• 제목/요약/키워드: Power demand prediction

검색결과 112건 처리시간 0.029초

클라우드 컴퓨팅 환경에서 자원의 사용률을 이용한 소비전력 예측 방안 (Prediction Method about Power Consumption by Using Utilization Rate of Resources in Cloud Computing Environment)

  • 박상면;문영성
    • 인터넷정보학회논문지
    • /
    • 제17권1호
    • /
    • pp.7-14
    • /
    • 2016
  • 최근 클라우드 컴퓨팅 기술이 발전함에 따라, 언제 어디서나 스마트 폰이나 컴퓨터로 접속하여 업무를 처리할 수 있다. 또한 IT 인프라를 구축하기 위한 초기투자비용과 유지보수에 대한 부담을 줄이는 방안으로 적합하다고 여겨지면서 클라우드 컴퓨팅은 발전하였다. 클라우드 컴퓨팅의 수요가 급격하게 늘어남에 따라, 데이터센터의 환경을 유지하기 위해 소비되는 전력에 관한 문제가 발생하였다. 이 문제를 해결하기 위해서는 먼저 소비전력을 측정할 수 있어야 한다. 비록 전력측정기를 이용하여 소비전력을 측정하는 것은 정확한 소비전력을 얻을 수 있지만, 추가비용이 발생한다. 따라서 본 논문에서는 전력측정기에 의존하지 않고 소비전력을 예측하는 방안을 제시한다. 제시한 방안의 정확성을 입증하기 위해 클라우드 컴퓨팅 환경에서 CPU와 Hard disk 테스트를 실시하였다. 테스트가 진행되는 동안, 제안한 방안과 전력측정기에 의해 예측 값과 실제 값을 얻고. 오차율을 계산하였다. 그 결과 CPU 테스트에서 예측 값과 실제 값의 차이는 약 4.22%이고, Hard disk 테스트에서는 약 8.51%을 보였다.

Newton 보외법에 의한 수요전력 예측 알고리즘 (New Algorithm for Demand Power Prediction Using Newton Extrapolation Method)

  • 정대원
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2001년도 하계학술대회 논문집 D
    • /
    • pp.2782-2784
    • /
    • 2001
  • 최대수요전력 제어기의 실시간 부하전력예측을 위하여 Newton 보외법을 적용하였다. 기존의 선형기법에 비하여 실제 데이터에 가까운 부하전력을 예측할 수 있었다. 이 새로운 알고리즘을 적용함으로써 부하예측을 보다 정확히 할 수 있어 빈번한 부하차단이나 우발적인 차단을 방지하여 설비 운용의 신뢰성을 높일 수 있다. 개선된 알고리즘은 마이컴으로 제어되는 실제 시스템에 적용하여 보다 나은 성능을 얻을 수 있었다.

  • PDF

수급모형을 이용한 양식넙치의 생산 및 출하조절 효과분석 (An Analysis of Production and Marketing Control Effect of Aqua-cultured Flounder Using Supply and Demand Models)

  • 고봉현
    • 수산경영론집
    • /
    • 제47권4호
    • /
    • pp.65-75
    • /
    • 2016
  • The purpose of this study was to analyze the production and marketing control effects of aqua-cultured flounder required for stable income growth of aqua-cultured household. We analyzed the supply and demand structure of cultured flounder using the partial equilibrium model approach. And we estimated the optimal yield of cultured flounder and analyzed the effect of marketing control through constructed model. The main results of this study are summarized as follows. First, the fitness and predictive power of the estimated model showed that the RMSPE and MAPE values were less than 5% and Theil's inequality coefficient was very close to 0 rather than 1. It was evaluated that the prediction ability of the aqua-cultured flounder supply and demand model by dynamic simulation was excellent. Second, dynamic simulation based on policy simulation was conducted to analyze the price increase effect of production and shipment control of cultured flounder. As a result, if the annual production volume is reduced by 1%, 5%, and 10% among 32,852~37,520 tons, it is analyzed that the price increase effect is from 1.2% to 12.5%. Finally, this study suggests that the production and marketing control can increase the price of aqua-cultured flounder in the market. In this paper, we propose a policy implementation of the total supply system instead of conclusions.

주상 변압기 최대부하 추정을 위한 부하상관계수 및 수용율 조정 (Adjustment of Load Regression Coefficients and Demand-Factor for the Peak Load Estimation of Pole-Type Transformers)

  • 윤상윤;김재철;박경호;문종필;이진;박창호
    • 대한전기학회논문지:전력기술부문A
    • /
    • 제53권2호
    • /
    • pp.87-96
    • /
    • 2004
  • This paper summarizes the research results of the load management for pole transformers done in 1997-1998 and 2000-2002. The purpose of the research is to enhance the accuracy of peak load estimation in pole transformers. We concentrated our effort on the acquisition of massive actual load data for modifying the load regression coefficients, which related to the peak load estimation of lamp-use customers, and adjusting the demand-factor coefficients, which used for the peak load prediction of motor-use customers. To enhance the load regression equations, the 264 load data acquisition devices are equipped to the sample pole transformers. For the modification of demand factor coefficients, the peak load currents are measured in each customer and pole transformer for 13 KEPCO (Korea Electric Power Corporation) distribution branch offices. Case studies for 50 sample pole transformers show that the proposed coefficients could reduce estimating error of the peak load for pole transformers, compared with the conventional one.

