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| 1 | Robust optimization for improving resilience of integrated energy systems with electricity and natural gas infrastructures显示文摘The integration of natural gas in electricity network requires a more reliable operating plan for increasing uncertainties in the whole system. In this paper, a threestage robust optimization model is proposed for resilient operation of energy system which integrates electricity and natural gas transmission networks with the objective of minimizing load curtailments caused by attacks. Nonconvex constrains are linearized in order to formulate the dual problem of optimal energy flow. Then, the proposed three-stage problem can be reformulated into a two-stage mixed integer linear program(MILP) and solved by Benders decomposition algorithm. Numerical studies on IEEE30-bus power system with 7-node natural gas network and IEEE 118-bus power system with 14-node natural gas network validate the feasibility of the proposed model for improving resilience of integrated energy system. Energy storage facilities are also considered for the resiliency analysis. | Hao CONG Yang HE Xu WANG Chuanwen JIANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，5： | 17 |
| 2 | Reliability-based Robust Optimization Design of Automobile Components with Non-normal Distribution Parameters显示文摘In the reliability designing procedure of the vehicle components, when the distribution styles of the random variables are unknown or non-normal distribution, the result evaluated contains great error or even is wrong if the reliability value R is larger than 1 by using the existent method, in which case the formula is necessary to be revised. This is obviously inconvenient for programming. Combining reliability-based optimization theory, robust designing method and reliability based sensitivity analysis, a new method for reliability robust designing is proposed. Therefore the influence level of the designing parameters' changing to the reliability of vehicle components can be obtained. The reliability sensitivity with respect to design parameters is viewed as a sub-objective function in the multi-objective optimization problem satisfying reliability constraints. Given the first four moments of basic random variables, a fourth-moment technique and the proposed optimization procedure can obtain reliability-based robust design of automobile components with non-normal distribution parameters accurately and quickly. By using the proposed method, the distribution style of the random parameters is relaxed. Therefore it is much closer to the actual reliability problems. The numerical examples indicate the following: (1) The reliability value obtained by the robust method proposed increases (>0.04%) comparing to the value obtained by the ordinary optimization algorithm; (2) The absolute value of reliability-based sensitivity decreases (>0.01%), and the robustness of the products' quality is improved accordingly. Utilizing the reliability-based optimization and robust design method in the reliability designing procedure reduces the manufacture cost and provides the theoretical basis for the reliability and robust design of the vehicle components. | YANG Zhou ZHANG Yimin HUANG Xianzhen ZHANG Xufang TANG Le | 2013 | Chinese Journal of Mechanical Engineering2013，26，4： | 14 |
| 3 | A robust optimization method for energy management of CCHP microgrid显示文摘Energy management is facing new challenges due to the increasing supply and demand uncertainties,which is caused by the integration of variable generation resources,inaccurate load forecasts and non-linear efficiency curves.To meet these challenges,a robust optimization method incorporating piecewise linear thermal and electrical efficiency curve is proposed to accommodate the uncertainties of cooling,thermal and electrical load,as well as photovoltaic(PV)output power.Case study results demonstrate that the robust optimization model performs better than the deterministic optimization model in terms of the expected operation cost.The fluctuation of net electrical load has greater effect on the dispatching results of the combined cooling,heating and power(CCHP)microgrid than the fluctuation of the cooling and thermal load.The day-ahead schedule is greatly affected by the uncertainty budget of the load demand.The economy of the optimal decision could be achieved by adjusting different uncertainty budget levels according to control the conservatism of the model. | Zhao LUO Wei GU Zhi WU Zhihe WANG Yiyuan TANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，1： | 12 |
| 4 | Robust topology optimization of hinge-free compliant mechanisms with material uncertainties based on a non-probabilistic field model显示文摘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-bouncled coeflficients 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. | Junjie ZHAN Yangjun LUO | 2019 | Frontiers of Mechanical Engineering2019，14，2： | 5 |
