• Title/Summary/Keyword: Estimation of Energy

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Estimation of Cost of Energy for Offshore Wind Turbines (해상 풍력발전의 경제성 분석)

  • Chung, Taeyoung;Moon, Seokjun;Lee, Hanmin;Rim, Chaewhan
    • 한국신재생에너지학회:학술대회논문집
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    • 2010.11a
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    • pp.177.1-177.1
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    • 2010
  • Large offshore wind farms have actively been developed in order to meet the needs for wind energy since the land-based wind farms have almost been fully developed especially in Europe. The key problem for the construction of offshore wind farms may be on the high cost of energy compared to land-based ones. NREL (National Renewable Energy Laboratory) has developed a spreadsheet-based tool to estimate the cost of wind-generated electricity from both land-based and offshore wind turbines. Component formulas for various kinds and scales of wind turbines were made using available field data. Annual energy production has been estimated based on the Weibull probability distributions of wind. In this paper, this NREL estimation model is introduced and applied to the offshore wind turbines now under designing or in production in Korea, and the result is discussed.

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THE OPEN-CIRCUIT VOLTAGE STATE ESTIMATION OF THE BATTERY

  • LEE, SHINWON
    • Journal of applied mathematics & informatics
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    • v.39 no.5_6
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    • pp.805-811
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    • 2021
  • Currently, batteries use commonly as energy sources for mobile electric devices. Due to the high density of energy, the energy storage state of a battery is very important information. To know the battery's energy storage state, it is necessary to find out the open state voltage of the battery. The open state voltage calculates with a mathematical model, but the computation of the real time state is complicated and requires many calculations. Therefore, the state observer designs to estimate in real time the battery open-circuit voltage as disturbance including model error. Using the estimated open voltage and applying it to the state estimation algorithm, we can estimate the charge. In this study, we first estimate the open-circuit voltage and design an estimation algorithm for estimating the state of battery charge. This includes errors in the system model and has a robust characteristic to noise. It is possible to increase the precision of the charge state estimation.

A Study on the Method about the Economic Feasibility Estimation Considering Renewable Energy (신재생에너지원을 고려한 집단에너지 경제성평가 방법론에 관한 연구)

  • Shin, Hye-Kyeong;Choi, Young-Jun;Choi, In-Sun
    • 한국신재생에너지학회:학술대회논문집
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    • 2008.10a
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    • pp.372-374
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    • 2008
  • Korea classified into a development country when UNFCCC was concluded in 1995. So Korea doesn't have a GHG reduction duty until 2012. As the UNFCCC is strengthened, recently there is a growing interest in renewable energy and energy usage efficiency improvement for reducing GHG emission. It is associated with CES and renewable energy. CES is a total energy (heat, cooling and power)supplier in aggregated demand zone like a hotel, building, hospital and redevelopment district using CHP and it improves energy usage efficiency. At present, renewable energy is needed for GHG reduction duty but renewable energy doesn't have economic feasibility. So renewable energy is needed various support system to popularize which is a FIT and RPS. Especially RPS is carrying out instead of FIT in many advanced country and it will be inroduced in Korea. RPS is a duty which electricity service provider must guarantee renewable energy as much as specific ratio of total capacity. Therefore this study conducts an economic feasibility estimation of CES considering renewable energy when RPS will introduced in the future.

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Impact parameter prediction of a simulated metallic loose part using convolutional neural network

  • Moon, Seongin;Han, Seongjin;Kang, To;Han, Soonwoo;Kim, Kyungmo;Yu, Yongkyun;Eom, Joseph
    • Nuclear Engineering and Technology
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    • v.53 no.4
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    • pp.1199-1209
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    • 2021
  • The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

Control-Gain Estimation of Energy Dissipation Control Algorithms (에너지소산 제어 알고리듬의 제어이득 산정)

  • 이상현;민경원;강상훈
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.04a
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    • pp.431-438
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    • 2004
  • This study is on control-gain estimation of energy dissipation control algorithms. Velocity feedback, bang-bang, and energy dissipation control algorithms are proposed based on the Lyapunov stability theory and their performances are evaluated and compared. Saturation problem is considered in the design of the velocity feedback and energy dissipation control algorithms, and chattering problem in bang-bang control is solved by using boundary layer. Numerical results show that the proposed control algorithms can dissipate the structural energy induced by wind loads efficiently, and thus provide good control performance.

