• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1140-1145
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• 2011

This paper proposes a new loss minimization control method for the vector controlled induction motors. The aim of the proposed loss minimization method is how to determine the optimal flux reference to minimize the total loss of induction motor. Even though the proposed algorithm is based on the equivalent circuit of induction motor including iron loss and leakage inductance, the algorithm is easy to be found and simple to be implemented. Futhermore, the proposed loss minimization algorithm can be applied easily to the traditional vector control system without any additional hardware. Simulation and experimental results are given to validate the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1356-1357
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• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes on-line efficiency optimization of IPMSM drive using fuzzy logic control(FLC) and the loss minimization method. In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to IPMSM drive system and the operating characteristics controlled by the loss minimization method and FLC control are examined in detail.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.580-582
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• 2005

This paper presents a new method which applies a genetic algorithm(GA) for determining which sectionalizing switch to operate in order to solve the distribution system loss minimization re-configuration problem. The distribution system loss minimization re-configuration problem is in essence a 0-1 planning problem which means that for typical system scales the number of combinations requiring searches becomes extremely large. In order to deal with this problem, a new a roach which applies a GA was presented. Briefly, GA are a type of random number search method, however, they incorporate a multi-point search feature. Further, every point is not is not separately and respectively renewed, therefore, if parallel processing is applied, we can expect a fast solution algorithm to result.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.40-43
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• 2005

This paper presents the minimization of the fuel cost by optimal allocation of P-Q generation in a three-bus sample system. Derivation of the system loss sensitivities by optimization technique is introduced. The loss sensitivities are substituted into the optimality conditions and the optimal P-Q allocation is computed to obtain the minimal fuel cost.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.1
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• pp.28-37
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• 2001

This paper presents an efficient algorithm for the loss minimization of distribution system by automatic sectionalizing switch operation in large scale distribution systems. Simulated annealing is particularly well suited for large combinational optimization problem, but the use of this algorithm is also responsible for an excessive computation time requirement. Tabu search attempts to determine a better solution in the manner of a greatest-descent algorithm, but it can not give any guarantee for the convergence property. The hybrid algorithm of two methods with two tabu lists and the proposed perturbation mechanism is applied to improve the computation time and convergence property Numerical examples demonstrate the validity and effectiveness of the proposed methodology using a KEPCO's distribution system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.188-196
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• 2001

This paper presents and efficient algorithm for the loss minimization by automatic sectionalizing switch operation in distribution systems. Ant colony algorithm is multi-agent system in which the behaviour of each single agent, called artificial ant, is inspired by the behaviour of real ants. Ant colony algorithm is suitable for combinatiorial optimization problem as network reconfiguration because it use the long term memory, called pheromone, and heuristic information with the property of the problem. The proposed methodology with some adoptions have been applied to improve the computation time and convergence property. Numerical examples demonstrate the validity and effectiveness of the proposed methodology using a KEPCO's distribution system.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.289-290
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• 2003

This paper gives a method for the minimization of the fuel cost by optimal generation. Derivation of the sensitivity of system loss by optimization technique is introduced and the loss sensitivities are substituted into the optimality conditions to obtain the minimized fuel cost.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.7
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• pp.380-388
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• 2006

In this paper, a novel control algorithm to minimize the power loss of the induction generator for wind power generation system is presented. The proposed method is based on the flux level reduction, where the flux level is computed from the machine model for the optimum d-axis current of the generator. For the vector-controlled induction generator, the d-axis current controls the excitation level in order to minimize the generator loss while the q-axis current controls the generator torque, by which the speed of the induction generator is controlled according to the variation of the wind speed in order to produce the maximum output power. Wind turbine simulator has been implemented in laboratory to validate the theoretical development. The experimental results show that the loss minimization process is more effective at low wind speed and that the percent of power loss saving can approach to 25%. Experimental results are shown to verify the validity of the proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.492-498
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• 2009

The placement of the UPFC is the major concern to ensure the full potential of utilization in the transmission network. Voltage stability enhancement with the optimal placement of UPFC using stability index such as modal analysis, Voltage Phasor method is made and the loss minimization including UPFC is formulated as an optimization problem. This paper proposes particle swarm optimization for the exact real power loss minimization including UPFC. The implementation of loss minimization for the optimal location of UPFC was tested with IEEE-14 and IEEE-57 bus system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.80-87
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• 2003

Network reconfiguration in distribution systems is realized by changing the status of sectiona1izing switches, and is usually done for loss minimization or load balancing in the system This parer presents an approach for loss minization in distribution systems using reactive tabu search. Tabu search attempts to determine a better solution in the manner of a greatest-descent algorithm, but it can not give any guarantee for the convergence property. Reactive tabu search can give convergence property by using reaction and escape mechanism. Therefore, it can find global optimal solution regardless of initial system configuration. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the 32 bus system models.