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

Frontiers in Energy 2023, Volume 17, Issue 2,   Pages 198-210 doi: 10.1007/s11708-023-0874-8

Abstract: variables or accurate predictive approaches, a lightweight solution was used to make real-time decisions undermicrogrid to reduce the operating cost by determining the best electricity purchase timing for each task under

Keywords： energy management systems     demand response     scheduling under uncertainty     renewable energy sources     multiple-choice    

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

Frontiers in Energy doi: 10.1007/s11708-023-0912-6

Abstract: However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power gridsIn this paper, a multi-timescale optimal scheduling model is established for interconnected data centers

Keywords： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributedpower supply     landscape uncertainty    

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

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Frontiers in Energy 2013, Volume 7, Issue 4,   Pages 468-478 doi: 10.1007/s11708-013-0282-6

Abstract: generation in balance with the load demand, which creates a need for the precise real time generation schedulingUnder-prediction or over-prediction will result in an unnecessary commitment of generating units or buying

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

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

Zunaira Asif, Zhi Chen

Frontiers of Environmental Science & Engineering 2019, Volume 13, Issue 5, doi: 10.1007/s11783-019-1156-x

Abstract: 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.

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

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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

Frontiers in Energy 2021, Volume 15, Issue 1,   Pages 186-200 doi: 10.1007/s11708-019-0644-9

Abstract: predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load schedulingelectric water heater is transformed into an interval number model, based on which, the day-ahead load scheduling

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

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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

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 6,   Pages 1510-1519 doi: 10.1007/s11709-019-0577-8

Abstract: series of nonlinear dynamic time-history analysis of the bridge at three different site conditions underOn this basis, the uncertainty analysis is conducted with the key sources of uncertainty during the finiteAll the results are quantified by the “swing” base on the specific distribution range of each uncertaintyprobabilistic seismic demand model; damping ratio, pier diameter and concrete strength are the main uncertainty

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

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

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 2,   Pages 141-152 doi: 10.1007/s11465-019-0531-4

Abstract: density-based robust topology optimization method for meso- or macro-scale multi-material lattice structures undermaterials, and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertaintyExamples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit

Keywords： robust topology optimization     lattice structures     multi-material     material uncertainty     load uncertainty    

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Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4,   Pages 852-862 doi: 10.1007/s11709-019-0522-x

Abstract: As classical procedures of probabilistic-based optimization under uncertainties, such as RDO and reliability-basedThis leads to a bi-level optimization program where the volume of the dam is optimized under the worstThe optimization of an arch-type dam is realized here by a robust optimization method under load uncertaintyThe load uncertainty is modeled as an ellipsoidal expression.offers a solution candidate close to limit-states, the RDO method provides a robust solution against uncertainty

Keywords： arch dam     shape optimization     robust optimization     load uncertainty     approximation model    

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Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

Frontiers of Agricultural Science and Engineering 2015, Volume 2, Issue 3,   Pages 205-215 doi: 10.15302/J-FASE-2015073

Abstract: The main characteristic of the water resources system (WRS) is its great complexity and uncertainty,In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS areFinally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized

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

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An uncertain energy planning model under carbon taxes

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

Frontiers of Environmental Science & Engineering 2012, Volume 6, Issue 4,   Pages 549-558 doi: 10.1007/s11783-012-0414-y

Abstract: In this study, an interval fuzzy mixed-integer energy planning model (IFMI-EPM) is developed under considering

Keywords： energy     carbon tax     planning     uncertainty     fuzzy    

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

Shuai LI, Da HU, Jiannan CAI, Hubo CAI

Frontiers of Engineering Management 2020, Volume 7, Issue 3,   Pages 413-425 doi: 10.1007/s42524-019-0045-0

Abstract: Financial incentives that stimulate energy investments under public–private partnerships are consideredambiguity in the evolution of social benefits, the decision-maker’s attitude toward ambiguity, and the uncertaintycase study is presented to illustrate how the limited financial incentives can be optimally allocated underuncertainty and ambiguity, which demonstrates the efficacy of the proposed method.

