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Wide-area damping control using signal restoration under communication uncertainties
(2020-06-01)
Ngamroo, Issarachai
In large-scale power systems, the wide-area damping controller (WADC) using remote input signals is an effective device that can be applied to deal with poor inter-area oscillation damping. However, its control effect will be degraded by communication uncertainties such as variable time delays in both input and output sides of WADC, partial and complete communication failures. This paper focuses on a new WADC design by regarding communication uncertainties. Such uncertainties are mathematically formulated and analyzed in order to signify its impact on the oscillatory stability. The signal restoration of input and output pairs of WADC is proposed to alleviate an adverse effect of communication uncertainties. Simulation study in an IEEE 50-machine 145-bus test system elucidates that the proposed WADC is superior to that of the conventional WADC without considering communication uncertainties in both performance and robustness.
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Two-level inter-area oscillation dampers design by monte carlo simulation
(2019-01-01)
Ngamroo, Issarachai
Various system operations such as load changes, time delays, communication failure, and line outages have an influence on the stabilizing effect of inter-area damping controllers. Moreover, the penetration of large wind farms makes power oscillations problem more complicated. This paper proposes the two-level control design of power system stabilizers and power oscillation dampers of wind turbines with doubly fed induction generator by Monte Carlo simulation (MCS) and probability. In the twolevel damping control, the centralized damper acts as the main control while the local damper works as the backup control when the communication failure occurs. Using the MCS to produce random operating points, the parameters tuning of centralized and local dampers is independently performed by the particle swarm optimization so that the probability of expected damping ratio is maximized. Study results in the modified IEEE New England 39 bus system guarantee the damping effect and robustness of the proposed control.
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Robust power oscillation damper design for DFIG-based wind turbine based on specified structure mixed H2/H∞ control
(2014-01-01)
Surinkaew, Tossaporn
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Ngamroo, Issarachai
As the integration of a doubly fed induction generator (DFIG)-based wind power generation into power systems tends to increase significantly, the contribution of DFIG wind turbine is highly expected. Since the active and reactive power outputs of DFIG can be independently modulated, the stabilizing effect of DFIG on the inter-area power system oscillation is a challenging issue. This paper proposes a new robust control design of power oscillation damper (POD) for a DFIG-based wind turbine using a specified structure mixed H<inf>2</inf>/H<inf>∞</inf> control. The POD structure is a practical 2nd-order lead-lag compensator with single input. Normally, H<inf>∞</inf> control mainly enforces the closed-loop stability while noise attenuation or regulation against random disturbances is expressed in H<inf>2</inf> control. As a result, the mixed H<inf>2</inf>/H<inf>∞</inf> control gives a powerful multi-objective control design so that both closed-loop stability and performance of designed controller can be guaranteed. Here, the linear matrix inequality is applied to formulate the optimization problem of POD based on a mixed H<inf>2</inf>/H<inf>∞</inf> control. The POD parameters are optimized so that the performance and robustness of the POD against system disturbances and uncertainties are maximal. The firefly algorithm is automatically applied to solve the optimization problem. Simulation study in a two-area four-machine interconnected power system shows that the DFIG with robust POD is superior to conventional POD in terms of stabilizing effect as well as robustness against various power generating and loading conditions, unpredictable network structure, and random wind patterns. © 2013.
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PSO based decentralized robust power system stabilizer for a multi-machine power system
(2012-06-12)
Kaitwanidvilai, Somyot
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Ussawapusitgul, Chanchai
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Limcharoen, Worrakan
This paper presents a new technique to design a robust Power System Stabilizer (PSS) in multi-machine power system. The Particle Swarm Optimization (PSO) is adopted to find the optimal parameters of the predefined structure decentralized controller. The main objectives of this research are to reduce the oscillation and to increase the overall robust performance of the system. The proposed technique adopts the stability margin (ε) as the index of robustness and performance of the controlled system. In addition, the optimal weight selection, which is a difficult process of the robust loop shaping design, can be achieved by the proposed technique. In this paper, the performance of the proposed controller is investigated in the standard IEEE four generators system in comparison with the classical robust loop shaping control. The results of rotor speed deviation of generators by the proposed PSS and the conventional PSS verify the effectiveness of the proposed algorithm.
