• 제목/요약/키워드: stochastic simulation.

검색결과 786건 처리시간 0.024초

Development of ESS Scheduling Algorithm to Maximize the Potential Profitability of PV Generation Supplier in South Korea

  • Kong, Junhyuk;Jufri, Fauzan Hanif;Kang, Byung O;Jung, Jaesung
    • Journal of Electrical Engineering and Technology
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    • 제13권6호
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    • pp.2227-2235
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    • 2018
  • Under the current policies and compensation rules in South Korea, Photovoltaic (PV) generation supplier can maximize the profit by combining PV generation with Energy Storage System (ESS). However, the existing operational strategy of ESS is not able to maximize the profit due to the limitation of ESS capacity. In this paper, new ESS scheduling algorithm is introduced by utilizing the System Marginal Price (SMP) and PV generation forecasting to maximize the profits of PV generation supplier. The proposed algorithm determines the charging time of ESS by ranking the charging schedule from low to high SMP when PV generation is more than enough to charge ESS. The discharging time of ESS is determined by ranking the discharging schedule from high to low SMP when ESS energy is not enough to maintain the discharging. To compensate forecasting error, the algorithm is updated every hour to apply the up-to-date information. The simulation is performed to verify the effectiveness of the proposed algorithm by using actual PV generation and ESS information.

모멘트 생성 함수 기법을 이용한 물류 운반 시스템 이용에 따른 유연 생산 시스템의 성능 해석 (Performance Analysis of the Flexible Manufacturing System According to the Strategy of Material Handling System Using Moment Generating Function Based Approach)

  • 양희구;김종원
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.1186-1190
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    • 1995
  • This paper is focused on the formulation of explicit closed-form functions describing the performance measures of the general flexible manufacturing system (FMS)according to the strategy of material handling system(MHS). the performance measures such as the production rate, the production lead-time and the utilization rate of the general FMS are expressed, respectively, as the explicit closed-form functions of the part processing time, the service rate of the material handling system (MHS) and the number of machine tools in the FMS. For this, the gensral FMS is presented as a generalized stochastic Petri net model, then, the moment generating function (MGF) based approach is applied to obtain the steady-state probabity formulation. Based on the steady-state formulation, the explicit closed-form functions for performance measures of the probability FMS can be obtained. Finally, the analytical results are compared with the Petri net simulation results to verify the validity of the suggested method. The paper is of significance in the sense that it provides a comprehensive formula for performance measures of the FMS even to the industry engineers and academic reademic resuarchers who have no background on Markov chain analysis method or Petrinet modeling

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모델 변환법을 이용한 점핑 로봇 제어의 운동경로 생성에 관한 연구 (A Study on Motion Planning Generation of Jumping Robot Control Using Model Transformation Method)

  • 서진호;산북창의;이권순
    • 한국정밀공학회지
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    • 제21권4호
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    • pp.120-131
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    • 2004
  • In this paper, we propose the method of a motion planning generation in which the movement of the 3-link leg subsystem is constrained to a slider-link and a singular posture can be easily avoided. The proposed method is the jumping control moving in vertical direction which mimics a cat's behavior. That is, it is jumping toward wall and kicking it to get a higher-place. Considering the movement from the point of constraint mechanical system, the robotic system which realizes the motion changes its configuration according to the position and it has several phases such as; ⅰ) an one-leg phase, ⅱ) in an air-phase. In other words, the system is under nonholonomic constraint due to the reservation of its momentum. Especially, in an air-phase, we will use a control method using state transformation and linearization in order to control the landing posture. Also, an iterative learning control algorithm is applied in order to improve the robustness of the control. The simulation results for jumping control will illustrate the effectiveness of the proposed control method.

자동창고시스템의 성능평가를 위한 M/G/1 대기모형 (M/G/1 Queueing Model for the Performance Estimation of AS/RS)

  • 임시영;허선;이문환;이영해
    • 대한산업공학회지
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    • 제27권1호
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    • pp.111-117
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    • 2001
  • Most of the techniques for the performance estimation of unit-load AS/RS are a static model or computer simulation. Especially, their models have been developed under the assumption that the Storage/Retrieval (S/R) machine performs either single command(SC) or dual command(DC) only. In reality, depending on the operating policy and the status of the system at a particular time, the S/R machine performs a SC or a DC, or becomes idle. In order to resolve this weak point, we propose a stochastic model for the performance estimation of unit-load ASIRS by using a M/G/1 queueing model with a single server and two queues. Server utilization, expected numbers of waiting storage and retrieval commands and mean time spent in queue and system are found.

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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
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    • 제12권5호
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    • pp.1709-1718
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    • 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.

