• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• 한국군사과학기술학회지
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• 제16권5호
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• pp.631-638
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• 2013

The probabilistic fatigue life analysis is one of the common methods to account the uncertainty of parameters on the structural failure. Frequently, the Bayesian approach has been demonstrated as a proper method to show the uncertainty of parameters. In this work, the application of probabilistic fatigue life prediction method for the aircraft structure was studied. This effort was conducted by using the PoF(Probability of Failure) based on Bayesian approach. Furthermore, numerical example was carried out to confirm the validation of the suggested approach. In conclusion, it was shown that the Bayesian approach can calculate the probabilistic fatigue lives and the quantitative value of PoF effectively for the aircraft structural component. Moreover the calculated probabilistic fatigue lives can be utilized to determine the optimized inspection period of aircraft structures.

• International Journal of Concrete Structures and Materials
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• 제19권1E호
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• pp.11-16
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• 2007

Recently, probabilistic neural network (PNN) has been proposed to predict the compressive strength of concrete for the known effect of improvement on PNN by the iteration method. However, an empirical method has been incorporated in the PNN technique to specify its smoothing parameter, which causes significant uncertainty in predicting the compressive strength of concrete. In this study, a modified probabilistic neural network (MPNN) approach is hence proposed. The global probability density function (PDF) of variables is reflected by summing the heterogeneous local PDFs which are automatically determined by the individual standard deviation of each variable. The proposed MPNN is applied to predict the compressive strength of concrete using actual test data from a concrete company. The estimated results of MPNN are compared with those of the conventional PNN. MPNN showed better results than the conventional PNN in predicting the compressive strength of concrete and provided promising results for the probabilistic approach to predict the concrete strength by using the individual standard deviation of a variable.

• 산업기술연구
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• 제22권B호
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• pp.231-240
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• 2002

The rational method of estimating peak flow is used largely for the simplicity. But the accuracy of rational method is not easy to estimate, because the rational method is analyzed by the deterministic point or view and the runoff coefficients of the rational method are proposed from other countries. In this study the rational method is analyzed by the probabilistic way to be a more reliable method. The runoff coefficient is regarded to parameter that changes the probabilistic rainfall to the peak flow. The runoff coeffient for each return period is analyzed to be a reliable index which is used to estimate the peak flow of ungauged natural catchments.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.65-70
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• 2008

The capacity spectrum method (CSM) is a deterministic seismic analysis approach wherein the expected seismic response of a structure is established as the intersection of the demand and capacity curves. Recently, there are a few studies about a probabilistic CSM where uncertainties in design factors such as material properties, loads, and ground motion are being considered. However, researches show that soil-structure interaction also affects the seismic responses of structures. Thus, their uncertainties should also be taken into account. Therefore, this paper presents a probabilistic approach of using the CSM for seismic analysis considering uncertainties in soil properties. For application, a reinforced concrete bridge column structure is employed as a test model. Considering the randomness of the various design parameters, the structure's probability of failure is obtained. Monte Carlo importance sampling is used as the tool to assess the structure's reliability when subjected to earthquakes. In this study, probabilistic CSM with and without consideration of soil uncertainties are compared and analyzed. Results show that the analysis considering soil structure interaction yields to a greater probability of failure, and thus can lead to a more conservative structural design.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1832-1842
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• 2014

A novel probabilistic small signal stability analysis (PSSSA) method considering load correlation is proposed in this paper. The superiority Latin hypercube sampling (LHS) technique combined with Monte Carlo simulation (MCS) is utilized to investigate the probabilistic small signal stability of power system in presence of load correlation. LHS helps to reduce the sampling size, meanwhile guarantees the accuracy and robustness of the solutions. The correlation coefficient matrix is adopted to represent the correlations between loads. Simulation results of the two-area, four-machine system prove that the proposed method is an efficient and robust sampling method. Simulation results of the 16-machine, 68-bus test system indicate that load correlation has a significant impact on the probabilistic analysis result of the critical oscillation mode under a certain degree of load uncertainty.

• 한국환경과학회지
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• 제22권8호
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• 한국산학기술학회논문지
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• 제13권1호
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• pp.382-389
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• 2012

위조된 보고서 공격은 무선 센서 네트워크에서 이벤트가 발생한 위치에 대한 송신 응답과 같은 거짓 경보를 야기하는 것뿐만 아니라 제한된 량의 에너지를 고갈시킨다. 본 논문에서는 위조된 보고서를 필터링하기 위해 확률적인 보안 필터링 기법(PFSS: Probabilistic Filtering method for Sensor network Security)을 제안한다. 제안 내용은 클러스터 헤드와 기지국과의 거리를 이용하여 기지국까지의 중간 클러스터 헤드가 검증 노드인지를 확률적으로 선택하여 보안 검증에 필요한 에너지를 줄이고, 보안 처리에 따른 핫 스팟 문제를 완화시킨다. 제안된 기법의 성능은 수식 분석과 실험을 통하여 분석하였으며, 이를 통하여 제안된 기법이 기존의 보안 검증 처리에 비해 효율적임을 알 수 있다.

• 대한전기학회논문지:전력기술부문A
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• 제50권9호
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• pp.431-439
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• 2001

This Paper illustrates a new numerical analysis method using a nodal effective load model for nodal probabilistic production cost simulation of the load point in a composite power system. The new effective load model includes capacities and uncertainties of generators as well as transmission lines. The CMELDC(composite power system effective load duration curve) based on the new effective load model at HLll(Hierarchical Level H) has been developed also. The CMELDC can be obtained from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. It is expected that the new model for the CMELDC proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems under competition environment in future. The CMELDC based on the new model at HLll will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of MRBTS(Modified Roy Billinton Test System).

• 전자공학회논문지CI
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• 제39권4호
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• pp.28-37
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• 2002

본 논문에서는, 확률적 방법과 질의 위치 이동 방법을 융합하여 검색 성능을 향상시키는 영상검색 방법을 제안한다. 제안한 알고리즘은, 질의 영상과 데이터베이스 영상 사이의 유사도 계산에서, 확률적 방법의 유사도와 질의 위치 이동 방법의 유사도를 융합한다. 본 논문에서 이용된 확률적 방법은 부정적 예제들을 다루기에 적합하다. 반면에, 질의 위치 이동 방법은 긍정적예제의 통계적인 특성을 다룬다. 본 논문의 목적은 이러한 두 방법을 융합함으로써, 각각의 방법이 가지고 있는 단점을 극복하는 것이다. 실험결과는 제안한 방법이 확률적 방법과 질의 위치 이동 방법을 각각 적용한 경우보다 더 나은 성능을 나타낸다는 것을 보여준다.