• Title/Summary/Keyword: power prediction

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Spatio-temporal Load Forecasting Considering Aggregation Features of Electricity Cells and Uncertainties in Input Variables

  • Zhao, Teng;Zhang, Yan;Chen, Haibo
    • Journal of Electrical Engineering and Technology
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    • v.13 no.1
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    • pp.38-50
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    • 2018
  • Spatio-temporal load forecasting (STLF) is a foundation for building the prediction-based power map, which could be a useful tool for the visualization and tendency assessment of urban energy application. Constructing one point-forecasting model for each electricity cell in the geographic space is possible; however, it is unadvisable and insufficient, considering the aggregation features of electricity cells and uncertainties in input variables. This paper presents a new STLF method, with a data-driven framework consisting of 3 subroutines: multi-level clustering of cells considering their aggregation features, load regression for each category of cells based on SLS-SVRNs (sparse least squares support vector regression networks), and interval forecasting of spatio-temporal load with sampled blind number. Take some area in Pudong, Shanghai as the region of study. Results of multi-level clustering show that electricity cells in the same category are clustered in geographic space to some extent, which reveals the spatial aggregation feature of cells. For cellular load regression, a comparison has been made with 3 other forecasting methods, indicating the higher accuracy of the proposed method in point-forecasting of spatio-temporal load. Furthermore, results of interval load forecasting demonstrate that the proposed prediction-interval construction method can effectively convey the uncertainties in input variables.

Evaluation on Creep Life Prediction of Aircraft Gas Turbine Material by AE (음향방출법에 의한 항공기용 가스터빈 재료의 크리프 수명예측 평가)

  • Kong, Y.S.;Yoon, H.K.;Oh, S.K.
    • Journal of Power System Engineering
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    • v.6 no.1
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    • pp.55-60
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    • 2002
  • There has been no report on the life prediction for gas turbine materials at high temperatures based on the creep properties and their relationship with the AE(acoustic emission) properties as a means of real-time non-destructive testing. One of the important issues is thus to develop a reliable method of evaluating creep properties by the AE technique. In this paper, the real-time evaluation of high temperature creep time and AE cumulative counts for nickel-based superalloy Udimet 720 was performed on round-bar type specimens under pure load at the temperatures of 811, 922 and 977K. The total AE cumulative counts until the starting point of secondary creep($N_1$) and that of tertiary creep($N_2$) have quantitative relationship with the tertiary creep time and the rupture time. It is thus possible to construct the life prediction system based on creep and the prevention system of tertiary creep by using AE technique.

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A Study on Prediction of Temperature and Humidity for Estimation of Cooling Load (냉방부하 추정을 위한 온도와 습도 예측에 관한 연구)

  • Yoo, Seong-Yeon;Lee, Je-Myo;Han, Kyou-Hyun;Han, Seung-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.19 no.5
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    • pp.394-402
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    • 2007
  • To estimate the cooling load for the following day, outdoor temperature and humidity are needed in hourly base. But the meteorological administration forecasts only maximum and minimum temperature. New methodology is proposed for predicting hourly outdoor temperature and humidity by using the forecasted maximum and minimum temperature. The correlations for normalized outdoor temperature and specific humidity has been derived from the weather data for five years from 2001 to 2005 at Seoul, Daejeon and Pusan. The correlations for normalized temperature are independent of date, while the correlations for specific humidity are linearly dependent on date. The predicted results show fairly good agreement with the measured data. The prediction program is also developed for hourly outdoor dry bulb temperature, specific humidity, dew point, relative humidity, enthalpy and specific volume.

