资源类型

期刊论文 490

会议视频 21

年份

2023 40

2022 42

2021 54

2020 39

2019 50

2018 24

2017 33

2016 25

2015 26

2014 16

2013 10

2012 19

2011 11

2010 20

2009 13

2008 24

2007 16

2006 9

2005 5

2004 4

展开 ︾

关键词

不确定性 9

能源 4

优化调度 3

智能制造 3

不确定性评估 2

人工智能 2

人才培养 2

优化 2

可持续发展 2

可靠性 2

工业4.0 2

桥梁工程 2

泥水盾构 2

生产调度 2

砂卵石地层 2

细水雾 2

规划 2

2020全球工程前沿 1

Backbone 1

展开 ︾

检索范围：

排序： 展示方式：

A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

《能源前沿（英文）》 2023年 第17卷 第2期   页码 198-210 doi: 10.1007/s11708-023-0874-8

摘要： The increasing use of distributed energy resources changes the way to manage the electricity system. Unlike the traditional centralized powered utility, many homes and businesses with local electricity generators have established their own microgrids, which increases the use of renewable energy while introducing a new challenge to the management of the microgrid system from the mismatch and unknown of renewable energy generations, load demands, and dynamic electricity prices. To address this challenge, a rank-based multiple-choice secretary algorithm (RMSA) was proposed for microgrid management, to reduce the microgrid operating cost. Rather than relying on the complete information of future dynamic variables or accurate predictive approaches, a lightweight solution was used to make real-time decisions under uncertainties. The RMSA enables a microgrid to reduce the operating cost by determining the best electricity purchase timing for each task under dynamic pricing. Extensive experiments were conducted on real-world data sets to prove the efficacy of our solution in complex and divergent real-world scenarios.

关键词： energy management systems     demand response     scheduling under uncertainty     renewable energy sources     multiple-choice secretary algorithm    

HTML PDF 收藏

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

《能源前沿（英文）》 doi: 10.1007/s11708-023-0912-6

摘要： With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energy sources (RESs) has become a trend in the industry. However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids. In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimization, and intraday real-time correction. The day-ahead optimization stage aims at the lowest operating cost, the rolling optimization stage aims at the lowest intraday economic cost, and the real-time correction aims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale optimization. The simulation results show that the economic loss is reduced by 19.6%, and the power fluctuation is decreased by 15.23%.

关键词： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed power supply     landscape uncertainty    

HTML PDF 收藏

Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

《能源前沿（英文）》 2013年 第7卷 第4期   页码 468-478 doi: 10.1007/s11708-013-0282-6

摘要： In a competitive and deregulated power scenario, the utilities try to maintain their real electric power generation in balance with the load demand, which creates a need for the precise real time generation scheduling (GS). In this paper, the GS problem is solved to perform the unit commitment (UC) based on frequency prediction by using artificial neural network (ANN) with the objective to minimize the overall system cost of the state utility. The introduction of availability-based tariff (ABT) signifies the importance of frequency in GS. Under-prediction or over-prediction will result in an unnecessary commitment of generating units or buying power from central generating units at a higher cost. Therefore, an accurate frequency prediction is the first step toward optimal GS. The dependency of frequency on various parameters such as actual generation, load demand, wind power and power deficit has been considered in this paper. The proposed technique provides a reliable solution for the input parameter different from the one presented in the training data. The performance of the frequency predictor model has been evaluated based on the absolute percentage error (APE) and the mean absolute percentage error (MAPE). The proposed predicted frequency sensitive GS model is applied to the system of Indian state of Tamilnadu, which reduces the overall system cost of the state utility by keeping off the dearer units selected based on the predicted frequency.

关键词： artificial neural network (ANN)     frequency prediction     availability-based tariff (ABT)     generation scheduling (GS)    

HTML PDF 收藏

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

《环境科学与工程前沿（英文）》 2019年 第13卷 第5期 doi: 10.1007/s11783-019-1156-x

摘要： Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM2.5, PM10, NOx, SO2 and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.

关键词： Air pollution     Decision analysis     Linear programming     Mining     Optimization     Fuzzy     Monte Carlo    

HTML PDF 收藏

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

《能源前沿（英文）》 2021年 第15卷 第1期   页码 186-200 doi: 10.1007/s11708-019-0644-9

摘要： In this paper, interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling. First of all, interval numbers are used to describe uncertain parameters including hot water demand, ambient temperature, and real-time price of electricity. Moreover, the traditional thermal dynamic model of electric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling problem with uncertain parameters is formulated, and solved by interval number optimization. Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices. Furthermore, the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day. Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand, ambient temperature, and real-time price of electricity, enabling customers to flexibly adjust electric water heater control strategy.

