• 제목/요약/키워드: Generation Prediction

검색결과 803건 처리시간 0.027초

지하철 터널내 열차풍 예측 프로그램 개발에 관한 연구 (A Study on the Development of the Train Wind Rate Prediction Program in Tunnel of the Subway)

  • 김종열;최광환
    • 동력기계공학회지
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    • 제3권1호
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    • pp.38-44
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    • 1999
  • Subway is one of the most important transportation and its facilities are increased by the drift of population to cities in these days. But heat generation results from lighting, human and traffic increase in subway, half-closed space, gives uncomfortable sense to the subway passengers. Therefore, natural ventilation by piston effect is done to relieve uncomfortable sense. But train wind by piston effect gives uncomfortable sense to the subway passengers, too. So the numerical calculation of inflow and outflow amounts is important to predict thermal environment and reduce train wind. In case of actual survey of train wind in target station, the amount of train wind are about $3100m^3/train$ at the minimum, about $6000m^3/train$ at the maximum, about $4200m^3/train$ on average. When comparison between simulation for train wind prediction and actual survey for accuracy was done train wind prediction program showed similar results.

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장단기 앙상블 모델과 이미지를 활용한 주가예측 향상 알고리즘 : 석유화학기업을 중심으로 (Stock Price Prediction Improvement Algorithm Using Long-Short Term Ensemble and Chart Images: Focusing on the Petrochemical Industry)

  • 방은지;변희용;조재민
    • 한국멀티미디어학회논문지
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    • 제25권2호
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    • pp.157-165
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    • 2022
  • As the stock market is affected by various circumstances including economic and political variables, predicting the stock market is considered a still open problem. When combined with corporate financial statement data analysis, which is used as fundamental analysis, and technical analysis with a short data generation cycle, there is a problem that the time domain does not match. Our proposed method, LSTE the operating profit and market outlook of a petrochemical company and estimates the sales and operating profit of the company, it was possible to solve the above-mentioned problems and improve the accuracy of stock price prediction. Extensive experiments on real-world stock data show that our method outperforms the 8.58% relative improvements on average w.r.t. accuracy.

건물적용 태양광발전시스템의 국내 지역에 따른 설치각도별 연간 전력생산량 예측에 관한 연구 (Annual energy yield prediction of building added PV system depending on the installation angle and the location in Korea)

  • 김동수;신우철;윤종호
    • KIEAE Journal
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    • 제14권1호
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    • pp.67-74
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    • 2014
  • There have distinctly been no the installation criteria and maintenance management of BIPV systems, although the BIPV market is consistently going on increasing. In addition, consideration of the BIPV generation quantity which has been installed at several diverse places is currently almost behind within region in Korea. Therefore, the main aim of this study is to evaluate the BIPV generation and to be base data of reducing rate depending on regional installation angles using PVpro which was verified by measured data. Various conditions were an angle of inclination and azimuth under six major cities: Seoul, Daejeon, Daegu, Busan, Gwangju, Jeju-si for the BIPV system generation analysis. As the results, Seoul showed the lowest BIPV generation: 1,054kWh/kWp.year, and Jeju-si have 5percent more generation: 1,108.0kWh/kWp.year than Seoul on horizontal plane. Gwangju and Daejeon turned out to have similar generation of result, and Busan showed the highest generation: 1,193.5kWh/kWp.year, which was increased by over 13percent from Seoul on horizontal plane. Another result, decreasing rate of BIPV generation depending on regional included angle indicate that the best position was located on azimuth: $0^{\circ}$(The south side) following the horizontal position(an angle of inclination: $30^{\circ}$). And the direction on a south vertical position(azimuth: $0^{\circ}$, an angle of inclination: $90^{\circ}$) then turned out reducing rate about 40percent compared with the best one. Therefore, these results would be used to identify the installation angle of the BIPV module as an appropriate position.

Chance-constrained Scheduling of Variable Generation and Energy Storage in a Multi-Timescale Framework

  • Tan, Wen-Shan;Abdullah, Md Pauzi;Shaaban, Mohamed
    • Journal of Electrical Engineering and Technology
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    • 제12권5호
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    • pp.1709-1718
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    • 2017
  • This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

위도와 해발높이에 따른 태양광발전 효율 분석 연구 (A Study on Solar Power Generation Efficiency Analysis according to Latitude and Altitude)

  • 차왕철;박정호;조욱래;김재철
    • 조명전기설비학회논문지
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    • 제28권10호
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    • pp.95-100
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    • 2014
  • To solve the problem of conventional fossil energy, utilization of renewable energy is growing rapidly. Solar energy as an energy source is infinite, and a variety of research is being conducted into its utilization. To change solar energy into electrical energy, we need to build a solar power plant. The efficiency of such a plant is strongly influenced by meteorological factors; that is, its efficiency is determined by solar radiation. However, when analyzing observed generation data, it is clear that the generated amount is changed by various factors such as weather, location and plant efficiency. In this paper, we proposed a solar power generation prediction algorithm using geographical factors such as latitude and elevation. Hence, changes in generated amount caused by the installation environment are calculated by curve fitting. Through applying the method to calculate this generation amount, the difference between real generated amount is analyzed.

장기 Outdoor Test를 통한 CPV와 PV 모듈의 발전량 비교분석 (A study of Comparative Analysis of CPV and PV Module through Long-term Outdoor Testing)

  • 김민수;이유리;조민제;오수영;정재학
    • Current Photovoltaic Research
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    • 제5권1호
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    • pp.33-37
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    • 2017
  • Today, photovoltaic power generation mostly uses Si crystalline solar cell modules. The most vulnerable part of the Si solar cell module is that the power generation decreases due to the temperature rise. But, it is widely used because of low installation cost. In the solar market, where Si crystalline solar cell modules are widely used. The CPV (Concentrated Photovoltaic) module appeared in the solar market. The CPV module reduces the manufacturing cost of the solar cell by using non-Si in the solar cell. Also, there is an advantage that a rise in temperature does not cause a drop in power generation. But this requires high technology to install and has a disadvantage that the initial installation cost is expensive compared to normal Si solar cell module. So that we built a testbed to see these characteristics. The testbed was used to measure the amount of power generation in a long-term outdoor environment and compared with the general Si solar cell module.

신경망 이론을 이용한 통행발생 모형연구 (선형/비선형 회귀모형과의 비교) (Trip Generation Model Using Backpropagation Neural Networks in Comparison with linear/nonlinear Regression Analysis)

  • 장수은;김대현;임강원
    • 대한교통학회지
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    • 제18권4호
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    • pp.95-105
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    • 2000
  • 본 연구의 목적은 기존의 대표적 통행발생모형인 회귀모형과 신경망 이론에 의한 통행발생모형을 비교.분석하여 통행발생모형에 대한 새로운 방법을 제시하고자 하는 것이다. 이를 위해 모형의 검정력과 안정성을 현재적 설명력과 장래 예측력의 결합으로 전제하고, 시나리오에 따른 모형의 검정력 변화를 통한 안정성 평가를 수행하였다. 연구결과 역전파 신경망 모형(Backpropagation Neural Networks)은 회귀모형의 검정력과 안정성을 상회하는 우수한 결과를 보여 주었으며, 이는 향후 통행발생 모형으로 역전파 신경망 모형의 적용 가능성을 의미하는 것으로 해석된다. 특히 복잡해진 교통현상과 다양한 수집자료를 고려할 때 교통분야에서의 신경망 모형의 적용은 더욱 확대될 전망이다.

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