based specified structure H∞ power system damping controller design considering uncertainties in time delay and system parameters
(2013-02-15)
Ngamroo, Issarachai
It is well known that the time delay due to the wide area phasor measurement may cause a malfunction of wide area centralized control of power system damping controller (PSDC) and system instability eventually. Nevertheless, the uncertainties due to time delay and system parameters have never been considered in the previous researches of PSDC design. To tackle this problem, a wide area robust centralized particle swarm optimization (PSO)-based specified structure H<inf>∞</inf> PSDC design taking uncertainties due to communication delay and system parameters into account is proposed in this paper. Without explicit mathematic equations, the inverse input multiplicative model is applied to represent the unstructured uncertainties. The structure of PSDC is the practical 2nd order lead/lag compensator. To automatically tune the control parameters, the optimization based on an enhancement of damping effect and robust stability margin is achieved by PSO. To evaluate the proposed design technique, two examples of robust centralized PSDC, i.e., power system stabilizer and thyristor control series capacitor are demonstrated in a two-area four-machine interconnected power system,. Simulation study confirm that the proposed robust centralized PSDC is much superior to the conventional centralized PSDC in terms of stabilizing effect and robustness against uncertainties due to time delay and system parameters. © 2013 ICIC International.
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Specified structure mixed H2=H∞ control-based robust frequency stabilization in a smart grid by plug-in hybrid electric vehicles
(2013-01-16)
Ngamroo, Issarachai
In the future smart grid, the penetration of wind power tends to increase significantly. This may cause the tie-line power and frequency fluctuations in the power grid. On the other hand, the plug-in hybrid electric vehicles (PHEV) are highly expected to be installed in the customer side. The bidirectional power control of PHEV can be applied to stabilize the power and frequency fluctuations. This paper proposes the specified structure mixed H<inf>2</inf>=H<inf>∞</inf> control design of bidirectional power controller of PHEV for robust frequency stabilization of the smart grid with large wind farms. System uncertainties are represented by the multiplicative perturbation model. The structure of power controller is specified as a proportional integral (PI) with single input. The PI parameters optimization problem is formulated based on the enhancement of control performance and robustness against system uncertainties. Without the difficulty of weighting functions selection as in a mixed H<inf>2</inf>=H<inf>∞</inf> control, the PI parameters are automatically tuned by particle swarm optimization. Simulation results confirm that the proposed robust controller is much superior to the conventional controller in terms of control performance and robustness against various uncertainties. © 2013 ICIC International.
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PSO-based specified structure mixed H2/H∞ multiple PHEV controllers for robust frequency control in interconnected power systems with large wind farms
(2013-01-16)
Rattanapornchai, Chalotorn
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Ngamroo, Issarachai
This paper focuses on the new robust control design of multiple plug-in hybrid electric vehicle (PHEV) units for frequency control in interconnected power systems with large wind farms. The controller structure of PHEV is specified as a proportional integral (PI). Unstructured system uncertainties such as various wind patterns, system parameters variation, are modeled by the inverse output multiplicative perturbation. The particle swarm optimization is applied for tuning the PI parameters for all PHEV units based on the mixed H<inf>2</inf>/H<inf>∞</inf> control approach. Simulation results confirm the superior performance and robustness of the proposed PHEV controller. © 2013 ISSN 1881-803X.
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Alleviation of power fluctuation in interconnected power systems with wind farm by SMES with optimal coil size
(2012-06-25)
Saejia, Mongkol
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Ngamroo, Issarachai
The large penetration of wind power into interconnected power systems causes the severe power fluctuation in tie-lines. To alleviate power fluctuation, the superconducting magnetic energy storage (SMES) can be applied. Nevertheless, the installation of SMES is quite costly. Especially, the superconducting coil size which is the vital part of SMES, must be carefully specified. This paper proposes a new optimization technique of power controller parameters and coil sizes of multiple SMES units for alleviation of tie-line power fluctuation in interconnected power systems with wind farms. The structure of active and reactive power controllers of SMES is the proportional-integral (PI). Based on the minimization of the variance of tie-line power fluctuation and the initial stored energy of a SMES unit, the optimal PI parameters and coil size can be automatically tuned by a particle swarm optimization. Simulation study in the West Japan interconnected systems confirms that the proposed SMES with optimal coil size is able to effectively and robustly suppress power fluctuation against various wind power patterns and heavy power flow levels. © 2002-2011 IEEE.