关键词： electric water heater     load scheduling     interval number optimization     model predictive control     uncertainty    

HTML PDF 收藏

Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

《结构与土木工程前沿（英文）》 2019年 第13卷 第6期   页码 1510-1519 doi: 10.1007/s11709-019-0577-8

摘要： Performance-based seismic design can generate predictable structure damage result with given seismic hazard. However, there are multiple sources of uncertainties in the seismic design process that can affect desired performance predictability. This paper mainly focuses on the effects of near-fault pulse-like ground motions and the uncertainties in bridge modeling on the seismic demands of regular continuous highway bridges. By modeling a regular continuous bridge with OpenSees software, a series of nonlinear dynamic time-history analysis of the bridge at three different site conditions under near-fault pulse-like ground motions are carried out. The relationships between different Intensity Measure (IM) parameters and the Engineering Demand Parameter (EDP) are discussed. After selecting the peak ground acceleration as the most correlated IM parameter and the drift ratio of the bridge column as the EDP parameter, a probabilistic seismic demand model is developed for near-fault earthquake ground motions for 3 different site conditions. On this basis, the uncertainty analysis is conducted with the key sources of uncertainty during the finite element modeling. All the results are quantified by the “swing” base on the specific distribution range of each uncertainty parameter both in near-fault and far-fault cases. All the ground motions are selected from PEER database, while the bridge case study is a typical regular highway bridge designed in accordance with the Chinese Guidelines for Seismic Design of Highway Bridges. The results show that PGA is a proper IM parameter for setting up a linear probabilistic seismic demand model; damping ratio, pier diameter and concrete strength are the main uncertainty parameters during bridge modeling, which should be considered both in near-fault and far-fault ground motion cases.

关键词： continuous bridge     probabilistic seismic demand model     Intensity Measure     near-fault     uncertainty    

HTML PDF 收藏

Robust topology optimization of multi-material lattice structures under material and load uncertainties

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

《机械工程前沿（英文）》 2019年 第14卷 第2期   页码 141-152 doi: 10.1007/s11465-019-0531-4

摘要： Enabled by advancements in multi-material additive manufacturing, lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide array of functions. This work proposes a density-based robust topology optimization method for meso- or macro-scale multi-material lattice structures under any combination of material and load uncertainties. The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials, and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertainty. By formulating the objective function as a weighted sum of the mean and standard deviation of compliance, the tradeoff between optimality and robustness can be studied and controlled. Examples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit the efficiency and flexibility of the approach. The accuracy of univariate dimension reduction is validated by comparing the results to the Monte Carlo approach.

关键词： robust topology optimization     lattice structures     multi-material     material uncertainty     load uncertainty     univariate dimension reduction    

HTML PDF 收藏

Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 852-862 doi: 10.1007/s11709-019-0522-x

摘要： Due to an increased need in hydro-electricity, water storage, and flood protection, it is assumed that a series of new dams will be build throughout the world. The focus of this paper is on the non-probabilistic-based design of new arch-type dams by applying means of robust design optimization (RDO). This type of optimization takes into account uncertainties in the loads and in the material properties of the structure. As classical procedures of probabilistic-based optimization under uncertainties, such as RDO and reliability-based design optimization (RBDO), are in general computationally expensive and rely on estimates of the system’s response variance, we will not follow a full-probabilistic approach but work with predefined confidence levels. This leads to a bi-level optimization program where the volume of the dam is optimized under the worst combination of the uncertain parameters. As a result, robust and reliable designs are obtained and the result is independent from any assumptions on stochastic properties of the random variables in the model. The optimization of an arch-type dam is realized here by a robust optimization method under load uncertainty, where hydraulic and thermal loads are considered. The load uncertainty is modeled as an ellipsoidal expression. Comparing with any traditional deterministic optimization method, which only concerns the minimum objective value and offers a solution candidate close to limit-states, the RDO method provides a robust solution against uncertainty. To reduce the computational cost, a ranking strategy and an approximation model are further involved to do a preliminary screening. By this means, the robust design can generate an improved arch dam structure that ensures both safety and serviceability during its lifetime.