| 5 | Multi-objective robust airfoil optimization based on non-uniform rational B-spline (NURBS) representation显示文摘In order to improve airfoil performance under different flight conditions and to make the performance insensitive to off-design condition at the same time,a multi-objective optimization approach considering robust design has been developed and applied to airfoil design. Non-uniform rational B-spline (NURBS) representation is adopted in airfoil design process,control points and related weights around airfoil are used as design variables. Two airfoil representation cases show that the NURBS method can get airfoil geometry with max geometry error less than 0.0019. By using six-sigma robust approach in multi-objective airfoil design,each sub-objective function of the problem has robustness property. By adopting multi-objective genetic algorithm that is based on non-dominated sorting,a set of non-dominated airfoil solutions with robustness can be obtained in the design. The optimum robust airfoil can be traded off and selected in these non-dominated solutions by design tendency. By using the above methods,a multi-objective robust optimization was conducted for NASA SC0712 airfoil. After performing robust airfoil optimization,the mean value of drag coefficient at Ma0.7-0.8 and the mean value of lift coefficient at post stall regime (Ma0.3) have been improved by 12.2% and 25.4%. By comparing the aerodynamic force coefficients of optimization result,it shows that: different from single robust airfoil design which just improves the property of drag divergence at Ma0.7-0.8,multi-objective robust design can improve both the drag divergence property at Ma0.7-0.8 and stall property at low speed. The design cases show that the multi-objective robust design method makes the airfoil performance robust under different off-design conditions. | LIANG Yu, CHENG XiaoQuan, LI ZhengNeng & XIANG JinWu School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China | 2010 | Science China(Technological Sciences)2010，53，10： | 4 |
| 6 | Robust single machine scheduling problem with uncertain job due dates for industrial mass production显示文摘The single machine scheduling problem which involves uncertain job due dates is one of the most important issues in the real make-to-order environment. To deal with the uncertainty, this paper establishes a robust optimization model by minimizing the maximum tardiness in the worst case scenario over all jobs. Unlike the traditional stochastic programming model which requires exact distributions, our model only needs the information of due date intervals. The worst case scenario for a given sequence that belongs to a set containing only n scenarios is proved, where n is the number of jobs. Then, the model is simplified and reformulated as an equivalent mixed 0-1 integer linear programming(MILP) problem. To solve the MILP problems efficiently, a heuristic approach is proposed based on a robust dominance rule. The experimental results show that the proposed method has the advantages of robustness and high calculating efficiency, and it is feasible for large-scale problems. | YUE Fan SONG Shiji JIA Peng WU Guangping ZHAO Han | 2020 | Journal of Systems Engineering and Electronics2020，31，2： | 4 |
| 7 | Six sigma robust design optimization for thermal protection system of hypersonic vehicles based on successive response surface method显示文摘Lightweight design is important for the Thermal Protection System(TPS) of hypersonic vehicles in that it protects the inner structure from severe heating environment. However, due to the existence of uncertainties in material properties and geometry, it is imperative to incorporate uncertainty analysis into the design optimization to obtain reliable results. In this paper, a six sigma robust design optimization based on Successive Response Surface Method(SRSM) is established for the TPS to improve the reliability and robustness with considering the uncertainties. The uncertain parameters related to material properties and thicknesses of insulation layers are considered and characterized by random variables following normal distributions. By employing SRSM, the values of objective function and constraints are approximated by the response surfaces to reduce computational cost. The optimization is an iterative process with response surfaces updating to find the true optimal solution. The optimization of the nose cone of hypersonic vehicle cabin is provided as an example to illustrate the feasibility and effectiveness of the proposed method. | Jingjing ZHU Xiaojun WANG Haiguo ZHANG Yuwen LI Ruixing WANG Zhiping QIU | 2019 | Chinese Journal of Aeronautics2019，32，9： | 4 |
| 8 | Aircraft robust multidisciplinary design optimization methodology based on fuzzy preference function显示文摘This paper presents a Fuzzy Preference Function-based Robust Multidisciplinary Design Optimization(FPF-RMDO) methodology. This method is an effective approach to multidisciplinary systems, which can be used to designer experiences during the design optimization process by fuzzy preference functions. In this study, two optimizations are done for Predator MQ-1 Unmanned Aerial Vehicle(UAV):(A) deterministic optimization and(B) robust optimization. In both problems, minimization of takeoff weight and drag is considered as objective functions, which have been optimized using Non-dominated Sorting Genetic Algorithm(NSGA). In the robust design optimization, cruise altitude and velocity are considered as uncertainties that are modeled by the Monte Carlo Simulation(MCS) method. Aerodynamics, stability and control, mass properties, performance, and center of gravity are used for multidisciplinary analysis. Robust design optimization results show 46% and 42% robustness improvement for takeoff weight and cruise drag relative to optimal design respectively. | Ali Reza BABAEI Mohammad Reza SETAYANDEH Hamid FARROKHFAL | 2018 | Chinese Journal of Aeronautics2018，31，12： | 3 |
