配电网与综合能源系统(Integrated Energy System,IES)的互联运行是未来配电网重要的发展方向,这将对二者供能的可靠性产生深刻影响。为更加准确地评估配电网可靠性,提出一种计及IES接入影响的配电网可靠性评估方法。文中对IES-配电网...配电网与综合能源系统(Integrated Energy System,IES)的互联运行是未来配电网重要的发展方向,这将对二者供能的可靠性产生深刻影响。为更加准确地评估配电网可靠性,提出一种计及IES接入影响的配电网可靠性评估方法。文中对IES-配电网联合系统建模,分别建立IES和配电网的最优负荷削减模型;然后,采用目标级联法(Analysis Target Cascading,ATC)分布式求解联合系统的最优负荷削减问题,基于马尔科夫链蒙特卡洛,计算IES-配电网联合系统的可靠性指标,在多种运行场景下对改进的IEEE RBTS-BUS6系统进行可靠性评估。算例结果表明,在合理的运行策略下,IES接入后可以大幅改善配电网可靠性,且热电联产机组对配电网可靠性的重要度最高。展开更多
综合能源系统(integrated energy system,IES)具有灵活调度和多能互济的特点,针对当前综合能源系统供能可靠性研究尚不充分的问题,提出一种考虑最优负荷削减与热负荷惯性的综合能源系统可靠性评估方法。首先,建立了综合能源系统总停供...综合能源系统(integrated energy system,IES)具有灵活调度和多能互济的特点,针对当前综合能源系统供能可靠性研究尚不充分的问题,提出一种考虑最优负荷削减与热负荷惯性的综合能源系统可靠性评估方法。首先,建立了综合能源系统总停供损失期望指标,充分体现了综合能源系统停供能造成的经济损失;其次,考虑能源品位、负荷重要度、热负荷惯性,建立了故障场景下综合考虑运行成本最小与加权停供负荷量最小为目标的综合能源系统最优负荷削减模型,采用CPLEX软件求解获得电热负荷削减功率和元件设备出力;然后,基于序贯蒙特卡洛模拟原理,设计了综合能源系统可靠性评估方法和流程;最后,通过算例仿真进行验证。算例分析表明,采用最优负荷削减策略和考虑热负荷惯性能够有效提升综合能源系统的可靠性水平。展开更多
With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train ...With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.展开更多
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 arra...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.展开更多
文摘综合能源系统(integrated energy system,IES)具有灵活调度和多能互济的特点,针对当前综合能源系统供能可靠性研究尚不充分的问题,提出一种考虑最优负荷削减与热负荷惯性的综合能源系统可靠性评估方法。首先,建立了综合能源系统总停供损失期望指标,充分体现了综合能源系统停供能造成的经济损失;其次,考虑能源品位、负荷重要度、热负荷惯性,建立了故障场景下综合考虑运行成本最小与加权停供负荷量最小为目标的综合能源系统最优负荷削减模型,采用CPLEX软件求解获得电热负荷削减功率和元件设备出力;然后,基于序贯蒙特卡洛模拟原理,设计了综合能源系统可靠性评估方法和流程;最后,通过算例仿真进行验证。算例分析表明,采用最优负荷削减策略和考虑热负荷惯性能够有效提升综合能源系统的可靠性水平。
基金Project supported by the National Natural Science Foundation of China (No. 50823004)the National Key Technology R&D Program of China (No. 2009BAG12A01-C09)+1 种基金the 2013 Doctoral Innovation Funds of Southwest Jiaotong Universitythe Fundamental Research Funds for the Central Universities, China
文摘With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.
基金the Digital Manufacturing and Design Innovation Institute(DMDII)through award number 15-07-07the National Science Foundation Graduate Research Fellowship Program under Grant No.DGE-1842165.
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.