关键词： arch dam     shape optimization     robust optimization     load uncertainty     approximation model    

HTML PDF 收藏

Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

《农业科学与工程前沿（英文）》 2015年 第2卷 第3期   页码 205-215 doi: 10.15302/J-FASE-2015073

摘要： The main characteristic of the water resources system (WRS) is its great complexity and uncertainty, which makes it highly desirable to carry out a risk analysis of the WRS. The natural environmental, social economic conditions as well as limitations of human cognitive ability are possible sources of the uncertainties that need to be taken into account in the risk analysis process. In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS are discussed first, from both objective and subjective perspectives. Then the quantitative characterization methods of risk analysis are introduced, including three criteria (reliability, resiliency and vulnerability) and five basic optimization models (the expected risk value model, conditional value at risk model, chance-constrained risk model, minimizing probability of risk events model, and the multi-objective optimization model). Finally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized as random, fuzzy and mixed methods. A more comprehensive risk analysis methodology for the WRS is proposed based on the comparison of the advantages, disadvantages and applicable conditions of these three methods. This paper provides a decision support of risk analysis for researchers, policy makers and stakeholders of the WRS.

关键词： water resources system     evaluation criterion     optimization model     risk analysis method     uncertainty    

HTML PDF 收藏

An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

《环境科学与工程前沿（英文）》 2012年 第6卷 第4期   页码 549-558 doi: 10.1007/s11783-012-0414-y

摘要： In this study, an interval fuzzy mixed-integer energy planning model (IFMI-EPM) is developed under considering the carbon tax policy. The developed IFMI-EPM incorporates techniques of interval-parameter programming, fuzzy planning and mixed-integer programming within a general energy planning model. The IFMI-EPM can not only be used for quantitatively analyzing a variety of policy scenarios that are associated with different levels of carbon tax policy, but also tackle uncertainties expressed as discrete intervals and fuzzy sets in energy and environment systems. Considering low, medium and high carbon tax rates, the model is applied to an ideal energy and environment system. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired carbon tax policy.

关键词： energy     carbon tax     planning     uncertainty     fuzzy    

HTML PDF 收藏

Real option-based optimization for financial incentive allocation in infrastructure projects under public–private

Shuai LI, Da HU, Jiannan CAI, Hubo CAI

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 413-425 doi: 10.1007/s42524-019-0045-0

摘要： Financial incentives that stimulate energy investments under public–private partnerships are considered scarce public resources, which require deliberate allocation to the most economically justified projects to maximize the social benefits. This study aims to solve the financial incentive allocation problem through a real option-based nonlinear integer programming approach. Real option theory is leveraged to determine the optimal timing and the corresponding option value of providing financial incentives. The ambiguity in the evolution of social benefits, the decision-maker’s attitude toward ambiguity, and the uncertainty in social benefits and incentive costs are all considered. Incentives are offered to the project portfolio that generates the maximum total option value. The project portfolio selection is formulated as a stochastic knapsack problem with random option values in the objective function and random incentive costs in the probabilistic budget constraint. The linear probabilistic budget constraint is subsequently transformed into a nonlinear deterministic one. Finally, the integer non-linear programming problem is solved, and the optimality gap is computed to assess the quality of the optimal solution. A case study is presented to illustrate how the limited financial incentives can be optimally allocated under uncertainty and ambiguity, which demonstrates the efficacy of the proposed method.

关键词： financial incentives     public–private partnerships     energy infrastructure projects     real option     optimization     uncertainty    

HTML PDF 收藏

Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints

Quanxiao FANG, Liwang MA, Lajpat Rai AHUJA, Thomas James TROUT, Robert Wayne MALONE, Huihui ZHANG, Dongwei GUI, Qiang YU

《农业科学与工程前沿（英文）》 2017年 第4卷 第2期   页码 172-184 doi: 10.15302/J-FASE-2017139

摘要： Due to varying crop responses to water stress at different growth stages, scheduling irrigation is a challenge for farmers, especially when water availability varies on a monthly, seasonal and yearly basis. The objective of this study was to optimize irrigation between the vegetative (V) and reproductive (R) phases of maize under different available water levels in Colorado. Long-term (1992–2013) scenarios simulated with the calibrated Root Zone Water Quality Model were designed to meet 40%–100% of crop evapotranspiration (ET) requirements at V and R phases, subject to seasonal water availabilities (300, 400, 500 mm, and no water limit), with and without monthly limits (total of 112 scenarios). The most suitable irrigation between V and R phases of maize was identified as 60/100, 80/100, and 100/100 of crop ET requirement for the 300, 400, 500 mm water available, respectively, based on the simulations from 1992 to 2013. When a monthly water limit was imposed, the corresponding suitable irrigation targets between V and R stages were 60/100, 100/100, and 100/100 of crop ET requirement for the above three seasonal water availabilities, respectively. Irrigation targets for producing higher crop yield with reduced risk of poor yield were discussed for projected five-year water availabilities.

