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A solution to stochastic unit commitment problem for a wind-thermal system coordination

B. SARAVANAN,Shreya MISHRA,Debrupa NAG

《能源前沿（英文）》 2014年第8卷第2期页码 192-200 doi: 10.1007/s11708-014-0306-x

摘要： Unit commitment (UC) problem is one of the most important decision making problems in power system. In this paper the UC problem is solved by considering it as a real time problem by adding stochasticity in the generation side because of wind-thermal co-ordination system as well as stochasticity in the load side by incorporating the randomness of the load. The most important issue that needs to be addressed is the achievement of an economic unit commitment solution after solving UC as a real time problem. This paper proposes a hybrid approach to solve the stochastic unit commitment problem considering the volatile nature of wind and formulating the UC problem as a chance constrained problem in which the load is met with high probability over the entire time period.

关键词： unit commitment (UC) randomness wind generation univariate chance constrained

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A solution to the unit commitment problem—a review

B. SARAVANAN, Siddharth DAS, Surbhi SIKRI, D. P. KOTHARI

《能源前沿（英文）》 2013年第7卷第2期页码 223-236 doi: 10.1007/s11708-013-0240-3

摘要： Unit commitment (UC) is an optimization problem used to determine the operation schedule of the generating units at every hour interval with varying loads under different constraints and environments. Many algorithms have been invented in the past five decades for optimization of the UC problem, but still researchers are working in this field to find new hybrid algorithms to make the problem more realistic. The importance of UC is increasing with the constantly varying demands. Therefore, there is an urgent need in the power sector to keep track of the latest methodologies to further optimize the working criterions of the generating units. This paper focuses on providing a clear review of the latest techniques employed in optimizing UC problems for both stochastic and deterministic loads, which has been acquired from many peer reviewed published papers. It has been divided into many sections which include various constraints based on profit, security, emission and time. It emphasizes not only on deregulated and regulated environments but also on renewable energy and distributed generating systems. In terms of contributions, the detailed analysis of all the UC algorithms has been discussed for the benefit of new researchers interested in working in this field.

关键词： unit commitment (UC) optimization deterministic load stochastic load evolutionary programming (EP) hybrid

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Robust ensemble of metamodels based on the hybrid error measure

《机械工程前沿（英文）》 2021年第16卷第3期页码 623-634 doi: 10.1007/s11465-021-0641-7

摘要： Metamodels have been widely used as an alternative for expensive physical experiments or complex, time-consuming computational simulations to provide a fast but accurate analysis. However, challenge remains in the prior determination of the most suitable metamodel for a particular case because of the lack of information about the actual behavior of a system. In addition, existing studies on metamodels have largely restricted on solving deterministic problems (e.g., data from finite element models), whereas some real-life engineering problems (e.g., data from physical experiment) are stochastic problems with noisy data. In this work, a robust ensemble of metamodels (EMs) is proposed by combining three regression stand-alone metamodels in a weighted sum form. The weight factor is adaptively determined according to the hybrid error metric, which combines global and local error measures to improve the accuracy of the EMs. Furthermore, three typical individual metamodels that can filter noise are selected to construct the EMs to extend their application in practical engineering problems. Three well-known benchmark problems with different levels of noise and three engineering problems are used to verify the effectiveness of the proposed EMs. Results show that the proposed EMs have higher accuracy and robustness than the individual metamodels and other typical EMs in major cases.

关键词： metamodel ensemble of metamodels hybrid error measure stochastic problem

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随机环境中的自主水下航行器鲁棒全局路径规划 Research Article

张佳欣1,2,刘妹琴1,2,3,张森林1,2,郑荣濠1,2

《信息与电子工程前沿（英文）》 2022年第23卷第11期页码 1658-1672 doi: 10.1631/FITEE.2200026

摘要：

本文提出一种在随机局部路径成本下使自主水下航行器在作业海域选择性地完成部分预定任务的路径规划器。该问题被表述为定向越野问题的变体。本文在遗传算法（GA）的基础上，提出一种基于贪心策略的遗传算法（GGA）。该算法包含一种新颖的通过在进化过程中将不可行个体映射到可行解空间来提高优化效率的重生算子，并以差分进化规划器计算确定性局部路径成本。局部路径成本的不确定性来自不可预测的障碍物、测量误差和轨迹跟踪误差。为了提高规划器在不确定环境下的鲁棒性，设计了一种用于路径评估的采样策略，通过对局部路径的概率密度函数多次采样，得到对路径实际成本的估计。通过蒙特卡罗仿真实验验证所提规划器的优越性和有效性。仿真结果表明，所提出的GGA在总收益方面优于同类算法4.7%–¬¬24.6%，而基于抽样的GGA路径规划器（S-GGARP）相较于普通的GGA路径规划器（GGARP）提高了5.5%的平均收益。

关键词：自主水下航行器；路径规划；遗传算法；定向越野问题；随机路径成本

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Special Column on Multiscale Stochastic Finite Element Method

