• 한국통신학회논문지
• /
• 제33권7A호
• /
• pp.757-767
• /
• 2008

차세대 이동 통신망의 발전으로 상용 망과 이 기종 망이 서로 겹쳐진 다중 망 구조가 형성될 것이다. 이러한 여러 망이 겹쳐진 다중 망 구조에서 전체 무선자원의 사용 효율을 높이고 Eb/Io (bit energy-to-interference plus noise density ratio)를 개선하기 위해 이기종망간 혹은 동종망간 상호 연동 기술이 필요하다. 본 논문에서는 이러한 동종망과 이기종망들이 서로 겹쳐져 있는 다중 셀 환경에서 load를 효율적으로 분산시킴으로써 무선 자원의 효율을 높이고 신호의 간섭양을 줄여 사용자의 QoS 보장 및 성능 개선을 위한 soft load balancing algorithm을 제안 및 분석한다. 본 논문에서는 수학적 분석을 통해 효율적인 load sharing을 위한 최적의 LBR (load balancing ratio) 을 구하고 이를 이용하여 각 network에 traffic 양을 할당하여 서비스한다. 그러므로 soft load balancing 알고리듬은 보다 안정적인 데이터 전송을 가능하게 한다.

• 산업기술연구
• /
• 제18권
• /
• pp.379-384
• /
• 1998

Conventional short-term load forecasting techniques have limitation in their use on holidays due to dissimilar load behaviors of holidays and insufficiency of pattern data. Thus, a new short-term load forecasting method for special days in anomalous load conditions is proposed in this paper. The proposed method uses two Artificial Neural Networks(ANN); one is for the estimation of load curve, and the other is for the estimation of minimum and maximum value of load. The forecasting procedure is as follows. First, the normalized load curve is estimated by ANN. At next step, minimum and maximum values of load in a special day are estimated by another ANN. Finally, the estimate of load in a whole special day is obtained by combining these two outputs of ANNs. The proposed method shows a good performance, and it may be effectively applied to the practical situations.

• 대한전기학회논문지:전력기술부문A
• /
• 제53권8호
• /
• pp.466-471
• /
• 2004

Electricity industries throughout the world are undergoing unprecedented changes. As a result, these changes lead to the separation of traditional integrated utilities and the introduction of competition in order that increase efficiency in electricity industry. Direct load control (DLC) system in competitive electricity market has a hierarchical interactive operation system, therefore, its control logic is also applied by bilateral interactive method that interchanges information related to interruptible load between operation hierarchies. Consequently, load curtailment allocation algorithm appropriate for new DLC system is required, and based on interchanged information, this algorithm should be implemented by most efficient way for each operation hierarchy. In this paper, we develop the load curtailment allocation algorithm in an emergency for new DLC system. Especially, the optimal algorithm for load aggregator (LA) that participates in competitive electricity market as a main operator for load management is developed.

• 대한전기학회논문지:전력기술부문A
• /
• 제50권1호
• /
• pp.20-27
• /
• 2001

In this paper, we propose a method for estimating the peak load of pole-transformer in summer season considering the degree of cooling load possession in customer. The cooling load of customer is selected as the most reliable parameter of peak load in summer season. The proposed estimation method is restricted to the aspect of load management for pole-transformer. The main concept of proposed method is that the error of peak load estimation using load regression equation reduces with considering the degree of cooling load possession in customer. We propose an index for estimation of cooling load possession in each customer. The proposed index is defined as cooling load possession in customer (CLPC) and obtained from the increment of monthly electric energy. The membership function for deciding the uncertainty of cooling load possession in customer is used. The database of pole-transformer in Korea Electric Power Corporation (KEPCO) is used for case studies. Through the case studies, we verify that the proposed method reduces the error of peak load estimation than the conventional method in domestic.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
• /
• pp.562-564
• /
• 2002

Noise reduction and a simplification of a precision measurement system has been performed by changing analog output mode of a load cell into digital output mode. Usually, analog output signal of a few $\mu V$ from a load cell are amplified by amp and acquired by A/D converter. If the distance from a load cell to a DAS(Data Acquisition System) increases, more noise signals are mixed. So, a microprocessor has been integrated into a load cell so that the amplification and A/D conversion of output signals could be done in close proximity to the lode cell for the reduction in mixing of noise. Obtained data from the load cell like this manner are transferred to a computer with digital values(of TTL level). To simplify the configuration of a multi-channel DAS, RS-485 communication system has used for data transfer.

• Journal of Electrical Engineering and Technology
• /
• 제7권6호
• /
• pp.845-851
• /
• 2012

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

• KEPCO Journal on Electric Power and Energy
• /
• 제7권1호
• /
• pp.115-123
• /
• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• The Journal of Korean Physical Therapy
• /
• 제21권2호
• /
• pp.97-101
• /
• 2009

Purpose: This study examined how the direction of carrying a load affects the foot stability and kinesiology while walking. Methods: The heel rotation, Hallux stiffness, foot balance, metatarsal load, toe out angle, subtalar joint flexibility were measured in 40 adults (men and women) who carried a load back and forth, walking on a 2-meter-long board. The measurement was carried out three times and the mean of the measurements was used to compare the difference between the front, back and the condition without a load. Results: While walking, heel rotation and hallux stiffness occurred most when a front load was applied compared to a back load or no load condition (p<0.05). A metatarsal load also appeared to be the highest with the frond load, but there was no significant difference in the balance of the whole foot. Both the toe out angle and subtalar joint flexibility appeared to increase significantly (p<0.05). Conclusion: Applying the front load causes subtalar joint instability and increases the plantar foot pressure imbalance during walking.

• 전기학회논문지
• /
• 제58권9호
• /
• pp.1700-1705
• /
• 2009

In general, short term load forecasting is based on the periodical load pattern during a day or a week. Therefore, the conventional methods do not expose stable performance to every day during a year. Especially for anomalous weather conditions such as typhoons, the methods have a tendency to show the conspicuous accuracy deterioration. Furthermore, the tendency raises the reliability and stability problems of the conventional load forecast. In this study, a new load forecasting method is proposed in order to increase the accuracy of the forecast result in case of anomalous weather conditions such as typhoons. For irregular weather conditions, the sensitivity between temperature and daily load is used to improve the accuracy of the load forecast. The proposed method was tested with the actual load profiles during 14 years, which shows that the suggested scheme considerably improves the accuracy of the load forecast results.

• 산업기술연구
• /
• 제15권
• /
• pp.187-193
• /
• 1995

In this paper, a short-term load forecasting expert system considering the load variation due to the change in temperature is presented. The change in temperature is an important load variation factor that varies the normal load pattern. The conventional load forecasting methods by artificial neural networks have used the technique where the temperature variables were included in the input neurons of artificial neural networks. However, simply adding the input units of temperature data may make the forecasting accuracy worse, since the accuracy of the load forecasting in this method depends on the accuracy of weather forecasting. In this paper, the fuzzy expert system that modifies the forecasted load using fuzzy rules representing the relations of load and temperature is presented and compared with a conventional load forecasting technique. In the test case of 1991, the proposed model provided a more accurate forecast than the conventional technique.