시계열 모델을 이용한 행동기반 에너지 효율화 프로그램의 고객기준부하 산정 방안 (Customer Baseline Load Calculation using Time Series Prediction Technique in Energy Efficiency Programs)

  • 고세현;주성관;이재희;문국현;위영민
    • 전기학회논문지
    • /
    • 제68권1호
    • /
    • pp.19-26
    • /
    • 2019
  • As global demand for energy, energy prices, and power generation has increased worldwide, the government is turning to supply-oriented electricity supply and demand policies, such as behavior-based energy efficiency programs. In order to measure the implementation effect of the behavior-based energy efficiency program, the energy reduction must be accurately calculated by calculating the customer baseline load.

Spatiotemporal Impact Assessments of Highway Construction: Autonomous SWAT Modeling

  • Choi, Kunhee;Bae, Junseo
    • 국제학술발표논문집
    • /
    • The 6th International Conference on Construction Engineering and Project Management
    • /
    • pp.294-298
    • /
    • 2015
  • In the United States, the completion of Construction Work Zone (CWZ) impact assessments for all federally-funded highway infrastructure improvement projects is mandated, yet it is regarded as a daunting task for state transportation agencies, due to a lack of standardized analytical methods for developing sounder Transportation Management Plans (TMPs). To circumvent these issues, this study aims to create a spatiotemporal modeling framework, dubbed "SWAT" (Spatiotemporal Work zone Assessment for TMPs). This study drew a total of 43,795 traffic sensor reading data collected from heavily trafficked highways in U.S. metropolitan areas. A multilevel-cluster-driven analysis characterized traffic patterns, while being verified using a measurement system analysis. An artificial neural networks model was created to predict potential 24/7 traffic demand automatically, and its predictive power was statistically validated. It is proposed that the predicted traffic patterns will be then incorporated into a what-if scenario analysis that evaluates the impact of numerous alternative construction plans. This study will yield a breakthrough in automating CWZ impact assessments with the first view of a systematic estimation method.

  • PDF

역전파 신경회로망 기반의 단기시장가격 예측 (Locational Marginal Price Forecasting Using Artificial Neural Network)

  • 송병선;이정규;박종배;신중린
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2004년도 하계학술대회 논문집 A
    • /
    • pp.698-700
    • /
    • 2004
  • Electric power restructuring offers a major change to the vertically integrated utility monopoly. Deregulation has had a great impact on the electric power industry in various countries. Bidding competition is one of the main transaction approaches after deregulation. The energy trading levels between market participants is largely dependent on the short-term price forecasts. This paper presents the short-term System Marginal Price (SMP) forecasting implementation using backpropagation Neural Network in competitive electricity market. Demand and SMP that supplied from Korea Power Exchange (KPX) are used by a input data and then predict SMP. It needs to analysis the input data for accurate prediction.

  • PDF

기계학습을 이용한 태양광 발전량 예측 및 결함 검출 시스템 개발 (Development of a System for Predicting Photovoltaic Power Generation and Detecting Defects Using Machine Learning)

  • 이승민;이우진
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
    • /
    • 제5권10호
    • /
    • pp.353-360
    • /
    • 2016
  • 여러 개의 태양전지들이 붙어 있는 태양광 패널을 이용하여 전력을 생산하는 태양광 발전은 최근 신재생 에너지 기술로 빠르게 성장하고 있는 분야이다. 하지만 태양광발전의 단점 중 하나인 불규칙한 전력 생산문제로 인해, 장비 및 패널 결함에 빠르게 대응하지 못하는 문제가 발생한다. 이 연구에서는 다양한 기후데이터와 패널 정보를 이용하여 태양광발전량 예측 방법들을 비교하여 최적의 예측 알고리즘을 평가하고 이를 기반으로 태양광발전소 결함 검출 시스템을 개발하여 국내 태양광 발전소에 적용한 사례를 기술한다.

웨이브릿 변환을 이용한 발전시스템 한계원가 예측기법 (Prediction technique for system marginal price using wavelet transform)

  • 김창일;김봉태;김우현;유인근
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
    • /
    • pp.210-212
    • /
    • 1999
  • This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.

  • PDF

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
    • /
    • 제12권5호
    • /
    • pp.1709-1718
    • /
    • 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.