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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    

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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    

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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    

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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

《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    

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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    

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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    

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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

《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    

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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    

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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    

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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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基于TLBO算法的不确定性条件下复杂产品协同设计的可靠性拓扑优化

洪兆溪, 蒋翔宇, 冯毅雄, 田钦羽, 谭建荣

《工程（英文）》 2023年 第22卷 第3期   页码 71-81 doi: 10.1016/j.eng.2021.06.027

摘要：

复杂产品的拓扑优化设计可以显著改善材料和节能，有效地降低惯性力和机械振动。本研究选择了一种大吨位液压机作为典型的复杂产品，用以表述这种优化方法。基于可靠性和优化解耦模型与基于教与学优化（TLBO）算法，本文提出了一种可靠性拓扑优化方法。将由板系结构形成的支撑物作为拓扑优化对象，具有轻量化和稳定性好的特点。将某种不确定性下的可靠性优化和结构拓扑优化协同处理。首先，利用有限差分法将优化问题中的不确定性参数修正为确定性参数。然后，将不确定性可靠性分析和拓扑优化的复杂嵌套解耦。最后，利用TLBO算法求解解耦模型。该算法参数少，求解速度快。TLBO算法采用了自适应教学因子，在初始阶段实现了更快的收敛速度，并在后期阶段进行了更精细的搜索。本文给出了一个液压机基板结构的数值实例，验证了该方法的有效性。

关键词： 板系结构     可靠性     协同拓扑优化     教与学优化算法     不确定性     产品生命周期的协同设计    

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Multiresolution and multimaterial topology optimization of fail-safe structures under B-spline spaces

《机械工程前沿（英文）》 2023年 第18卷 第4期 doi: 10.1007/s11465-023-0768-9

摘要： This study proposes a B-spline-based multiresolution and multimaterial topology optimization (TO) design method for fail-safe structures (FSSs), aiming to achieve efficient and lightweight structural design while ensuring safety and facilitating the postprocessing of topological structures. The approach involves constructing a multimaterial interpolation model based on an ordered solid isotropic material with penalization (ordered-SIMP) that incorporates fail-safe considerations. To reduce the computational burden of finite element analysis, we adopt a much coarser analysis mesh and finer density mesh to discretize the design domain, in which the density field is described by the B-spline function. The B-spline can efficiently and accurately convert optimized FSSs into computer-aided design models. The 2D and 3D numerical examples demonstrate the significantly enhanced computational efficiency of the proposed method compared with the traditional SIMP approach, and the multimaterial TO provides a superior structural design scheme for FSSs. Furthermore, the postprocessing procedures are significantly streamlined.

关键词： multiresolution     multimaterial     topology optimization     fail-safe structure     B-spline    

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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    

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Robust topology optimization of hinge-free compliant mechanisms with material uncertainties based on

Junjie ZHAN, Yangjun LUO

《机械工程前沿（英文）》 2019年 第14卷 第2期   页码 201-212 doi: 10.1007/s11465-019-0529-y

摘要： This paper presents a new robust topology optimization framework for hinge-free compliant mechanisms with spatially varying material uncertainties, which are described using a non-probabilistic bounded field model. Bounded field uncertainties are efficiently represented by a reduced set of uncertain-but-bounded coefficients on the basis of the series expansion method. Robust topology optimization of compliant mechanisms is then defined to minimize the variation in output displacement under constraints of the mean displacement and predefined material volume. The nest optimization problem is solved using a gradient-based optimization algorithm. Numerical examples are presented to illustrate the effectiveness of the proposed method for circumventing hinges in topology optimization of compliant mechanisms.

关键词： compliant mechanisms     robust topology optimization     hinges     uncertainty     bounded field    

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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

《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    

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标题 作者 时间 类型 操作

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

Zunaira Asif, Zhi Chen

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

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

Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

期刊论文

Energy systems engineering: methodologies and applications

Pei LIU, Efstratios N. PISTIKOPOULOS, Zheng 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

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

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

Review of stochastic optimization methods for smart grid

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

期刊论文

基于TLBO算法的不确定性条件下复杂产品协同设计的可靠性拓扑优化

洪兆溪, 蒋翔宇, 冯毅雄, 田钦羽, 谭建荣

期刊论文

Multiresolution and multimaterial topology optimization of fail-safe structures under B-spline spaces

期刊论文

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

期刊论文

Robust topology optimization of hinge-free compliant mechanisms with material uncertainties based on

Junjie ZHAN, Yangjun LUO

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