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Real-time Stability Assessment and Energy Margin Estimation using Fuzzy (퍼지를 이용한 실시간 안정도 판별과 에너지 마진의 추정)

  • Choi, Won-Chan;Kim, Soo-Nam;You, Seok-Ku
    • Proceedings of the KIEE Conference
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    • 1999.07c
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    • pp.1239-1241
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    • 1999
  • In this paper, we propose real time transient stability assessment and energy margin estimation using fuzzy approximate reasoning. The proposed method used rotor angle, kinetic energy and acceleration power of generators at clearing time as fuzzy input. In order to calculate energy margin in transient energy function (TEF), we obtained controlling unstable equilibrium point (UEP) using mode of disturbance procedure (MOD). The proposed algorithm is tested on 4-machine, 6-bus, 7-line power system to prove of effectiveness.

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The RTD Measurement on a Submerged Bio-Reactor using a Radioisotope Tracer and the RTD Analysis

  • Seungkwon Shin;Kim, Jongbum;Sunghee Jung;Joonha Jin
    • International Journal of Control, Automation, and Systems
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    • v.1 no.2
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    • pp.210-214
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    • 2003
  • This paper presents a residence time distribution (RTD) measurement method using a radioisotope tracer and the estimation method of RTD model parameters to analyze a submerged bio-reactor. The mathematical RTD models have been investigated to represent the flow behavior and the existence of stagnant regions in the reactor. Knowing the parameters of the RTD model is important for understanding the mixing characteristics of a reactor The radioisotope tracer experiment was carried out by injecting a radioisotope tracer as a pulse into the inlet of the reactor and recording the change of its concentration at the outlet of the reactor to obtain the experimental RTD response. The parameter estimation was performed by the Levenberg-Marquardt optimization algorithm. The proposed scheme allowed the parameter estimation of RTD model suggested by Adler-Hovorka with very low deviations. The estimation procedure is shown to lead to accurate estimation of the RTD parameters and to a good agreement between experimental and simulated response.

Evapotranspiration Estimation Study Based on Coupled Water-energy Balance Theory in River Basin

  • Xue, Lijun;Kim, JooCheol;Li, Hongyan;Jung, Kwansue
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.146-146
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    • 2018
  • Basin evapotranspiration is the result of water balance and energy balance, which is affected by climate and underlying surface characteristics, the process is complex, and spatial and temporal variability is large, the evapotranspiration estimation of river basin is an important but difficult problem in the field of hydrology, over the years, many scholars devoted to the basin actual evapotranspiration estimation and achieved excellent results. We discuss Budyko coupled water-energy balance theory and evaporation paradox, then use the Fu's equation to estimate actual evapotranspiration yearly in different areas with different dryness. The result shows that Fu's equation has high precision for estimating evapotranspiration yearly in our selected study area, and the estimation result has higher precision in the area with high dryness. Then, we propose an improved formula which can be used to estimate actual evapotranspiration monthly. Furthermore, we found that the parameter in the formula reflects general conditions of underlying surface and it is affected by several factors, at last, we tried to propose the calculation formula. The study indicates that Fu's equation provides a reliable method for evapotranspiration estimation in dry regions as well as semi-humid and semi-arid regions, which has great significance for forecasting river basin water resources and inquiring into ecological water requirement.

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MASS ESTIMATION OF IMPACTING OBJECTS AGAINST A STRUCTURE USING AN ARTIFICIAL NEURAL NETWORK WITHOUT CONSIDERATION OF BACKGROUND NOISE

  • Shin, Sung-Hwan;Park, Jin-Ho;Yoon, Doo-Byung;Choi, Young-Chul
    • Nuclear Engineering and Technology
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    • v.43 no.4
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    • pp.343-354
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    • 2011
  • It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

A Method of Estimation of Energy Consumption according to a Supply Pressure for Pneumatic Cylinder Driving Apparatus (공급압력 변화에 의한 공기압 실린더 구동장치의 소비에너지 변화량 추정 방법)

  • Jang, J.S.
    • Journal of Drive and Control
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    • v.9 no.2
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    • pp.15-20
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    • 2012
  • Pneumatic cylinder meter-out driving apparatus is used widely because it is clean, lightweight, and can be easily serviced. In this study an estimation method of energy consumption for pneumatic cylinder meter-out driving apparatus is proposed. The proposed method is derived from state equation and energy equation of air, and, the equation of motion of a moving part of a pneumatic cylinder reflecting the characteristics of the meter-out driving. The effectiveness of the proposed method is proved by simulation study and it demonstrates that the proposed method can evaluate the energy consumption quickly and easily when the parameters of the driving apparatus are changed.