LonWorks-IP 가상 디바이스 네트워크상에서 예지 및 예방보전을 위한 DC 서보모터의 분산제어 (Distributed Control of DC Servo Motor on LonWorks-IP Virtual Device Network for Predictive and Preventive Maintenance)

  • 송기원
    • 한국안전학회지
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    • 제21권4호
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    • pp.25-32
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    • 2006
  • LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

Stochastic thermo-mechanically induced post buckling response of elastically supported nanotube-reinforced composite beam

  • Chaudhari, Virendra Kumar;Shegokar, Niranjan L.;Lal, Achchhe
    • Advances in aircraft and spacecraft science
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    • 제4권5호
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    • pp.585-611
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    • 2017
  • This article covenants with the post buckling witticism of carbon nanotube reinforced composite (CNTRC) beam supported with an elastic foundation in thermal atmospheres with arbitrary assumed random system properties. The arbitrary assumed random system properties are be modeled as uncorrelated Gaussian random input variables. Unvaryingly distributed (UD) and functionally graded (FG) distributions of the carbon nanotube are deliberated. The material belongings of CNTRC beam are presumed to be graded in the beam depth way and appraised through a micromechanical exemplary. The basic equations of a CNTRC beam are imitative constructed on a higher order shear deformation beam (HSDT) theory with von-Karman type nonlinearity. The beam is supported by two parameters Pasternak elastic foundation with Winkler cubic nonlinearity. The thermal dominance is involved in the material properties of CNTRC beam is foreseen to be temperature dependent (TD). The first and second order perturbation method (SOPT) and Monte Carlo sampling (MCS) by way of CO nonlinear finite element method (FEM) through direct iterative way are offered to observe the mean, coefficient of variation (COV) and probability distribution function (PDF) of critical post buckling load. Archetypal outcomes are presented for the volume fraction of CNTRC, slenderness ratios, boundary conditions, underpinning parameters, amplitude ratios, temperature reliant and sovereign random material properties with arbitrary system properties. The present defined tactic is corroborated with the results available in the literature and by employing MCS.

경로 탐색 기법과 강화학습을 사용한 주먹 지르기동작 생성 기법 (Punching Motion Generation using Reinforcement Learning and Trajectory Search Method)

  • 박현준;최위동;장승호;홍정모
    • 한국멀티미디어학회논문지
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    • 제21권8호
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    • pp.969-981
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    • 2018
  • Recent advances in machine learning approaches such as deep neural network and reinforcement learning offer significant performance improvements in generating detailed and varied motions in physically simulated virtual environments. The optimization methods are highly attractive because it allows for less understanding of underlying physics or mechanisms even for high-dimensional subtle control problems. In this paper, we propose an efficient learning method for stochastic policy represented as deep neural networks so that agent can generate various energetic motions adaptively to the changes of tasks and states without losing interactivity and robustness. This strategy could be realized by our novel trajectory search method motivated by the trust region policy optimization method. Our value-based trajectory smoothing technique finds stably learnable trajectories without consulting neural network responses directly. This policy is set as a trust region of the artificial neural network, so that it can learn the desired motion quickly.

용존산소 농도모의시 상태공간모형과 승법 ARIMA모형의 시계열 분석 (Time series Analysis of State-space Model and Multiplication ARIMA Model in Dissolved Oxygen Simulation)

  • 이원호;서인석;한양수
    • 환경위생공학
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    • 제15권2호
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    • pp.65-74
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    • 2000
  • The purpose of this study is to develop the stochastic stream water quality model for the intake station of Chung-Ju city waterworks in the Han river system. This model was based on the theory of Box-Jenkins Multiplicative ARIMA(SARIMA) and the state space model to simulate changes of water qualities. Variable of water qualities included in the model are temperature and dissolved oxygen(DO). The models development were based on the data obtained from Jan. 1990 to Dec. 1997 and followed the typical procedures of the Box-Jenkins method including identification and estimation. The seasonality of DO and temperature data to formulate for the SARIMA model are conspicuous and the period of revolution was twelve months. Both models had seasonality of twelve months and were formulates as SARIMA {TEX}$(2,1,1)(1,1,1)_{12}${/TEX} for DO and temperature. The models were validated by testing normality and independency of the residuals. The prediction ability of SARIMA model and state space model were tested using the data collected from Jan. 1998 to Oct. 1999. There were good agreements between the model predictions and the field measurements. The performance of the SARIMA model and state space model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the state space model lead to the improved accuracy.

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선형화 오차에 강인한 확장칼만필터 (An Extended Kalman Filter Robust to Linearization Error)

  • 혼형수;이장규;박찬국
    • 제어로봇시스템학회논문지
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    • 제12권2호
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    • pp.93-100
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    • 2006
  • In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.