分布式电源在配电网中布点规划研究

为了满足我国经济高速发展的需求,在己建中央电站及电网的基础上,大力发展分布式发电技术将是电力系统未来发展的必然趋势。但是,大量分布式电源的渗入也使得配电网在规划和运行方面要面临比以往更多的不确定性因素。在总结国内外研究成果的基础上,在含分布式发电的配电网规划中,对分布式电源的布点规划问题进行研究。这里首先对分布式发电技术进行了概念性的介绍,并系统地分析了分布式电源接入配电网后在规划和运行方面可能带来的影响;建立了以配电网最小网络损耗为目标函数的经济性模型,应用遗传算法对分布式电源的位置和容量进行优化,对遗传过程中生成的每个分布式电源位置和容量方案个体,考虑分布式电源对配电网潮流和线路负载能力的影响;最后通过IEEE33节点算例验证了所提方法能够得到较合理的分布式电源接入位置和容量的方案。     

U形接触片多工位级进模设计与制造

针对U形接触片的技术要求,确定了合理的冲压工艺方案,阐述了该多工位级进模设计要点,产品质量达到设计要求。同时,还介绍了楔块装置及磷铜薄片整形的微调装置。     

超声衍射时差法探伤和定量技术--焊缝超声检测最新欧洲标准介绍

超声衍射时差(TOFD)法是焊缝超声检测和缺陷定量很有发展前景的新技术。它根据入射纵波在缺陷端部产生的衍射波传播时差进行测深定高,是一种可靠性甚高的方法,有A,D,B三种显示方式,探伤结果记录较直观和客观。根据最新欧洲标准(草案)ENV583 6:2000的有关规定,介绍超声TOFD技术应用要领,企望该技术在国内无损检测(NDT)领域迅速推广应用。     

基于改进粒子群算法的多目标分布式电源选址定容规划

通过分析分布式电源对配电网的影响,以有功功率损耗、电压质量及分布式电源总容量为优化目标,基于模糊理论建立了分布式电源在配电网中选址定容的多目标优化模型,并提出了一种改进粒子群算法进行求解。在算例仿真中,基于IEEE 14标准节点系统,采用MATLAB仿真工具对所提算法进行了测试,证实了所提算法全局搜索能力较强、收敛速度较快,并通过比较分析验证了该模型和算法的可行性及有效性。     

Lot streaming for product assembly in job shop environment

Assembly job shop scheduling problem (AJSP) is an extension of classical job shop scheduling problem (JSP). AJSP starts with JSP and appends an assembly stage to the completed jobs. Lot streaming (LS) technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. This paper combines, for the first time, LS and AJSP, extending LS applicability to both machining and assembly. To solve this complex problem, an efficient algorithm is proposed using genetic algorithms and simple dispatching rules. Experimental results suggest that equal size LS outperforms varied size LS with respect to the objective function.     

使用扩展逻辑效力的逻辑路径尺寸优化方法

为解决集成电路物理设计中考虑互连线影响的逻辑路径延迟优化问题,提出一个计入互连线负载的扩展的逻辑效力(ELE),并针对ELE给出一个可同时优化逻辑路径中各个逻辑门尺寸及各段互连线长度的优化流程.ELE在保留原有逻辑效力参数的同时,使用互连寄生参数提取软件获得的Ⅱ型互连线参数,实现对带有互连线负载的逻辑门的传播延迟的描述和估计;逻辑路径优化流程采用效力延迟分配策略作为初始条件来表示各段互连线负载对总效力延迟的影响,将所用目标单元库和制造工艺的物理尺寸信息作为限制条件,以ELE表达式为核心展开优化计算,辅以动态规划办法,无需迭代运算,仅通过一轮计算即可求得全部结果.实验结果表明,该流程计算任务简单,资源耗费少,可以准确、快速地获得所需的逻辑门尺寸和互连线长度;结果清晰合理,与目标单元库和工艺库完全兼容.     

基于单片机的在线颗粒分析仪智能控制系统设计

针对国内粉末生产过程中粒度分布检验的滞后性,提出了在线颗粒分析仪智能控制系统设计。通过控制采样速度和喂料速度实现样品的在线分析,并实现分析数据的实时采集和传输,实现在线监控。实验结果表明,该系统测试范围达到4-300μm,可持续工作8小时,延时小于1分钟,测试准确度,重复性均达到在线控制的需要。     

计及可靠性收益的配电网柔性多状态开关及分布式电源综合优化配置

柔性多状态开关(flexible multi-state switch,FMS)是支撑新型电力系统背景下配电网运行控制能力提升和可再生能源接入渗透率改善的重要技术装备,针对现有配电网中FMS的规划并未详细考虑FMS与分布式电源(distributed generation,DG)的协调配置,以及对于FMS接入带来的可靠性提升考虑不足的问题。文章在规划配置阶段详细考虑了含FMS和DG的协同优化运行,并充分计及FMS接入带来的可靠性收益,构建了基于嵌套优化的FMS和DG选址定容双层优化配置模型。针对双层嵌套规划模型求解的复杂性,提出了基于改进粒子群算法和GAMS(general algebraic modeling language)算法相结合的模型求解策略,以改造后的IEEE 33节点算例系统为例,对所提出模型和方法的有效性进行了验证,结果表明提出的方法相比传统单一FMS规划具有更好的经济性,能最大程度地降低配电网年综合费用,同时减少用户因停电带来的损失。     

Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

The urgent need to meet increasingly tight environmental regulations and new fuel economy requirements has motivated system science researchers and automotive engineers to take advantage of emerging computational techniques to further advance hybrid electric vehicle and plug-in hybrid electric vehicle (PHEV) designs. In particular, research has focused on vehicle powertrain system design optimization, to reduce the fuel consumption and total energy cost while improving the vehicle's driving performance. In this work, two different natural optimization machines, namely the synchronous self-learning Pareto strategy and the elitism non-dominated sorting genetic algorithm, are implemented for component sizing of a specific power-split PHEV platform with a Toyota plug-in Prius as the baseline vehicle. To do this, a high-fidelity model of the Toyota plug-in Prius is employed for the numerical experiments using the Autonomie simulation software. Based on the simulation results, it is demonstrated that Pareto-based algorithms can successfully optimize the design parameters of the vehicle powertrain.     

Solving a multi-level capacitated lot sizing problem with multi-period setup carry-over via a fix-and-optimize heuristic

This paper presents a new algorithm for the dynamic multi-level capacitated lot sizing problem with setup carry-overs (MLCLSP-L). The MLCLSP-L is a big-bucket model that allows the production of any number of products within a period, but it incorporates partial sequencing of the production orders in the sense that the first and the last products produced in a period are determined by the model. We solve a model which is applicable to general bill-of-material structures and which includes minimum lead times of one period and multi-period setup carry-overs. Our algorithm solves a series of mixed-integer linear programs in an iterative so-called fix-and-optimize approach. In each instance of these mixed-integer linear programs a large number of binary setup variables is fixed whereas only a small subset of these variables is optimized, together with the complete set of the inventory and lot size variables. A numerical study shows that the algorithm provides high-quality results and that the computational effort is moderate.