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PMU-based system identification for wide area robust PSS design in interconnected power systems with wind farm
(2012-01-01)
Ngamroo, Issarachai
It is well known that the penetration of wind power in the smart power grids not only causes the power fluctuation problem, but also results in the system instability. To tackle this problem, a sophisticated design of robust power system stabilizer (PSS) based on system identification using multiple synchronized phasor measurement units (PMUs) is proposed. The small load fluctuation is applied to the system in order to generate the phasor data measured from multiple PMUs which are assumed to be located in the system. Applying the least square method, the phasor data are used to identify the coupled vibration model (CVM) which represents the dominant inter-area oscillation modes. The CVM is used to design the PSS which is a 2nd-order lead-lag compensator. To take system uncertainties such as variation of system parameters etc., in the CVM, the inverse additive perturbation model is applied. Based on an enhancement of the robust stability margin and damping effect, the PSS parameters optimization problem is formulated. The genetic algorithm is used to solve the problem and achieve the PSS parameters. The performance and robustness of the proposed PSS are evaluated in the IEEJ Western Japan 10 machine power system with wind farm in comparison with a conventional PSS. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.
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A heuristic training-based least squares support vector machines for power system stabilization by SMES
(2011-10-01)
Pahasa, Jonglak
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Ngamroo, Issarachai
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.
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Least squares support vector machine for power system stabilizer design using wide area phasor measurements
(2011-07-01)
Pahasa, Jonglak
;
Ngamroo, Issarachai
This paper proposes a design method of power system stabilizer by a least squares support vector machine (LS-SVMPSS) for wide area stability control. Both local and inter-area data based on synchronized phasor measurements considering time delay are considered as the input features of the LS-SVMPSS. A large number of the training data sets of a multi-machine power system are reduced by the measurement of similarity between samples. Removing the redundant data in the training set not only improves the LS-SVMPSS performance but also decreases computation expense during the operation of LS-SVMPSS. The LS-SVMPSS parameters and the similarity threshold are optimized by a genetic algorithm. As a result, the redundant data in the training set can be discarded while the reduced data are the optimal support vectors in the LS-SVMPSS model. The LS-SVMPSS control signals can be adapted in real time by various operating conditions and different disturbances. The performance of the LS-SVMPSS is compared with the conventional PSS and the neural network-based PSS. Simulation results in a two-area four-machine power system demonstrate that the proposed LS-SVMPSS is very robust to various disturbances under wide range of operating conditions in comparison to other PSSs. © 2011 ISSN.
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A robust centralized SMES controller design based on WAMS considering system and communication delay uncertainties
(2011-04-01)
Saejia, Mongkol
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Ngamroo, Issarachai
It is well known that the communication delay due to the phasor measurement in wide area monitoring system (WAMS) as well as various system operating conditions such as heavy line flows and unpredictable network structures, may deteriorate the wide-area stabilizing control effect. To overcome this problem, the inverse input and output multiplicative model is proposed to represent unstructured uncertainties due to system operations and communication delay in the robust centralized damping controller design of superconducting magnetic energy storage (SMES) based on WAMS. The structure of centralized controller for SMES is the practical 1st-order lead/lag compensator. To automatically tune the control parameters, the optimization problem based on the enhancement of damping performance and system robust stability margin is achieved by particle swarm optimization. Simulation studies in the West Japan six-area interconnected system confirm that the proposed robust SMES centralized controller is superior to the conventional SMES centralized controller in terms of damping performance and robustness against system and time delay uncertainties. © 2010 Elsevier B.V.
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GA-based support vector machines for adaptive power system damping controller of SMES
(2010-07-30)
Pahasa, Jonglak
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Ngamroo, Issarachai
This paper proposes the application of support vector machines (SVMs) to design of an adaptive power system damping controller for superconducting magnetic energy storage (SMES). A genetic algorithm is used to optimize the SVM parameters based on k-fold cross-validation. The SVMs for SMES controllers are trained by the data obtained from a multi-machine power system, and the optimal SVM parameters. The SVMs can be adapted by various operating conditions when the power system operates either inside or outside of the training set. Simulation results in a two-area four-machine power system demonstrate that the proposed SVMs for adaptive SMES is much superior to the conventional SMES controller with fixed parameters under various operating conditions and severe disturbances.
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Dynamic event analysis using synchronized PMUs via 220 V wall outlets
(2007-12-01)
Ngamroo, Issarachai
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Lappanakul, Panlert
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Voraphonpiput, Nitus
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Dechanupaprittha, Sanchai
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Mitani, Yasunori
This paper presents the dynamic analysis results of a system event in Thailand power network using a wide-area monitoring system based on synchronized phasor measurement units (PMUs). The salient feature of the proposed monitoring system is the convenient installation of PMU at 220V wall power outlets. The event considering here is a 80 MW load transferring from Thailand to Malaysia systems through a weak 115 kV tieline. To perform load transferring, a synchronization between both systems is required. This causes a problem of frequency oscillation in a southern area of Thailand. Besides, this event severely excites the inter-area oscillation in a 230 kV tie-line between central and southern areas of Thailand. Analyzed results based on discrete wavelet decomposition and short-time Fourier Transform provide valuable information of the system dynamic behavior in both frequency and time domains. © 2007 RPS.

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