• Title/Summary/Keyword: Stochastic Generation

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Multi-Phase Interleaved Boost Converter for Fuel Cell Generation System using LabVIEW (LabVIEW를 이용한 연료전지 발전시스템용 다상부스트 컨버터)

  • Park, So-Ri;Jang, Su-Jin;Won, Chung-Yuen;Kim, Soo-Seok
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2007.11a
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    • pp.319-322
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    • 2007
  • In the development of paralleling techniques, Multi-Phase Interleaved(MPI) converter constitutes one of the most promising alternatives reported in the last years. This technique consists of a phase shifting of the control signals of several cells in parallel operating at the same switching frequency. As a result, the aggregated input and output current waveform exhibit lower ripple amplitude and smaller harmonics content than in synchronous or stochastic operation modes. Based on the inherent advantages of the MPI converter, in this paper, a control scheme, which can reduce current and voltage rifle, is proposed for PEMFC generation systems. The MPI boost converter is composed of several identical boost converters connected in parallel.

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A Generation of Synthetic Monthly Streamflows in the Han River Basin by Disaggregation Model (한강수계에 있어서 분해모형에 의한 모의 월유량 발생)

  • 강관수;선우중호
    • Water for future
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    • v.20 no.2
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    • pp.107-116
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    • 1987
  • The stochastic model has been developed for synthetic generation of hydrologic series that would be needed in the analysis, planning, design and operation of water resources system. In this study, after generating the yearly streamflows by multisite AR(1) model using the historical data in the Han River Basin, the monthly streamflows is generated by the disaggregation model. The model is verified of its applicability to domestic rivers, which is obtained through the statistical analysis and good ness of fit test using synthetic streamflows generated.

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Unit Commitment of a Microgrid Considering Islanded Operation Scenarios (독립운전 시나리오를 고려한 마이크로그리드의 최적 발전기 기동정지 계획)

  • Lee, Si Young
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.6
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    • pp.708-714
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    • 2018
  • Islanded operation of a microgrid can ensure the reliable operation of the system when a large accident occurs in the main grid. However, because the generation capability of a microgrid is typically limited, a microgrid operator should take islanded operation risk into account in scheduling its generation resources. To address this problem, in this paper we have proposed two unit commitment formulations based on the islanding scenario that reflect the expected and worst-case values of the islanded operation risk. An optimal resource scheduling strategy is obtained for the microgrid operator by solving these optimization problem, and the effectiveness of the proposed method is investigated by numerical simulations.

Studies on the Stochastic Generation of Synthetic Streamflow Sequences(I) -On the Simulation Models of Streamflow- (하천유량의 추계학적 모의발생에 관한 연구(I) -하천유량의 Simulation 모델에 대하여-)

  • 이순탁
    • Water for future
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    • v.7 no.1
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    • pp.71-77
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    • 1974
  • This paper reviews several different single site generation models for further development of a model for generating the Synthetic sequences of streamflow in the continuous streams like main streams in Korea. Initially the historical time series is looked using a time series technique, that is correlograms, to determine whether a lag one Markov model will satisfactorily represent the historical data. The single site models which were examined include an empirical model using the historical probability distribution of the random component, the linear autoregressive model(Markov model, or Thomas-Fiering model) using both logarithms of the data and Matala's log-normal transformation equations, and finally gamma distribution model.

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A Study on Generation of Stochastic Rainfall Variation using Multivariate Monte Carlo method (다변량 Monte Carlo 기법을 이용한 추계학적 강우 변동 생성기법에 관한 연구)

  • Ahn, Ki-Hong;Han, Kun-Yeun
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.3
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    • pp.127-133
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    • 2009
  • In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

A Study on Real-time State Estimation for Smart Microgrids (스마트 마이크로그리드 실시간 상태 추정에 관한 연구)

  • Bae, Jun-Hyung;Lee, Sang-Woo;Park, Tae-Joon;Lee, Dong-Ha;Kang, Jin-Kyu
    • 한국태양에너지학회:학술대회논문집
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    • 2012.03a
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    • pp.419-424
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    • 2012
  • This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