| 9 | Hybrid genetic algorithm for a type-Ⅱ robust mixed-model assembly line balancing problem with interval task times显示文摘The typemixed-model assembly line balancing problem with uncertain task times is a critical problem. This paper addresses this issue of practical significance to production efficiency. Herein, a robust optimization model for this problem is formulated to hedge against uncertainty. Moreover, the counterpart of the robust optimization model is developed by duality. A hybrid genetic algorithm (HGA) is proposed to solve this problem. In this algorithm, a heuristic method is utilized to seed the initial population. In addition, an adaptive local search procedure and a discrete Levy flight are hybridized with the genetic algorithm (GA) to enhance the performance of the algorithm. The effectiveness of the HGA is tested on a set of benchmark instances. Furthermore, the effect of uncertainty parameters on production efficiency is also investigated. | Jia-Hua Zhang Ai-Ping Li Xue-Mei Liu | 2019 | Advances in Manufacturing2019，7，2： | 2 |
| 10 | A two-level hierarchical discrete-device control method for power networks with integrated wind farms显示文摘Power systems depend on discrete devices, such as shunt capacitors/reactors and on-load tap changers, for their long-term reliability.In transmission systems that contain large wind farms, we must take into account the uncertainties in wind power generation when deciding when to operate these devices.In this paper, we describe a method to schedule the operation of these devices over the course of the following day.These schedules are designed to minimize wind-power generation curtailment, bus voltage violations, and dynamic reactive-power deviations,even under the worst possible conditions.Daily voltagecontrol decisions are initiated every 15 min using a dynamic optimization algorithm that predicts the state of the system over the next 4-hour period.For this, forecasts updated in real-time are employed, because they are more precise than forecasts for the day ahead.Day-ahead schedules are calculated using a two-stage robust mixedinteger optimization algorithm.The proposed control strategies were tested on a Chinese power network with wind power sources; the control performance was also validated numerically. | Fengda XU Qinglai GUO Hongbin SUN Boming ZHANG Lin JIA | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，1： | 2 |
| 11 | A comprehensive energy solution for households employing a micro combined cooling,heating and power generation system显示文摘In recent years,micro combined cooling, heating and power generation (mCCHP)systems have attracted much attention in the energy demand side sector. The input energy ofa mCCHP system is natural gas,while the outputs include heating,cooling and electricity energy. The mCCHP system is deemed as a possible solution for households with multiple energy demands.Given this background,a mCCHP based comprehensive energy solution for households is proposed in this paper.First, the mathematical model of a home energy hub (HEH)is presented to describe the inputs,outputs,conversion and consumption process of multiple energies in households. Then,electrical loads and thermal demands are classified and modeled in detail,and the coordination and complementation between electricity and natural gas are studied. Afterwards,the concept of thermal comfort is introduced and a robust optimization model for HEH is developed considering electricity price uncertainties.Finally,a household using a mCCI-IP as the energy conversion device is studied.The simulation results show that the comprehensive energy solution proposed in this work can realize multiple kinds of energy supplies for households with the minimized total energy cost. | Huayi ZHANG Can ZHANG Fushuan WEN Yan XU | 2018 | Frontiers in Energy2018，12，4： | 1 |
| 12 | Robust topology optimization of multi-material lattice structures under material and load uncertainties显示文摘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 macroscale 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. | Yu-Chin CHAN Kohei SHINTANI Wei CHEN | 2019 | Frontiers of Mechanical Engineering2019，14，2： | 1 |
