• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.348-350
• /
• 2003

본 논문에서는 태양광-풍력 복합발전시스템의 발전용량 예측을 통한 시스템 시설투자비 및 발전단가와 경제성에 대하여 분석한다. 도시지역의 일사량 및 풍속 데이터를 기초로 하여 복합발전시스템의 일일 발전량을 구하고, 수용가의 일일부하패턴과 수요부하를 고려하여 태양전지 어레이와 풍력발전기의 용량을 산정한다. 그리고 용량 산정에 따른 복합발전시스템의 초기투자비용과 연간 발전량, 연간 소요경비 등의 요소를 고려하여 총 수명가 분석법(Total Life-Cycle Cost Analysis)에 기초한 발전단가를 계산하고 잉여전력을 계통에 판매할 경우의 경제성을 평가한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.942-945
• /
• 2010

The development of decentralized power has appeared as part of an effort to decrease the energy loss and the cost for electric power facilities through installing small renewable energy generation systems including solar and wind power generation. Recently a new era for decentralized power environment in building is coming in order to handle the climatic and environmental change occurred all over the world. Especially solar and wind power generation systems can be easily set up and are also economically feasible, and thus many industrial companies enter into this business. This paper suggests the overall architecture for the decentralized renewable power system and the prediction method of power on climatic change. The ultimate goal is to help manage the overall power efficiently and thus provide the technological basis for achieving zero-energy house.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.2
• /
• pp.121-141
• /
• 2017

The thermal analysis of an underground power conduit for electrical cables is essential to determine their current capacity with an increasing number of demands for high-voltage underground cables. The temperature rises around a buried cable, caused by excessive heat dissipation, may increase considerably the thermal resistance of the cables, leading to the danger of "thermal runaway" or damaging to insulators. It is a key design factor to develop the mechanism on thermal behavior of backfilling materials for underground power conduits. With a full-scale field test, a numerical model was developed to estimate the temperature change as well as the thermal resistance existing between an underground power conduit and backfill materials. In comparison with the field test, the numerical model for analyzing thermal behavior depending on density, moisture content and soil constituents is verified by the one-year-long field measurement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.782-785
• /
• 2011

Needs for MG(Microgrid) development are increasing all over the world as a solution to the problems including the depletion problem of energy resources, the growing demand for electric power and the climatic and environmental change. Especially Photovoltaic power is one of the most general renewable energy resources. However there is a problem of the uniformity of power quality because the power generated from solar light is very sensitive to climate fluctuation (variation of insolation and duration of sunshine, etc). As a solution to the above problem, ESS(Energy Storage System) is considered generally, but it has some limitations. To solve this problem this paper suggests a hybrid estimation method of photovoltaic power generation according to two climatic factors, i.e. insolation and sunshine. This result seems to help design the appropriate capacity of ESS and estimate the proper switching time between DC and AC power in the premises power system and thus maintain the uniformity of power quality.

• The KIPS Transactions:PartD
• /
• v.17D no.3
• /
• pp.185-192
• /
• 2010

In sensor network environments, each sensor measures the physical environments according to the sampling period, and transmits a sensor reading to the base station. Thus, the sample period influences against importance resources such as a network bandwidth, and a battery power. In this paper, we propose new adaptive sampling technique that adjusts the sampling period of a sensor with respect to the features of sensor readings. The proposed technique predicts a future readings based on KF (Kalman Filter). By using the differences of actual readings and estimated reading, we identify the importance of sensor readings, and then, we adjust the sampling period according to the importance. In our experiments, we demonstrate the effectiveness of our technique.

• KEPCO Journal on Electric Power and Energy
• /
• v.2 no.3
• /
• pp.391-395
• /
• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.654-655
• /
• 2011

운영예비력은 전력설비의 불시사고, 예상치 못한 전력수요 증가 등의 불확실 상황에 대비하기 위해 운영된다. 발전설비의 경제적 효율 및 부하분포에 따라 운영예비력이 지역별로 불균형하게 분포되면 특정 지역의 사고에 대해 신속히 대응하지 못할 수 있다. 특히, 전력수급의 상당부분을 타 지역에서의 송전에 의존하는 지역의 경우, 연계송전 선로 및 지역 내 발전설비 사고에 대비해 지역 내 충분한 운전예비력이 확보되어야 설비사고의 확대를 방지할 수 있다. 본 논문에서는 전력의 상당량을 외부로부터 수전하는 지역의 신속한 사고대응을 위한 지역 내운전예비력의 적정성 평가 방안을 제시하였다. 제시 방법에는 외부 연계선 및 발전설비의 사고 확률모델 및 수요예측 오차를 고려하여 지역 내운전예비력의 적정성을 평가할 수 있는 부하차단확률 지표를 제시하였다.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.19 no.1
• /
• pp.29-39
• /
• 2017

In this research, thermal design data such as heat transfer coefficient on the wall surface required for ventilation system design which is to prevent the temperature rise in the underground utility tunnel that three sides are adjoined with the ground was investigated in numerical analalysis. The numerical model has been devised including the tunnel lining of the underground utility tunnel in order to take account for the heat transfer in the tunnel walls. The air temperature in the tunnel, wall temperature, and the heating value through the wall based on heating value(117~468 kW/km) of the power cable installed in the tunnel and the wind speed in the tunnel(0.5~4.0 m/s) were calculated by CFD simulation. In addition, the wall heat transfer coefficient was computed from the results analysis, and the limit distance used to keep the air temperature in the tunnel stable was examined through the research. The convective heat transfer coefficient at the wall surface shows unstable pattern at the inlet area. However, it converges to a constant value beyond approximately 100 meter. The tunnel wall heat transfer coefficient is $3.1{\sim}9.16W/m^2^{\circ}C$ depending on the wind speed, and following is the dimensionless number:$Nu=1.081Re^{0.4927}({\mu}/{\mu}_w)^{0.14}$. This study has suggested the prediction model of temperature in the tunnel based on the thermal resistance analysis technique, and it is appraised that deviation can be used in the range of 3% estimation.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.5
• /
• pp.412-417
• /
• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of Energy Engineering
• /
• v.25 no.3
• /
• pp.136-148
• /
• 2016

We analyze economic effects of GHG reduction measures of the generation industry to meet 2030 GHG reduction target using the scenario based approach. We estimate the GHG emission of the Korean power industry in 2030 based on both the $7^{th}$ Electricity Supply & Demand Plan and the GHG emission coefficients issued by IAEA. We set up three scenarios for reduction measures by replacing the coal fired plants with nuclear power, renewable energy and carbon capture and storage. Once and for all, the nuclear power scenario dominates the other energy technologies in terms of GHG reduction quantities and economic effects.