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

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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

Frontiers of Agricultural Science and Engineering 2017, Volume 4, Issue 2,   Pages 172-184 doi: 10.15302/J-FASE-2017139

Abstract: Due to varying crop responses to water stress at different growth stages, scheduling irrigation is athis study was to optimize irrigation between the vegetative (V) and reproductive (R) phases of maize under

Keywords： RZWQM     ET-based irrigation schedule     maize     water constrains    

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Energy systems engineering: methodologies and applications

Pei LIU, Efstratios N. PISTIKOPOULOS, Zheng LI

Frontiers in Energy 2010, Volume 4, Issue 2,   Pages 131-142 doi: 10.1007/s11708-010-0035-8

Abstract: superstructure based modelling, mixed-integer programming, multi-objective optimization, optimization underuncertainty, and life-cycle assessment.

Keywords： systems engineering     superstructure     mixed-integer programming     multi-objective optimization     optimization underuncertainty     life-cycle assessment    

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Nonlinear Model-Based Process Operation under Uncertainty Using Exact Parametric Programming

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

Engineering 2017, Volume 3, Issue 2,   Pages 202-213 doi: 10.1016/J.ENG.2017.02.008

Abstract:

In the present work, two new, (multi-)parametric programming (mp-P)-inspired algorithms for the solution of mixed-integer nonlinear programming (MINLP) problems are developed, with their main focus being on process synthesis problems. The algorithms are developed for the special case in which the nonlinearities arise because of logarithmic terms, with the first one being developed for the deterministic case, and the second for the parametric case (p-MINLP). The key idea is to formulate and solve the square system of the first-order Karush-Kuhn-Tucker (KKT) conditions in an analytical way, by treating the binary variables and/or uncertain parameters as symbolic parameters. To this effect, symbolic manipulation and solution techniques are employed. In order to demonstrate the applicability and validity of the proposed algorithms, two process synthesis case studies are examined. The corresponding solutions are then validated using state-of-the-art numerical MINLP solvers. For p-MINLP, the solution is given by an optimal solution as an explicit function of the uncertain parameters.

Keywords： Parametric programming     Uncertainty     Process synthesis     Mixed-integer nonlinear programming     Symbolic manipulation    

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

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

Frontiers of Engineering Management 2020, Volume 7, Issue 3,   Pages 373-383 doi: 10.1007/s42524-020-0123-3

Abstract: Production planning and scheduling are becoming the core of production management, which support theThe optimization of production planning and scheduling is attempted by every refinery because it gainsresearch with mathematical programming is a conventional approach used to address the planning and schedulingThis paper introduces the perspective of production planning and scheduling from the development viewpoint

Keywords： planning and scheduling     optimization     modeling    

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Title Author Date Type Operation

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

Journal Article

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

Journal Article

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

Simarjit KAUR, Yajvender Pal VERMA, Sunil AGRAWAL

Journal Article

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

Zunaira Asif, Zhi Chen

Journal Article

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

Journal Article

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

Journal Article

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

Yu-Chin CHAN, Kohei SHINTANI, Wei CHEN

Journal Article

Shape design of arch dams under load uncertainties with robust optimization

Fengjie TAN, Tom LAHMER

Journal Article

Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

Journal Article

An uncertain energy planning model under carbon taxes

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

Journal Article

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

Shuai LI, Da HU, Jiannan CAI, Hubo CAI

Journal Article

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

Journal Article

Energy systems engineering: methodologies and applications

Pei LIU, Efstratios N. PISTIKOPOULOS, Zheng LI

Journal Article

Nonlinear Model-Based Process Operation under Uncertainty Using Exact Parametric Programming

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

Journal Article

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

Fupei LI, Minglei YANG, Wenli DU, Xin DAI

Journal Article