• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.344-346
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• 2006

In this paper, a novel algorithm for increasing the steady state efficiency during light load operation of the induction generator that integrated with a wind power generation system is presented. The proposed algorithm based on the flux level reduction, where the flux level is estimated using Support-Vector -Machines for regression (SVR) for the optimum d-axis current of the generator. SVR is trained off-line to estimate the unknown mapping between the system's inputs and outputs, and then is used online to calculate the optimum d-axis current for minimizing generator loss. The experimental results show that SVR can define the flux-power loss accurately and determine the optimum d-axis current value precisely. The loss minimization process is more effective at low wind speed and the percent of power saving can approach to 40%.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.320-326
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• 2002

Distribution system loss minimization re-configuration is 0-1 planning problem, and the number of combinations requiring searches is extremely large when dealing with typical system scales. For this reason, the application of a genetic algorithm (GA) seems attactive to solve this problem. Although Genetic algorithms are a type of random number search method, they incorporate a multi-point search feature and are therefore superior to one-point search techniques. The efficiency of GAs for solving large combinational problem has received wide attention. Further, parallel searching can be performed and the optimal solution is more easily reached. In this paper, for improving GA convergence characteristics in the distribution system loss minimization re-configeration problem, a chromosome "Limited Life" concept is intro duced. Briefly, considering the population homogenization and genetic drift problems, natural selection is achieved by providing this new concept, in addition to natural selection by fitness. This is possible because individuals in a population have an age value. Simulations were carried out using a model system to check this method's validity.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.6-9
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• 2001

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 approach 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.

• 대한전기학회논문지:전력기술부문A
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• 제53권5호
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• pp.266-274
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• 2004

This paper presents a scheme for the interconnection of dispersed generator systems(DGs) based on load .unbalance and load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The unbalance is involved with many single-phase line segment. . Voltage profile improvement and system loss minimization by installation of DGs depend greatly on how they are placed and operated in the distribution systems. So, DGs can reduce distribution real power losses and replace large-scale generators if they are placed appropriately in the distribution systems. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 13 bus and 34 bus test systems to demonstrate its effectiveness.

• 조명전기설비학회논문지
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• 제15권3호
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• pp.35-44
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• 2001

본 논문에서는 배전 계통에서 여러 가지 제약조건을 만족하면서 최소 손실 구성을 찾는 문제에 루프 기반의 유전자 알고리즘을 적용하였다. 전역적인 탐색 능력이 뛰어난 유전자 알고리즘이 아크를 기반으로 하여 배전 계통 재구성 문제에 적용되었지만 비가능해가 많이 발생하여 탐색의 효율성이 떨어졌다. 본 논문에서는 루프를 기반으로 스트링을 구성하여 가능해가 될 확률을 높였고 비가능해를 가능해로 쉽게 전환할 수 있는 복구함수를 적용해 기존의 유전자 알고리즘에서 갖고 있던 단점을 극복하였다. 본 논문에서 제안한 루프 기반의 유전자 알고리즘은 32, 69 모선 시스템에서 기존의 아크 기반의 유전자 알고리즘과 비교하여 좋은 결과를 보임으로써 실제 크기의 배전 계통에 충분히 적용할 수 있을 것으로 생각된다.

• Journal of Power Electronics
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• 제9권6호
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• pp.940-948
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• 2009

The main objective of this a paper is to improve the efficiency of permanent magnet synchronous motors (PMSMs) by using an improved direct torque control (DTC) strategy. The basic idea behind the proposed strategy is to predict the impact of a small change in the stator flux amplitude at each sampling period to decrease electrical loss before the change is applied. Accordingly, at every sampling time, a voltage vector is predicted and applied to the machine to fulfill the flux change. The motor drive simulations confirm a significant improvement in efficiency as well as a very fast and smooth response under the proposed strategy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1459-1461
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• 1999

Distribution systems is consist of network in physical aspect, and radial in electrical aspect. Therefore, radial operation is realized by changing the status of sectionalizing switches, and is usually done for loss reduction in the system. In this paper, we propose a optimal method for distribution systems reconfiguration. Specifically, we use K-optimal algorithm and tabu search method to solve distribution systems reconfiguration for loss minimization problem.

• Journal of Power Electronics
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• 제8권4호
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• pp.345-353
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• 2008

In this paper, a novel loss minimization of an induction generator in wind energy generation systems is presented. The proposed algorithm is based on the flux level reduction, for which the generator d-axis current reference is estimated using support vector regression (SVR). Wind speed is employed as an input of the SVR and the samples of the generator d-axis current reference are used as output to train the SVR algorithm off-line. Data samples for wind speed and d-axis current are collected for the training process, which plots a relation of input and output. The predicted off-line function and the instantaneous wind speed are then used to determine the d-axis current reference. It is shown that the effect of loss minimization is more significant at low wind speed and the loss reduction is about to 40% at 4[m/s] wind speed. The validity of the proposed scheme has been verified by experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.330-332
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• 2001

Distribution systems is consist of network in physical and radial in electrical aspect. Therefore radial operation is realized by changing the status of sectionalizing switches, and is usually done for loss reduction in the system. In this paper, we propose a optimal method for distribution systems reconfiguration. Specifically we use genetic algorithm method to solve distribution systems reconfiguration for loss minimization problem. A genetic algorithm(GA) is set up, in which some improvements are made on string coding, fitness function and mutation pattern. As a result, premature convergence is avoided.

• Journal of Power Electronics
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• 제14권2호
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• pp.351-361
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• 2014

The discrete torque generation mechanism and inherently nonlinear magnetic characterization of switched reluctance motors lead to unacceptable torque ripples and limit the application of these motors. In this study, a phase current profiling technique and torque sharing function are proposed in consideration of magnetic saturation effects and by minimizing power loss in the commutation area between the adjacent phases. Constant torque trajectories are considered in incoming and outgoing phase current planes based on nonlinear T-i-theta curves obtained from experimental measurements. Optimum points on constant torque trajectories are selected by improving drive efficiency and minimizing copper loss in each rotor position. A novel analytic invertible function is introduced to express phase torque based on rotor position and its corresponding phase current. The optimization problem is solved by the proposed torque function, and optimum torque sharing functions are derived. A modification method is also introduced to enhance the torque ripple-free region based on simple logic rules. Compared with conventional torque sharing functions, the resultant reference current from the proposed method has less peak and effective values and exhibits lower copper loss. Experimental and simulation results from a four-phase 4 KW 8/6 SRM validate the effectiveness of the proposed method.