关键词： RZWQM     ET-based irrigation schedule     maize     water constrains    

HTML PDF 收藏

Energy systems engineering: methodologies and applications

Pei LIU, Efstratios N. PISTIKOPOULOS, Zheng LI

《能源前沿（英文）》 2010年 第4卷 第2期   页码 131-142 doi: 10.1007/s11708-010-0035-8

摘要： Energy systems are the major contributor to ever-increasing primary energy consumption and consequent greenhouse gas emissions. To tackle these critical problems, planning and design of energy systems needs to be improved towards a more efficient, cost-effective, and environmentally benign direction. However, although there are many technical choices available, they are often developed separately by their own technical communities and driven by their specific interest, thus methods and experience obtained in planning and design of a certain type of energy systems are usually not applicable to other types of energy systems. Energy systems engineering provides a generic methodological framework to facilitate the planning and design of energy systems and to produce integrated solutions to real-life complex energy problems via a systematic approach.In this paper, we present an overview of key methodologies of energy systems engineering, covering superstructure based modelling, mixed-integer programming, multi-objective optimization, optimization under uncertainty, and life-cycle assessment. Applications of these methodologies in polygeneration energy systems design, hydrogen infrastructure planning, and design of energy systems in commercial buildings are provided to demonstrate the capability of these methodologies.

关键词： energy systems engineering     superstructure     mixed-integer programming     multi-objective optimization     optimization under uncertainty     life-cycle assessment    

HTML PDF 收藏

不确定条件下采用精确参数规划的非线性模型过程操作

Vassilis M. Charitopoulos,Lazaros G. Papageorgiou,Vivek Dua

《工程（英文）》 2017年 第3卷 第2期   页码 202-213 doi: 10.1016/J.ENG.2017.02.008

摘要：

本文提出了新的两(多) 参数规划(mp-P) 启发算法以求解混合整数非线性规划(MINLP) 问题，并着重说明了算法在过程综合问题中的应用。对于因对数项导致的非线性，开发了针对确定性问题的参数算法(p-MINLP)。关键之处是通过将二进制变量和(或) 不确定参数作为符号参数重新生成和求解一阶Karush Kuhn Tucker(KKT) 系统的解析表达式。为此，采用了符号处理和求解技术。为了证明所提出的算法的适用性和有效性，对两个过程综合案例研究进行了验证，相应的结果经最新的数值MINLP 求解器验证是有效的。对于p-MINLP，给出了不确定参数的显函数表示的最优解。

关键词： 参数规划     不确定性     过程综合     混合整数非线性规划     符号操作    

HTML PDF 收藏

Development and challenges of planning and scheduling for petroleum and petrochemical production

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 373-383 doi: 10.1007/s42524-020-0123-3

摘要： Production planning and scheduling are becoming the core of production management, which support the decision of a petrochemical company. The optimization of production planning and scheduling is attempted by every refinery because it gains additional profit and stabilizes the daily production. The optimization problem considered in industry and academic research is of different levels of realism and complexity, thus increasing the gap. Operation research with mathematical programming is a conventional approach used to address the planning and scheduling problem. Additionally, modeling the processes, objectives, and constraints and developing the optimization algorithms are significant for industry and research. This paper introduces the perspective of production planning and scheduling from the development viewpoint.

关键词： planning and scheduling     optimization     modeling    

HTML PDF 收藏

标题 作者 时间 类型 操作

A rank-based multiple-choice secretary algorithm for minimising microgrid operating cost under uncertainties

期刊论文

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

期刊论文

Optimal generation scheduling in power system using frequency prediction through ANN under ABT environment

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

期刊论文

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

期刊论文

MPC-based interval number optimization for electric water heater scheduling in uncertain environments

Jidong WANG, Chenghao LI, Peng LI, Yanbo CHE, Yue ZHOU, Yinqi LI

期刊论文

Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

期刊论文

Robust topology optimization of multi-material lattice structures under material and load uncertainties

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

期刊论文

Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

期刊论文

Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

期刊论文

An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

期刊论文

Real option-based optimization for financial incentive allocation in infrastructure projects under public–private

Shuai LI, Da HU, Jiannan CAI, Hubo CAI

期刊论文

Long-term simulation of growth stage-based irrigation scheduling in maize under various water constraints

Quanxiao FANG, Liwang MA, Lajpat Rai AHUJA, Thomas James TROUT, Robert Wayne MALONE, Huihui ZHANG, Dongwei GUI, Qiang YU

期刊论文

Energy systems engineering: methodologies and applications

Pei LIU, Efstratios N. PISTIKOPOULOS, Zheng LI

期刊论文

不确定条件下采用精确参数规划的非线性模型过程操作

Vassilis M. Charitopoulos,Lazaros G. Papageorgiou,Vivek Dua

期刊论文

Development and challenges of planning and scheduling for petroleum and petrochemical production

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

期刊论文