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Robust load frequency control in a smart microgrid with PHEV-based V2G control
(2012-06-12)
Vachirasricirikul, Sitthidet
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Ngamroo, Issarachai
This paper focuses on a new design of frequency controller for robust load frequency control (LFC) in a smart isolated microgrid (MG) system with plug-in hybrid electric vehicles (PHEV)-based vehicle-to-grid (V2G) control and wind farms. The V2G control can compensate the unbalance of real power in system. The state-of-charge (SOC) of battery can be managed by using the SOC balance control method. The studied frequency controller structure is a proportional integral (PI) with a single input. The multiplicative uncertainty is used to model the system uncertainties. To improve both robust stability margin and performance, the PI control parameters are automatically designed by the particle swarm optimization (PSO) based on the specified-structure mixed H <inf>2</inf>/H <inf>∞</inf> control method. Simulation results exhibit the superior robustness and performance of the proposed controller against the system parameters change.
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PSO-based learning of support vector machines for adaptive TCSC
(2012-06-12)
Pahasa, Jonglak
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Hongesombut, Komsan
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Ngamroo, Issarachai
This paper proposes the design of an adaptive thyristor controlled series capacitor (TCSC) using support vector machines (SVMs) and particle swarm optimization (PSO). The SVMs for an adaptive TCSC are trained by the data obtained from a multi-machine power system. PSO is used to optimize the SVM parameters based on k-fold cross-validation technique. The TCSC parameters produced by SVMs can be adapted by various operating conditions. Simulation results in a two-area four-machine power system demonstrate that the proposed SVMs for an adaptive TCSC is much superior to the conventional TCSC with fixed parameters under various operating conditions.
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Bidirectional power controller design of PHEV for robust frequency control
(2012-06-12)
Ngamroo, Issarachai
;
Rattanapornchai, Chalotorn
This paper presents a bidirectional power controller design of plug-in hybrid electric vehicle (PHEV) for robust frequency control in the two-area interconnected power system with wind farms. The controller structure is a proportional integral (PI). System uncertainties such as various wind patterns, system parameters variation etc., are modeled by the inverse output multiplicative perturbation. The particle swarm optimization is applied for tuning the PI parameters based on the mixed H2/H∞ control technique. Simulation results confirm the superior performance and robustness of the proposed controller.
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PSO based kernel principal component analysis and multi-class support vector machine for power quality problem classification
(2012-03-01)
Pahasa, Jonglak
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Ngamroo, Issarachai
Electric power quality (PQ) problems are very important aspects due to the increase in the number of loads which are sensitive to power disturbances. One of the important issues in the PQ problems is to detect and classify disturbance waveforms auto-matically in an efficient approach, because the possible solutions can be determined after the disturbance types are detected. This paper proposes a particle swarm optimization (PSO) based kernel principal component analysis (KPCA) and support vector machine (SVM) for PQ problem classification. Wavelet based multiresolution analysis (MRA) is utilized to extract features for various PQ disturbances. Dimension of these features are then reduced by KPCA so that the noise has less impact on the classification results. The multi-class SVM is used to classify the PQ problem using the dominant KPCA. The PSO is applied to optimize the KPCA and SVM parameters in order to improve the classification performance. The classification process implemented with various PQ events shows that the proposed technique provides more accuracy than the conventional technique under both noisy and noiseless environments. © 2012 ISSN 1349-4198.

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