• Title, Summary, Keyword: Predicting power

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Assessment of Wind Power Prediction Using Hybrid Method and Comparison with Different Models

  • Eissa, Mohammed;Yu, Jilai;Wang, Songyan;Liu, Peng
    • Journal of Electrical Engineering and Technology
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    • v.13 no.3
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    • pp.1089-1098
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    • 2018
  • This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.

Prediction of Mobile Phone Menu Selection with Markov Chains (Markov Chain을 이용한 핸드폰 메뉴 선택 예측)

  • Lee, Suk Won;Myung, Rohae
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.4
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    • pp.402-409
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    • 2007
  • Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

The Influence of Relationship Benefit Perception and Relationship Quality on Relationship Intention of Fashion Consumers: Focusing on the Multi-Loyal Relations (패션상품 소비자의 관계혜택지각과 관계본질이 관계유지의도에 미치는 영향: 다면적 충성대상에 따른 영향력의 차이를 중심으로)

  • Moon, Hee-Kang;Rhee, Eun-Young
    • Journal of the Korean Home Economics Association
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    • v.48 no.3
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    • pp.15-30
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    • 2010
  • The objective of this study is to identify the relationship quality and relationship benefit, which has greater explanatory power in predicting fashion consumers' future loyalty. This study is particularly interested in the different explanatory power of each relationship quality with various relationship partners of fashion consumers. The participants were 507 female consumers over 20 years old and they responed questionnaire. The result showed that relationship quality types and relationship benefits having greater explanatory power in predicting consumers' loyal relationship intention varied with multi-loyal relations. Consumers' intention to be loyal to an apparel brand and apparel company was more explained by self attachment than by any other relationship quality types, whereas the intention to be loyal to specific department store was predicted by low involved relationship quality types such as habitual alternative and compensational bind. Trusted intimacy was the only relationship quality type that was significant in predicting consumers' intention to be loyal to salesperson in the future. Among relationship benefits, the influence of convenience benefit was significant in predicting consumers' future loyalty in most relations.

A Study of Smart Uninterruptible Power Supply Capable High Efficiency Drive (고효율 운전이 가능한 지능형 무정전 전원장치에 관한 연구)

  • Eom, Tae-Wook
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.27 no.5
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    • pp.61-66
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    • 2013
  • In this paper, a control scheme with the capability of high efficiency, which is realized by predicting the conditions of a load power and an input power, is proposed for the uninterruptible power supply (UPS). Generally, on-line UPS system supplies a constant voltage and a constant frequency (CVCF). However, the efficiency of the On-line UPS system can be reduced due to the switching losses of semiconductor devices during the power conversion. The these losses are improved by the proposed smart UPS with the high efficiency drive system, which is realized by analysing and predicting the conditions of a load power and an input power.

Characteristics of Power Efficiency of Tractor Driveline (트랙터 전동라인의 전동효율 특성 분석)

  • 류일훈;김대철;김경욱
    • Journal of Biosystems Engineering
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    • v.27 no.1
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    • pp.19-24
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    • 2002
  • According to the field test, the transient power transmission efficiency of a tractor driveline fluctuated in a range of 56 to 86% and the mean value was about 72.5%. Therefore, the constant efficiency model commonly used for a simulation of power performance was not proper far predicting such a variable of efficiency. In order to predict power efficiency more accurately, new concepts of the maximum efficiency and drag torque were introduced and a new model based on the these concepts was proposed. The difference between measured and model-predicted efficiencies was about 1.5% in average with a standard deviation of 1.1%. The new power efficiency model was expected to enhance the accuracy of predicting power transmission efficiencies of tractor drivelines.

Planning ESS Managemt Pattern Algorithm for Saving Energy Through Predicting the Amount of Photovoltaic Generation

  • Shin, Seung-Uk;Park, Jeong-Min;Moon, Eun-A
    • Journal of the Chosun Natural Science
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    • v.12 no.1
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    • pp.20-23
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    • 2019
  • Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

K-IFRS Reconciliations and Predicting Future Earnings (K-IFRS 도입 시점의 전환조정이 이후 기간의 미래이익 예측력에 미치는 영향)

  • Ji, Sang-Hyun;Kwak, Young-Min
    • Journal of Digital Convergence
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    • v.15 no.12
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    • pp.283-291
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    • 2017
  • This Study analyzes the predictability of accounting information from mandatory K-IFRS adoption using the K-IFRS reconciliations information. We use the sample of 2,557 firm-year Korea listed companies belonging to non-financial corporate sector during 2010-2016. Specifically, we examine whether K-IFS reconciliation would improve or reduce the predicting power for future earnings after K-IFRS adoption. The results of empirical analyses show that reconciliation information from discretionary judgement tend to reduce the predicting power of K-IFRS based accounting earnings for future earnings. This result indicates that managers are likely to use the adjustments process to reconcile K-GAAP accounting numbers with corresponding K-IFRS as means to realize the various private utility. This study is expected to provide useful information by suggesting the need for more rigid screening schemes for the K-IFRS reconciliation process and also for adequate measures to be taken to ensure that the interests of the outside investors are properly protected.

Attitudinal Determinants of Summer Vacation Activity Participation -Application of the Theory of Planned Behavior- (여름휴가활동 선택의 영향요인에 관한 연구 - 계획행동이론을 적용하여 -)

  • 김승현;엄서호
    • Journal of the Korean Institute of Landscape Architecture
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    • v.25 no.1
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    • pp.135-142
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    • 1997
  • The objectives of this study was to test applicability of the theory of planned behavior by Ajzen & Driver(1992), to predicting summer vacation activity participation. Vacations to vist Sock-Cho City in summer were asked to complete a questionaire to measure attitudes, subjective norms, perceived behavioral control, and intentions in relation to participating in three vacation activities, at the beach, at the valley, and at the pool. After summer vacation, respondents were called to answer whether or not they had participated in those activities. The results showed that attitudes toward vocation consist of affective and instrumental component Consistent with the theory, attitudes, subjective norms and perceived behavioral control were significant variables in predicting intentions to participate in vacation activites. In addition, intentions and perceived control were influential in predicting vacation activities partication. Althouh the objectives of the study were achived, this application of the theory of planned behavior to Koreans summer vacation participations did not show the same power as the Ajzen & Driver's study(1992) in predicting recreation activties participation. It would be desirable for future research to apply the theory of planned behavior to various recreational settings.

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The new odd-burr rayleigh distribution for wind speed characterization

  • Arik, Ibrahim;Kantar, Yeliz M.;Usta, Ilhan
    • Wind and Structures
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    • v.28 no.6
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    • pp.369-380
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    • 2019
  • Statistical distributions are very useful in describing wind speed characteristics and in predicting wind power potential of a specified region. Although the Weibull distribution is the most popular one in wind energy literature, it does not seem to be able to perfectly fit all the investigated wind speed data in nature. Thus, many studies are still being conducted to find flexible distribution for modelling wind speed data. In this study, we propose a new Odd-Burr Rayleigh distribution for wind speed characterization. The Odd-Burr Rayleigh distribution with two shape parameters is flexible enough to model different shapes of wind speed data and thus it can be an alternative wind speed distribution for the assessment of wind energy potential. Therefore, suitability of the Odd-Burr Rayleigh distribution is investigated on real wind speed data taken from different regions in the South Africa. Numerical results of the conducted analysis confirm that the new Odd-Burr Rayleigh distribution is suitable for modelling most of the considered real wind speed cases and it also can be used for predicting wind power.