A review on China's wind power accommodation in the background of “Internet+” strategy

The consumption of fossil fuel has resulted in global warming, environmental pollution, and many other crucial problems. Replacing fossil fuel with renewable energy has become an important issue over the recent decades. As a renewable clean energy, wind power is a relatively well‐developed and promising energy method for current technology development in China. Under the background of growing demand for electricity and enhancing awareness for environmental, the “Internet+ wind power” concept has emerged based on both the wind power's characteristics that renewable and non‐polluting, and the rapid development of the Internet in China. Through querying an amount of literature and information, this paper reveals the resource endowment and policy environment about wind power and energy Internet at first. Then, the PEST‐SWOT strategy analysis model is used to analyze the internalities (strengths and weaknesses) and the externalities (opportunities and threats) of “Internet+ wind power”. According to these results, the paper puts forward some measures (development and utilization, business mode) for wind power accommodation. Then some policy recommendations have been proposed. The government should provide favorable conditions for wind power grid with the “Internet+” technology innovation.     

On monitoring the process mean of autocorrelated observations with measurement errors using the w-of-w runs-rules scheme

Runs-rules have been widely used since the 1950s in industrial and nonindustrial process monitoring applications to improve the performance of basic and other traditional monitoring schemes. However, none of the studies on runs-rules have accounted for a process with a combined effect of measurement errors and autocorrelation. Hence, in this paper, the use of the w-of-w runs-rules to improve the performance of the Shewhart $\overline{X}$ scheme using an additive model with a constant variance and a first-order autoregressive model is proposed. To reduce the combined negative effect of measurement errors and autocorrelation, we implement a sampling strategy based on rational subgroups in which (a) multiple measurements per item are taken (instead of a standard single measurement) and (b) non-neighboring observations are gathered. Moreover, the latter sampling strategy is incorporated into the values of probability elements of a Markov chain matrix which is used to derive some closed-form expressions for the zero- and steady-state run-length distribution. The main finding of this study is that, with respect to some overall performance measures, the proposed scheme outperforms the existing Shewhart $\overline{X}$ scheme by a significant margin. A real-life example is used to illustrate the practical implementation of the proposed scheme.     

Multi-stage power source and grid coordination planning method considering grid uniformity

Given the increasing uncertainties in power supply and load, this paper proposes the concept of power source and grid coordination uniformity planning. In this approach, the standard deviation of the transmission line load rate is considered as the uniformity evaluation index for power source and grid planning. A multi-stage and multi-objective optimization model of the power source and grid expansion planning is established to minimize the comprehensive cost of the entire planning cycle. In this study, the improved particle swarm optimization algorithm and genetic algorithm are combined to solve the model, thus improving the efficiency and accuracy of the solution. The analysis of a simple IEEE Garver’s 6-node system shows that the model and solution method are effective and feasible. Moreover, they are suitable for the coordinated planning of the power source and grid under a diversified nature of power supply and load.     

换热网络优化中换热单元生成频次的影响分析及策略改进

换热单元的生成频次对换热网络优化有直接的影响，分析其机理可以指导求解算法的改进。本文采用节点非结构模型及强制进化随机游走算法，通过设置不同的换热单元生成概率与生成个数以改变换热单元的生成频次，观察并记录个体在优化过程中产生的年综合费用变化情况。发现不同生成频次下整型变量和连续变量的相对优化频率发生了变化，从而改变了整体优化过程，并且与个体当前优化状态不适应的生成频次会造成相对优化频率不平衡、优化结果较差。基于此，本文提出了一种具有生成参数动态调节策略的换热单元生成方式，在优化过程中根据个体状态实时调整换热单元的生成概率与生成个数，平衡整型变量与连续变量的相对优化频率。最后，采用15SP、10SP和20SP算例进行验证，换热网络的年综合费用较文献结果分别下降了1.06%、0.16%、0.68%，验证了该策略使得换热单元的生成频次更为合理，有效地提高了算法的优化效率。     

Nonlinear optimization strategy based on multivariate prediction capability ratios: Analytical schemes and model validation for duplex stainless steel end milling

Given the complex nature of their phenomena and interactions, industrial processes often have multiple variables of interest, usually grouped into critical-to-quality and critical-to-performance characteristics. These variables often have significant correlations, which make engineering problems multivariate. For this reason, Response Surface Methodology, coupled with multivariate techniques, has been widely used as a logical roadmap for modeling and optimization of the characteristics of interest. However, the variability and prediction capability of the numerical solutions obtained are almost always neglected, reducing the likelihood that numerical results are indeed compatible with observable process improvements. To fill this gap, this paper proposes a nonlinear multiobjective optimization strategy based on multivariate prediction capability ratios. For this, rotated Factor Analysis is used as the multivariate technique for grouping process characteristics and composing capability ratios, so that the prediction variance is taken as the natural variability of the process modeled and the expected value distances to the nadir solutions of the latent variables are taken as the allowed variability. Normal Boundary Intersection method, combined with Generalized Reduced Gradient algorithm, is used as the numerical scheme to maximize the prediction capability of Pareto optimal solutions. To illustrate the feasibility of the proposed strategy, we present a case study of end milling without cutting fluids of duplex stainless steel UNS S32205. Rotatable Central Composite Design, with three cutting parameters, was employed for data collection. Traditional multivariate and proposed approaches were compared. The results demonstrate that the proposed optimization strategy is able to provide solutions with satisfactory prediction capability for all variables analyzed, regardless of their convexities, optimization directions, and correlation structure. In addition, while critical-to-quality characteristics are more difficult to control, they have been favored by the proposed optimization regarding prediction capability, which was a desirable result.     

