• Journal of Electrical Engineering and Technology
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• 제8권4호
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• pp.737-743
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• 2013

The small-scaled onsite generators such as photovoltaic power, wind power, biomass and fuel cell belong to decarbonization techniques. In general, these generators tend to be connected to utility systems, and they are called distributed generations (DGs) compared with conventional centralized power plants. However, DGs may impact on stabilization of utility systems, which gets utility into trouble. In order to reduce utility's burdens (e.g., investment for facilities reinforcement) and accelerate DG introduction, the advanced operation algorithms under the existing utility systems are urgently needed. This paper presents the advanced voltage regulation method in power systems since the sending voltage of voltage regulators has been played a decisive role restricting maximum installable DG capacity (MaxC_DG). For the proposed voltage regulation method, the difference from existing voltage regulation method is explained and the detailed concept is introduced in this paper. MaxC_DG estimation through case studies based on Korean model network verifies the superiority of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.537-539
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• 1999

본 연구에서는 UCA와 필드버스를 이용한 전력 설비 통합 자동화통신망 구축 방안을 제시한다. 이를 위하여 (i) UCA와 필드버스의 프로토콜간 인터페이스 작업 최소화와 (ii) 게이트웨이 내에서의 연산작업 최소화의 요구사항을 만족하는 UCA-필드버스 게이트웨이 구성 방안을 제시하고, 게이트웨이 내에서 UCA와 필드버스의 프로토콜 매핑 방법을 기술한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.197-198
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• 2008

In this paper, we study an opportunistic scheduling scheme for the OFDMA system with streaming services. The service is modeled by using the appropriate utility function. We formulate a stochastic optimization problem that aims at maximizing network utility while satisfying the QoS requirement of each user. The problem is solved by using the dual approach and the stochastic sub-gradient algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.39-42
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• 1991

The Application of Artificial Neural Network(ANN) to forecast a load in a power system is investigated. The load forecasting is important in the electric utility industry. This technique, methodology based on the fact that parallel structure can process very fast much information is a promising approach to a load forecasting. ANN that is highly interconnected processing element in a hierachy activated by the each input. The load pattern can be divided distinctively into two patterns, that is, weekday and weekend. ANN is composed of a input layer, several hidden layers, and a output layer and the past data is used to activate input layer. The output of ANN is the load forecast for a given day. The result of this simulation can be used as a reference to a electric utility operation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.141-146
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• 2007

A gear whine sound due to the axle system is one of the most important sound qualities in a sport utility vehicle (SUV). In the previous research about the gear whine sound, it was known that it is difficult to evaluate the gear whine sound objectively by using the only A-weighted sound pressure level because of the masking effect. In this paper, for the objective evaluation of the axle-gear whine sound, the characteristics of the axle-gear whine sound is at the first investigated based on the synthetic sound technology and the new objective evaluation method for the axle-gear whine sound is developed by using the sound metrics, which is the psychoacoustics parameters, and the artificial neural network (ANN) used for the modeling of the correlation between objective evaluation and subjective evaluation.

• 한국멀티미디어학회논문지
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• 제10권6호
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• pp.745-753
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• 2007

The wireless medium is known to be time-varying which could affect and result to a poor network's performance. As a solution, an opportunistic scheduling and power control algorithm based on IEEE 802.11 MAC protocol is proposed in this paper. The algorithm opportunistically exploits the channel condition for better network performance. Convex optimization problems were also formulated i.e. the overall transmission power of the system is minimized and the "net-utility" of he system is maximized. We have proven that an optimal transmission power vector may exist, satisfying the maximum power and SINR constraints at all receivers, thereby minimizing overall transmission power and maximizing net-utility of the system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.233-235
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• 2001

This paper deals with frequency control of demand users that have power plants by under-frequency relay. The demand users supply electrical power to a part of their loads by their power plants and to other rest of their loads by utility. While electrical power supply is stopped by faults of utility network, the system of demand users network is separated from total power system and their system frequency goes below normal limits. In this paper, this situation and the effect of under-frequency relay application are simulated by EMTDC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2281-2301
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• 2014

In wireless ad hoc networks the nodes focus on achieving the maximum SINR for efficient data transmission. In order to achieve maximum SINR the nodes culminate in exhausting the battery power for successful transmissions. This in turn affects the successful transmission of the other nodes as the maximum transmission power opted by each node serves as a source of interference for the other nodes in the network. This paper models the choice of power for each node as a non cooperative game where the throughput of the network with respect to the consumption of power is formulated as a utility function. We propose an adaptive pricing scheme that encourages the nodes to use minimum transmission power to achieve target SINR at the Nash equilibrium and improve their net utility in multiuser scenario.

• Journal of Communications and Networks
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• 제18권4호
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• pp.589-599
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• 2016

Most existing resource management problem models arise from the original desire of allocating resources in either a user-centric or network-centric manner. The difference between their objectives is obvious: user-centric methods attempt to optimize the utility of individual users, whereas network-centric models intend to optimize the collective utilities of the entire network. In this paper, from the above two aspects, we analyze the robust power control problem in device-to-device (D2D) communication underlaying cellular networks, where two types of channel uncertainty set (e.g., ellipsoidal and column-wise) are considered. In the user-centric method, we formulate the problem into the form of a Stackelberg game, where the energy efficiency (EE) of each user is the ingredient of utility function. In order to protect the cellular user equipment's (CUE) uplink transmission, we introduce a price based cost function into the objectives of D2D user equipment (DUE). The existence and uniqueness of the game with the influence of channel uncertainty and price are discussed. In the network-centric method, we aim to maximize the collective EE of CUEs and DUEs. We show that by the appropriate mathematical transformation, the network-centric D2D power control problem has the identical local solution to that of a special case of the user-centric problem, where price plays a key role. Numerical results show the performance of the robust power control algorithms in the user-centric and network-centric models.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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• pp.360-362
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• 1998

In the original mixtures of experts framework, the parameters of the network are determined by gradient descent, which is naturally slow. In [2], the Expectation-Maximization(EM) algorithm is used instead, to obtain the network parameters, resulting in substantially reduced training times. This paper presents the new EM algorithm for prediction. We show that an Efficient training algorithm may be derived for the HME network. To verify the utility of the algorithm we look at specific examples in time series prediction. The application of the new EM algorithm to time series prediction has been quiet successful.