| 13 | Adjustable and distributionally robust chance-constrained economic dispatch considering wind power uncertainty显示文摘This paper proposes an adjustable and distributionally robust chance-constrained(ADRCC) optimal power flow(OPF) model for economic dispatch considering wind power forecasting uncertainty. The proposed ADRCC-OPF model is distributionally robust because the uncertainties of the wind power forecasting are represented only by their first-and second-order moments instead of a specific distribution assumption. The proposed model is adjustable because it is formulated as a second-order cone programming(SOCP) model with an adjustable coefficient.This coefficient can control the robustness of the chance constraints, which may be set up for the Gaussian distribution, symmetrically distributional robustness, or distributionally robust cases considering wind forecasting uncertainty. The conservativeness of the ADRCC-OPF model is analyzed and compared with the actual distribution data of wind forecasting error. The system operators can choose an appropriate adjustable coefficient to tradeoff between the economics and system security. | Xin FANG Bri-Mathias HODGE Fangxing LI Ershun DU Chongqing KANG | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，3： | 1 |
| 14 | Enhancing Design of Visual-Servo Delayed System显示文摘A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network(RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative(PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization(PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor. | Zhi-Ren Tsai Yau-Zen Chang | 2018 | Journal of Electronic Science and Technology2018，16，3： | 1 |
| 15 | Response surface methodology-based hybrid robust design optimization for complex product under mixed uncertainties显示文摘Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters. | WAN Liangqi CHEN Hongzhuan OUYANG Linhan | 2019 | Journal of Systems Engineering and Electronics2019，30，2： | 1 |
| 16 | A Trajectory Planning-Based Energy-Optimal Method for an EMVT System显示文摘In this paper,a trajectory planning-based energy-optimal method is proposed to reduce the energy consumption of novel electromagnetic valve train(EMVT).Firstly,an EMVT optimization model based on state equation was established.Then,the Gauss pseudospectral method(GPM)was used to plan energy-optimal trajectory.And a robust feedforward-feedback tracking controller based on inverse system method is proposed to track the energy-optimal trajectory.In order to verify the effectiveness of the energyoptimal trajectory,a test bench was established.Finally,co-simulations based on MATLAB Simulink and AVL Boost were carried out to illustrate the effect of energyoptimal trajectories on engine performance.Experimental results show that the robust tracking controller can achieve good position tracking performance.And these energyoptimal trajectories can save up to 40%of the energy consumption compared with the conventional camshaft valve trajectories. | Jiayu Lu Siqin Chang | 2019 | Computer Modeling in Engineering & Sciences2019，，1： | 0 |
| 17 | A Heuristic Method for Some NP-hard Robust Combinatorial Optimization Problems | YANG Xiao\|guang\+1\ \ ZHU Qing\+2 1.Laboratory of Management, Decision and Information Systems Institute of Systems Science, Academia Sinica, Beijing 100080, China 2.Department of Mathematics, Anhui University, Hefei 230039, China | 1999 | Systems Science and Systems Engineering1999，9，3： | 0 |
| 18 | A Robust Optimization Approach Considering the Robustness of Design Objectives and Constraints显示文摘The problem of robust design is treated as a multi-objective optimization issue in which the performance mean and variation are optimized and minimized respectively, while maintaining the feasibility of design constraints under uncertainty. To effectively address this issue in robust design, this paper presents a novel robust optimization approach which integrates multi-objective optimization concepts with Taguchi’s crossed arrays techniques. In this approach, Pareto-optimal robust design solution sets are obtained with the aid of design of experiment set-ups, which utilize the results of Analysis of Variance to quantify relative dominance and significance of design variables. A beam design problem is used to illustrate the effectiveness of the proposed approach. | LIUChun-tao LINZhi-hang ZHOUChunojing | 2005 | Computer Aided Drafting,Design and Manufacturing2005，15，1： | 0 |
| 19 | Robust Topology Optimization of Vehicle Suspension Control Arm显示文摘A robust topology optimization design framework is developed to solve lightweight structural design problems under uncertain conditions. To enhance the calculation accuracy and flexibility of the statistical moments of robust analysis, number theory integral method is applied to sample point selection and weight assignment. Both the structure topology optimization and number theory integral methods are combined to form a new robust topology optimization method. A suspension control arm problem is provided as a demonstration of robust topology optimization methods under loading uncertainties. Based on the results of deterministic and robust topology optimization, it is demonstrated that the proposed robust topology optimization method can produce a more robust design than that obtained by deterministic topology optimization. It is also found that this new approach is easy to apply in the existing commercial topology optimization software and thus feasible in practical engineering problems. | Xiaokai Chen Cheng Zhang Qinghai Zhao | 2019 | Journal of Beijing Institute of Technology2019，28，3： | 0 |
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