基于网络学习行为聚类分析的在线课堂优化策略研究

利用聚类分析法对网络学习行为分类，从而挖掘不同类型学习者在学习行为和学习效果间的差异。以大学计算机公共课《数据库技术及应用》为例，综合学习者学习行为类别差异、在线课程内容组织以及课程特点等要素为在线课堂进一步发展提供优化策略。     

Prevention of substrate and product inhibitions by using a dilution strategy during dark fermentative hydrogen production from molasses

Substrate and product inhibitions have a significant effect on dark fermentative hydrogen gas production. Particularly, rapid formation of volatile fatty acids leads to fast pH decreases shifting the metabolic pathway. Therefore, controlling volatile fatty acid accumulation has great importance in maintaining effective hydrogen production. In this context, a dilution strategy was applied to regulate volatile fatty acids levels within the desired concentration range. A three-factor Box-Behnken statistical experiment design was established to assess the effects of dilution time, dilution percentage and initial COD concentration on hydrogen formation yield and rate. Highest hydrogen yield (7.7 mL H₂/mL_reactor) and rate (21. 47 mL H₂/h or 9.38 mmol/L_reactor.h) were achieved when 85 gCOD/L containing fermentation media was diluted with a percentage of 130 of the initial working volume at the 3rd hour of the fermentation period. Moreover, this strategy enabled to start fermentation with 55 g glucose/L.     

高精度多环片自动装配控制技术

为了实现对微小环片零件的自动化装配,搭建了自动装配系统.通过4根直线导向轴与4个直线轴承来提高系统的导向精度和刚度.采用直线导轨进行各装配作业模块之间的切换,保证了微小环片零件的自动装配与取出.在环片的装配方向上,螺旋升降机和光栅尺实现环片的位置精度控制.在Lab VIEW编程环境中,采用分层软件架构和模块化控制思想,避免了不必要的数据循环检测与丢失,能够达到环片组件的装配精度要求.控制系统分为系统初始化模块、参数设置模块、装配模块和取出模块,自动装配系统通过各个模块间的相互交流配合完成装配任务.采用本文中自动装配系统装配环片的实验结果表明,环片零件装配的最大位置误差为26μm,垂直度误差为17μm,平均装配时间为75 s/片,可满足环片组件所需的精度要求.     

A multi-start central force optimization for global optimization

Central force optimization (CFO) is an efficient and powerful population-based intelligence algorithm for optimization problems. CFO is deterministic in nature, unlike the most widely used metaheuristics. CFO, however, is not completely free from the problems of premature convergence. One way to overcome local optimality is to utilize the multi-start strategy. By combining the respective advantages of CFO and the multi-start strategy, a multi-start central force optimization (MCFO) algorithm is proposed in this paper. The performance of the MCFO approach is evaluated on a comprehensive set of benchmark functions. The experimental results demonstrate that MCFO not only saves the computational cost, but also performs better than some state-of-the-art CFO algorithms. MCFO is also compared with representative evolutionary algorithms. The results show that MCFO is highly competitive, achieving promising performance.     

Optimal configuration of cluster supply chains with augmented Lagrange coordination

Enterprises in an industrial cluster could dynamically alliance in the form of cluster supply chains to share inner-cluster resources and services, and respond to the ever-fluctuating customer demands in a cost-effective way. However, an effective and feasible method enabling such dynamic cluster supply chain configuration (CSCC) lags behind practice due to the conflict of interests. Researchers are designing All-in-One theoretic models to optimize CSCC with the assumed decision details of all enterprises, while in fact clustered enterprises are seeking effective decentralized decision mechanisms which protect their decision autonomy in the frequently re-configured CSC. A newly emerged multi-disciplinary optimization method, Augmented Lagrangian Coordination (ALC), which supports the open-structure collaboration with strict optimization convergence, is thoroughly investigated in this paper and applied to solve the conflict. Through a complete analysis of CSC’s configuration policies in typical stages, a generic CSCC model is proposed and then partitioned into an ALC-based decentralized decision model by the typical decision autonomy distribution in clusters. Clustered enterprises collaborate vertically and laterally along the ALC model through multi-dimensional couplings to achieve the overall consistency and optimality. Results have proved the effectiveness of ALC for CSCC problem. A set of sensitivity analysis is also conducted to find out the condition in which an order has to be fulfilled in a CSC and the most appropriate configuration.