《结构与土木工程前沿（英文）》 2015年第9卷第2期页码 105-106 doi: 10.1007/s11709-015-0297-7

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Stochastic analysis of laminated composite plate considering stochastic homogenization problem

S. SAKATA,K. OKUDA,K. IKEDA

《结构与土木工程前沿（英文）》 2015年第9卷第2期页码 141-153 doi: 10.1007/s11709-014-0286-2

摘要： This paper discusses a multiscale stochastic analysis of a laminated composite plate consisting of unidirectional fiber reinforced composite laminae. In particular, influence of a microscopic random variation of the elastic properties of component materials on mechanical properties of the laminated plate is investigated. Laminated composites are widely used in civil engineering, and therefore multiscale stochastic analysis of laminated composites should be performed for reliability evaluation of a composite civil structure. This study deals with the stochastic response of a laminated composite plate against the microscopic random variation in addition to a random variation of fiber orientation in each lamina, and stochastic properties of the mechanical responses of the laminated plate is investigated. Halpin-Tsai formula and the homogenization theory-based finite element analysis are employed for estimation of effective elastic properties of lamina, and the classical laminate theory is employed for analysis of a laminated plate. The Monte-Carlo simulation and the first-order second moment method with sensitivity analysis are employed for the stochastic analysis. From the numerical results, importance of the multiscale stochastic analysis for reliability evaluation of a laminated composite structure and applicability of the sensitivity-based approach are discussed.

关键词： stochastic homogenization multiscale stochastic analysis microscopic random variation laminated composite plate

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Application of an efficient stochastic calculation method on the seismic analysis of an isolated structure

Wei GUO, Zhiwu YU

《结构与土木工程前沿（英文）》 2012年第6卷第4期页码 379-384 doi: 10.1007/s11709-012-0180-8

摘要： An isolated structure often possesses distinct non-proportional damping characteristics. However, traditional seismic calculation theory and methods are derived based on the assumption that damping is proportional. Based on this drawback, a new, more efficient stochastic calculation method, an improvement on the pseudo-excitation method, is introduced. This method is then applied to the seismic analysis of an isolated structure. By comparing it with the forced decoupling, matrix inversion and iteration methods, it is shown that the presented method can produce accurate results while increasing the efficiency of the stochastic analysis. Moreover, the calculation process of the seismic response of an isolated structure is convergent. Based on the results of the example presented in this paper, the given method is applicable to the seismic analysis of an isolated structure and can be utilized in practice.

关键词： isolated structure stochastic response non-proportional damping efficient accurate pseudo-excitation method

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Hierarchical modeling of stochastic manufacturing and service systems

Zhe George ZHANG, Xiaoling YIN

《工程管理前沿（英文）》 2017年第4卷第3期页码 295-303 doi: 10.15302/J-FEM-2017047

摘要： This paper presents a review of methodologies for analyzing stochastic manufacturing and service systems. On the basis of the scale and level of details of operations, we can study stochastic systems using micro-, meso-, and macro-scopic models. Such a classification unifies stochastic modeling theory. For each model type, we highlight the advantages and disadvantages and the applicable situations. Micro-scopic models are based on quasi-birth-and-death process because of the phase-type distributed service times and/or Markov arrival processes. Such models are appropriate for modeling the detailed operations of a manufacturing system with relatively small number of servers (production facilities). By contrast, meso-scopic and macro-scopic models are based on the functional central limit theorem (FCLT) and functional strong law of large numbers (FSLLN), respectively, under heavy-traffic regimes. These high-level models are appropriate for modeling large-scale service systems with many servers, such as call centers or large service networks. This review will help practitioners select the appropriate level of modeling to enhance their understanding of the dynamic behavior of manufacturing or service systems. Enhanced understanding will ensure that optimal policies can be designed to improve system performance. Researchers in operation analytics and optimization of manufacturing and logistics also benefit from such a review.

关键词： stochastic modeling QBD process PH distribution heavy traffic limits diffusion process

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Discrete-event stochastic systems with correlated inputs: Modeling and performance evaluation

《工程管理前沿（英文）》 2022年第9卷第2期页码 214-220 doi: 10.1007/s42524-022-0192-6

摘要： In the majority of the previous works on discrete-event stochastic systems, they have been assumed to have independent input processes. However, in many applications, these input processes can be highly correlated. Furthermore, the performance measures of the systems with correlated inputs can be significantly different from those with independent inputs. In this paper, we provide an overview on some commonly used methods for modeling correlated input processes, and we discuss the difficulties and possible future research topics in the study of discrete-event stochastic systems with correlated inputs.