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Application of Rainwater Harvesting System Reliability Model Based on Non-parametric Stochastic Daily Rainfall Generator to Haundae District of Busan (비모수적 추계학적 일 강우 발생기 기반의 빗물이용시설 신뢰도 평가모형의 부산광역시 해운대 신시가지 적용)

  • Choi, ChiHyun;Park, MooJong;Baek, ChunWoo;Kim, SangDan
    • Journal of Korean Society on Water Environment
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    • v.27 no.5
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    • pp.634-645
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    • 2011
  • A newly developed rainwater harvesting (RWH) system reliability model is evaluated for roof area of buildings in Haeundae District of Busan. RWH system is used to supply water for toilet flushing, back garden irrigation, and air cooling. This model is portable because it is based on a non-parametric precipitation generation algorithm using a markov chain. Precipitation occurrence is simulated using transition probabilities derived for each day of the year based on the historical probability of wet and dry day state changes. Precipitation amounts are selected from a matrix of historical values within a moving 30 day window that is centered on the target day. Then, the reliability of RWH system is determined for catchment area and tank volume ranges using synthetic precipitation data. As a result, the synthetic rainfall data well reproduced the characteristics of precipitation in Busan. Also the reliabilities of RWH system for each of demands were computed to high values. Furthermore, for study area using the RWH system, reduction efficiencies for rooftop runoff inputs to the sewer system and potable water demand are evaluated for 23%, 53%, respectively.

Big Data and Knowledge Generation in Tertiary Education in the Philippines

  • Fadul, Jose A.
    • Journal of Contemporary Eastern Asia
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    • v.13 no.1
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    • pp.5-18
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    • 2014
  • This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

Measurement-Based Stochastic Cross-Correlation Models of a Multilink Channel in Cooperative Communication Environments

  • Park, Jae-Joon;Kim, Myung-Don;Kwon, Heon-Kook;Chung, Hyun Kyu;Yin, Xuefeng;Fu, Yaoyao
    • ETRI Journal
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    • v.34 no.6
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    • pp.858-868
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    • 2012
  • In this paper, stochastic models for the cross-correlation of multiple channels are established based on measurement data collected using a wideband multiple-input multiple-output relay Band Exploration and Channel Sounder system at 3.7 GHz. We propose models for the cross-correlation characteristics of large-scale parameters (LSPs) between two links, that is, the base station and mobile station (MS) link and the relay station and MS link. The LSPs include shadow fading, Rician K-factor, delay spread, angle spread of arrival, and angle spread of departure. Furthermore, models are established for the cross-correlation of the small-scale fading in the impulse responses of two links. The statistics of these model parameters are investigated as functions of geometrical features of the multilink. They are extracted from a large amount of cross-correlation observations, which are obtained in three measurement sites along more than one hundred measurement routes. These models can be used together with the standard single-link channel models for the generation of correlated components, for example, path clusters, in two separate channels.

Component Procurement Planning with Demand Uncertainty Under Assemble-to-Order Environments (불확실한 수요를 갖는 주문 조립 환경에서의 부품 조달 계획에 관한 연구)

  • Lee, Geun-Cheol;Kim, Jung-Ug;Hong, Jung Man
    • Korean Management Science Review
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    • v.29 no.3
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    • pp.121-134
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    • 2012
  • In this study, we consider a component procurement planning problem where the procurement amounts of components are determined under assemble-to-order systems with demand uncertainty. In the problem, procurement amount of each component is decided before the demands of finished products are known and after the demands are identified the assembly amounts of the finished products are decided. In this study, the objective function of the problem is minimizing the total costs which are composed of purchase and inventory costs of the components and the backorder costs of the finished products. We assume that the uncertain demand information is given as multiple scenarios of the demands, and we propose procurement planning methods based on stochastic models which considering the multiple demand scenarios. To evaluate the performances of the proposed methods, computational experiments were carried out on the proposed methods as well as benchmarks including a method based on deterministic mathematical model and a heuristic. From the results of the computational tests, the superiorities of the proposed methods were shown.