• 제목/요약/키워드: Electricity Load

검색결과 515건 처리시간 0.023초

계통계획을 위한 지역별 전력수요예측 (Regional Electricity Demand Forecasting for System Planning)

  • 조인승;이창호;박종진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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    • pp.292-294
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    • 1998
  • It is very important for electric utility to expand generating facilities and transmission equipments in accordance with the increase of electricity demand. Regional electricity demand forecasting is among the most important step for long-term investment and power supply planning. The main objectives of this paper are to develop the methodologies for forecasting regional load demand. The Model consists of four models, regional economy, regional electricity energy demand, areal electricity energy demand. and areal peak load demand. This paper mainly suggests regional electricity energy demand model and areal peak load demand. A case study is also presented.

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전력산업 경쟁도입에 따른 요금변화에 대한 부하모델수립 (A Study on Load Modeling with respect to the Change of Price in Competitive Electricity Market)

  • 한만형;김정훈;최준영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.376-378
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    • 2000
  • The current worldwide electricity market introduced competition, which is breaking up the monopoly structure and also enforcing phased structural reform in South Korea. The change of the electricity charge from cost base to price base due to the introduction of the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Therefore, in order to find a mathematical model of the sensitively-responding-to-price loads and reflect this to the DSM demand management, the price-sensitive load model is needed. Thus, this paper first proposes the composite price-sensitive load model that is expressed as a function of price, presents the methodology to estimate price-sensitive load model at each bus by bus load compositions.

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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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    • 제13권1호
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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.

경쟁적 전력시장에서의 최적 부하소비전략 수립을 위한 새로운 부하관리시스템 패키지 개발 (Development of a New Load Management System Package for Optimal Electricity Consumption Strategy in a Competitive Electricity Market)

  • 정구형;이찬주;김진호;김발호;박종배
    • 대한전기학회논문지:전력기술부문A
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    • 제53권3호
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    • pp.187-197
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    • 2004
  • This paper presents a window-based load management system (LMS) developed as a decision-making tool in the competitive electricity market The developed LMS can help the users to monitor system load patterns, analyze their past energy consumption and schedule for the future energy consumption. The LMS can also provide the effective information on real-time energy/cost monitoring, consumed energy/cost analysis, demand schedule and cost-savings. Therefore. this LMS can be used to plan the optimal demand schedule and consumption strategy.

CLUSTER ANALYSIS FOR REGION ELECTRIC LOAD FORECASTING SYSTEM

  • Park, Hong-Kyu;Kim, Young-Il;Park, Jin-Hyoung;Ryu, Keun-Ho
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.591-593
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    • 2007
  • This paper is to cluster the AMR (Automatic Meter Reading) data. The load survey system has been applied to record the power consumption of sampling the contract assortment in KEPRI AMR. The effect of the contract assortment change to the customer power consumption is determined by executing the clustering on the load survey results. We can supply the power to customer according to usage to the analysis cluster. The Korea a class of the electricity supply type is less than other country. Because of the Korea electricity markets exists one electricity provider. Need to further divide of electricity supply type for more efficient supply. We are found pattern that is different from supplied type to customer. Out experiment use the Clementine which data mining tools.

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전력산업 경쟁 환경에서의 요금부하모델 수립을 위한 부하기기의 학습곡선 분석 (Analysis on learning curves of end-use appliances for the establishment of price-sensitivity load model in competitive electricity market)

  • 황성욱;김정훈;송경빈;최준영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 A
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    • pp.386-388
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    • 2001
  • The change of the electricity charge from cost base to price base due to the introduction of the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding-to-price loads, the price-sensitive load model is needed. And the development of state-of-the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns.

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시계열 모형을 이용한 일별 최대 전력 수요 예측 연구 (Daily Peak Load Forecasting for Electricity Demand by Time series Models)

  • 이정순;손흥구;김삼용
    • 응용통계연구
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    • 제26권2호
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    • pp.349-360
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    • 2013
  • 최근 일별 최대 전력수요 예측은 전력설비 계획 및 운용에 매우 중요한 사안으로 주목받고 있다. 본 연구는 일별 최대 전력수요 예측을 위하여 대표적 시계열 모형을 소개하고, 예측의 성능 비교를 위하여 RMSE(Root mean squared error)와 MAPE(Mean absolute percentage error)를 사용한다. 연구결과로 보완된 Holt-Winters 모형과 Reg-ARIMA 모형이 다른 모형에 비하여 우수한 예측 성능을 보였다.

서울지역 사무소 건물의 환경부하에 관한 연구 (A study on the environmental load of office buildings in Seoul)

  • 이상형;이윤규;양관섭;안태경;이승언;박효순
    • 설비공학논문집
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    • 제11권2호
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    • pp.244-249
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    • 1999
  • This study is to examine the emission rate of $CO_2$gas as the environmental load in office buildings. After the investigation of monthly consumption of each energy source(electricity and natural gas), it is analyzed that the $CO_2$emission rate of 34 office buildings surveyed is 22.4kg-$c/m^2$.year, which consists of 17.5kg-$c/m^2$.year by consuming electricity, and 4.9kg-$c/m^2$.year by consuming natural gas. And the $CO_2$emission rate of each load in those buildings consists of 68% emitted by general electricity, 16% by cooling load and 16% by heating load. It is also proposed that the $CO_2$emission rate of cooling and heating load is profoundly pertinent to the variation of outdoor temperature.

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Multi-Objective Optimization Model of Electricity Behavior Considering the Combination of Household Appliance Correlation and Comfort

  • Qu, Zhaoyang;Qu, Nan;Liu, Yaowei;Yin, Xiangai;Qu, Chong;Wang, Wanxin;Han, Jing
    • Journal of Electrical Engineering and Technology
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    • 제13권5호
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    • pp.1821-1830
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    • 2018
  • With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

하계전력수급 안정을 위한 부하관리 대책 (A Study on the Load Management for the Stability of Power Supply in summer)

  • 조규승;강원구;이윤섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.17-18
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    • 1991
  • In electric Industry, the improvement of load factor by flattening load has been considered to be more important than any other tasks and has received wide concern and interest. Especially while annual peak load had occurred early evening in winter during past decades, but we found the trend has changed so that annual peak load occurred during the daytime in summer since 1981. In this paper we introduce various method for the load management.

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