Dynamic Thermal Rating of Overhead Transmission Lines Based on GRAPES Numerical Weather Forecast

  • Yan, Hongbo;Wang, Yanling;Zhou, Xiaofeng;Liang, Likai;Yin, Zhijun;Wang, Wei
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.724-736
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    • 2019
  • Dynamic thermal rating technology can effectively improve the thermal load capacity of transmission lines. However, its availability is limited by the quantity and high cost of the hardware facilities. This paper proposes a new dynamic thermal rating technology based on global/regional assimilation and prediction system (GRAPES) and geographic information system (GIS). The paper will also explore the method of obtaining any point meteorological data along the transmission line by using GRAPES and GIS, and provide the strategy of extracting and decoding meteorological data. In this paper, the accuracy of numerical weather prediction was verified from the perspective of time and space. Also, the 750-kV transmission line in Shaanxi Province is considered as an example to analyze. The results of the study indicate that dynamic thermal rating based on GRAPES and GIS can fully excavate the line power potential without additional cost on hardware, which saves a lot of investment.

A real-time unmeasured dynamic response prediction for nuclear facility pressure pipeline system

  • Seungin Oh ;Hyunwoo Baek ;Kang-Heon Lee ;Dae-Sic Jang;Jihyun Jun ;Jin-Gyun Kim
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2642-2649
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    • 2023
  • A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

Throughput Prediction of Pohang Port using Time Series Data: Application of SARIMA, Prophet and Neural Prophet (시계열 데이터를 활용한 포항항 물동량 예측: SARIMA, Prophet, Neural Prophet의 적용)

  • Jin-Ho Oh;Jeong-Won Choi;Tae-Hyun Kang;Young-Joon Seo;Dong-Wook Kwak
    • Korea Trade Review
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    • v.47 no.6
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    • pp.291-305
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    • 2022
  • In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.

A long-term tunnel settlement prediction model based on BO-GPBE with SHM data

  • Yang Ding;Yu-Jun Wei;Pei-Sen Xi;Peng-Peng Ang;Zhen Han
    • Smart Structures and Systems
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    • v.33 no.1
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    • pp.17-26
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    • 2024
  • The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

A Receiving Power Prediction Model for Exention of Sonics Area in CDMA mobile communication (CDMA 이동통신 서비스 영역 확장을 위한 수신전력 예측 모델 제안)

  • 최동유;최동우;노순국;김재섭;양흥영;박창균
    • Proceedings of the IEEK Conference
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    • 2000.11a
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    • pp.133-136
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    • 2000
  • Generally in the case of mobil communication service for long distance sea, unlike heavily populated residential areas, providers need to minimize the service area per base station. Therefore, in this thesis, the 800 ㎒ CDMA system should be extended to give better long distance communication service. This model is used to predict the occurring receiving power of the mobile stations that we simulated and analyzed. As a result, the experiment demonstrated the appropriateness of predicting receiving power using this model.

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A Study on Short-Term Prediction of Supplied Electrical Power using Chaos Fuzzy Controller (카오스 퍼지 제어기를 이용한 전력소요량의 단기예측에 관한 연구)

  • 추연규;정대균
    • Journal of the Korean Institute of Navigation
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    • v.24 no.3
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    • pp.147-155
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    • 2000
  • In this paper, we propose the Chaos Fuzzy controller to analyze the chaotic character of time series obtained from the specific plant and to predict the short-term for power consumption of the plant using the Fuzzy controller. We compared the predicted data with the active ones and checked the error generated by them after we time series of supplied power to the proposed controller. As a result of the simulation, we obtained a admirable consequence that the proposed controller can be advanced through various and accurate data acquisition, and continuous analysis of the resident and industrial environment.

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A kernel-based precomputation scheme for low-power design fo combinational circuits (저전력 논리 회로 설계를 위한 커널에 바탕을 둔 precomputation 알고리듬)

  • 최익성;류승현
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.11
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    • pp.12-19
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    • 1997
  • In this paper, we present a logic synthesis algorithm for low powr design fo combinational circuits. The proposed algorithm reduces power dissipation by eliminating unnecessary signal transitions. The proposed algorithm restructures a given circuit by using a kernel as prediction logic in a precomputation-based scheme such that switching activity of circuit can be minimized. Experimental results show that the system is efficient for low power design of combinational circuits.

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