关键词： discrete-event stochastic system correlated input performance evaluation

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Applying the spectral stochastic finite element method in multiple-random field RC structures

Abbas YAZDANI

《结构与土木工程前沿（英文）》 2022年第16卷第4期页码 434-447 doi: 10.1007/s11709-022-0820-6

摘要： This paper uses the spectral stochastic finite element method (SSFEM) for analyzing reinforced concrete (RC) beam/slab problems. In doing so, it presents a new framework to study how the correlation length of a random field (RF) with uncertain parameters will affect modeling uncertainties and reliability evaluations. It considers: 1) different correlation lengths for uncertainty parameters, and 2) dead and live loads as well as the elasticity moduli of concrete and steel as a multi-dimensional RF in concrete structures. To show the SSFEM’s efficiency in the study of concrete structures and to evaluate the sensitivity of the correlation length effects in evaluating the reliability, two examples of RC beams and slabs have been investigated. According to the results, the RF correlation length is effective in modeling uncertainties and evaluating reliabilities; the longer the correlation length, the greater the dispersion range of the structure response and the higher the failure probability.

关键词： uncertainty spectral stochastic finite element method correlation length reliability assessment reinforced concrete beam/slab

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Review of stochastic optimization methods for smart grid

S. Surender REDDY, Vuddanti SANDEEP, Chan-Mook JUNG

《能源前沿（英文）》 2017年第11卷第2期页码 197-209 doi: 10.1007/s11708-017-0457-7

摘要： This paper presents various approaches used by researchers for handling the uncertainties involved in renewable energy sources, load demands, etc. It gives an idea about stochastic programming (SP) and discusses the formulations given by different researchers for objective functions such as cost, loss, generation expansion, and voltage/V control with various conventional and advanced methods. Besides, it gives a brief idea about SP and its applications and discusses different variants of SP such as recourse model, chance constrained programming, sample average approximation, and risk aversion. Moreover, it includes the application of these variants in various power systems. Furthermore, it also includes the general mathematical form of expression for these variants and discusses the mathematical description of the problem and modeling of the system. This review of different optimization techniques will be helpful for smart grid development including renewable energy resources (RERs).

关键词： renewable energy sources stochastic optimization smart grid uncertainty optimal power flow (OPF)

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An efficient stochastic dynamic analysis of soil media using radial basis function artificial neural

P. ZAKIAN

《结构与土木工程前沿（英文）》 2017年第11卷第4期页码 470-479 doi: 10.1007/s11709-017-0440-8

摘要： Since a lot of engineering problems are along with uncertain parameters, stochastic methods are of great importance for incorporating random nature of a system property or random nature of a system input. In this study, the stochastic dynamic analysis of soil mass is performed by finite element method in the frequency domain. Two methods are used for stochastic analysis of soil media which are spectral decomposition and Monte Carlo methods. Shear modulus of soil is considered as a random field and the seismic excitation is also imposed as a random process. In this research, artificial neural network is proposed and added to Monte Carlo method for sake of reducing computational effort of the random analysis. Then, the effects of the proposed artificial neural network are illustrated on decreasing computational time of Monte Carlo simulations in comparison with standard Monte Carlo and spectral decomposition methods. Numerical verifications are provided to indicate capabilities, accuracy and efficiency of the proposed strategy compared to the other techniques.

关键词： stochastic analysis random seismic excitation finite element method artificial neural network frequency domain analysis Monte Carlo simulation

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Robust train speed trajectory optimization: A stochastic constrained shortest path approach

Li WANG, Lixing YANG, Ziyou GAO, Yeran HUANG

《工程管理前沿（英文）》 2017年第4卷第4期页码 408-417 doi: 10.15302/J-FEM-2017042

摘要： Train speed trajectory optimization is a significant issue in railway traffic systems, and it plays a key role in determining energy consumption and travel time of trains. Due to the complexity of real-world operational environments, a variety of factors can lead to the uncertainty in energy-consumption. To appropriately characterize the uncertainties and generate a robust speed trajectory, this study specifically proposes distance-speed networks over the inter-station and treats the uncertainty with respect to energy consumption as discrete sample-based random variables with correlation. The problem of interest is formulated as a stochastic constrained shortest path problem with travel time threshold constraints in which the expected total energy consumption is treated as the evaluation index. To generate an approximate optimal solution, a Lagrangian relaxation algorithm combined with dynamic programming algorithm is proposed to solve the optimal solutions. Numerical examples are implemented and analyzed to demonstrate the performance of proposed approaches.

关键词： train speed trajectory optimization railway operation stochastic programming

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Discussion on Problem-Based Engineering Management System

Qiao Xiang

《工程管理前沿（英文）》 2015年第2卷第3期页码 249-260 doi: 10.15302/J-FEM-2015054

摘要： The paper puts forward the idea of problem-based engineering management, expounds its connotation and guiding ideology and moreover, substantially demonstrates its practical significance in the engineering management system for the maintenance of Chinese military aircraft engines.

关键词： problem engineering management system

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Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent

Pankaj SHARMA,Ajai JAIN

《机械工程前沿（英文）》 2014年第9卷第4期页码 380-389 doi: 10.1007/s11465-014-0315-9

摘要：

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 % and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.

关键词： scheduling stochastic dynamic job shop sequence-dependent setup times dispatching rule simulation