Boron doping induced electronic reconfiguration of Fe-Nx sites in N-doped carbon matrix for efficient oxygen reduction reaction in both alkaline and acidic media

Developing non-precious metal-based catalysts as the substitution of precious catalysts (Pt/C) in oxygen reduction reaction (ORR) is crucial for energy devices. Herein, a template and organic solvent-free method was adopted to synthesize Fe, B, and N doped nanoflake-like carbon materials (Fe/B/N–C) by pyrolysis of monoclinic ZIF-8 coated with iron precursors and boric acid. Benefiting from introducing B into Fe–N–C, the regulated electron cloud density of Fe-N_x sites enhance the charge transfer and promotes the ORR process. The as-synthesized Fe/B/N–C electrocatalyst shows excellent ORR activity of a half-wave potential (0.90 V vs 0.87 V of Pt/C), together with superior long-term stability (95.5% current density retention after 27 h) in alkaline media and is even comparable to the commercial Pt/C catalyst (with a half-wave potential of 0.74 V vs 0.82 V of Pt/C) in an acidic electrolyte. A Zn-air battery assembled with Fe/B/N–C as ORR catalyst delivers a higher open-circuit potential (1.47 V), specific capacity (759.9 mA h g^?1_Zn at 10 mA cm^?2), peak power density (62 mW cm^?2), as well as excellent durability (5 mA cm^?2 for more than 160 h) compared to those with commercial Pt/C. This work provides an effective strategy to construct B doped Fe–N–C materials as nonprecious ORR catalyst. Theoretical calculations indicate that introduction of B could induce Fe-N_x species electronic configuration and is favorable for activation of OH1 intermediates to promote ORR process.     

Cross-fertilization for routine reconfiguration in IT-enabled organizational transformation

Routine reconfiguration is a key challenge for IT-enabled organizational transformation projects. However, how to successfully reconfigure existing routines remains unclear. This case study explores how to achieve routine reconfiguration in IT-enabled organizational transformation and suggests that routine reconfiguration can be achieved through the cross-fertilization of business domain knowledge. We identified a process model of cross-fertilization of business domain knowledge, which essentially incorporates three key processes (i.e., knowledge combination, reflection, and experimentation) and indicates that cross-fertilization can bring changes to all three types of trajectory components. The theoretical and practical implications of this study are also discussed.     

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.     

Self-adaptation of mobile systems driven by the Common Variability Language

The execution context in which pervasive systems or mobile computing run changes continually. Hence, applications for these systems require support for self-adaptation to the continual context changes. Most of the approaches for self-adaptive systems implement a reconfiguration service that receives as input the list of all possible configurations and the plans to switch between them. In this paper we present an alternative approach for the automatic generation of application configurations and the reconfiguration plans at runtime. With our approach, the generated configurations are optimal as regards different criteria, such as functionality or resource consumption (e.g. battery or memory). This is achieved by: (1) modelling architectural variability at design-time using the Common Variability Language (CVL), and (2) using a genetic algorithm that finds nearly-optimal configurations at run-time using the information provided by the variability model. We also specify a case study and we use it to evaluate our approach, showing that it is efficient and suitable for devices with scarce resources.     

Mathematical representation of radiality constraint in distribution system reconfiguration problem

Distribution systems are most commonly operated in a radial configuration for a number of reasons. In order to impose radiality constraint in the optimal network reconfiguration problem, an efficient algorithm is introduced in this paper based on graph theory. The paper shows that the normally followed methods of imposing radiality constraint within a mixed-integer programming formulation of the reconfiguration problem may not be sufficient. The minimum-loss network reconfiguration problem is formulated using different ways to impose radiality constraint. It is shown, through simulations, that the formulated problem using the proposed method for representing radiality constraint can be solved more efficiently, as opposed to the previously proposed formulations. This results in up to 30% reduction in CPU time for the test systems used in this study.     

Positioning of PV panels for reduction in line losses and mismatch losses in PV array

Partial shading decreases the power output of PV arrays due to mismatch losses. These losses are dependent on the shading pattern and the relative positions of shaded modules in the array. Various static and dynamic reconfiguration techniques have earlier been proposed to mitigate these losses. In an earlier proposed static reconfiguration technique, the power generation is enhanced by altering the physical location of the PV panels using a random Sudoku configuration without modifying the TCT (Total-Cross-Tied) based electrical connections. However, this arrangement faces drawbacks due to ineffective dispersion of shade and significant increase in wiring required. In this work, an optimal Sudoku arrangement to overcome these drawbacks is formulated. Further analysis indicate that the global peak of the optimal Sudoku based PV array occurs as the right most peak in the curve for most shading conditions, thus evidently obviating the need for complex MPPT (Maximum-Power-Point-Tracking) algorithms. The proposed configuration is compared with various other existing reconfiguration schemes in terms of power output and the comparison is presented. In addition, a general formulation is proposed to expand this pattern to any generic array. A strategy is also proposed to make such an interconnection practicable for very large size PV arrays.     

复杂有源配电网供电路径快速优化

配电网络结构日益复杂化以及分布式电源广泛接入带来的不确定性,增加了配电网供电路径优化的难度,传统配电网重构方法很难满足其快速性要求。针对风机、光伏出力的波动性,在构造的概率场景模型基础上,基于时间尺度进行出力分割,并利用无重复生成树策略对复杂搜索空间进行简化,避免重复性辐射型校验,减少解空间的冗余度,采取改进的编码策略以及改进的教学优化算法对重构模型进行求解,提高搜索的速度和全局寻优能力。算例分析证明了所提方法的快速性和有效性。     

考虑电热混合储能与重构联合优化的配电网风电消纳策略

可再生能源消纳是促进节能减排、建设低碳智能电网的重要内容之一。该文着眼于配电网运行环节,引入主动网络重构措施,协同电热混合储能管控,提出适用于配电网风电消纳的多能源优化消纳模型与求解策略。首先,对配电网各单元(如分布式风电系统、电热混合储能系统等)功率模型进行分析,在此基础上建立综合电热混合储能管控和网络重构的非线性混合整数数学优化模型,并采用二阶锥手段松弛线性化非线性约束,实现模型的快速求解。算例仿真验证并展示了电热混合储能管控和网络重构的联合优化策略对配电网促进风电消纳的影响。     

考虑重构的含可再生能源配电网电压控制模型与算法

风电、光伏等分布式电源高渗透并入10kV中压配电网,将导致系统运行经济性与电压质量等问题,若不加以有效管控,则难以充分消纳可再生能源。为实现可再生能源接入下配电网电压安全的主动管控,提出兼顾配电网结构灵活性与电压调节资源能力的机会约束双层优化模型。模型上层以配电网动态重构为手段,确保长时间尺度内的经济运行原则;下层以馈线自动调压器控制策略为对象,实现局部支路电压水平优化。为提高算法效率,利用二阶锥法松弛潮流约束,并采用库恩—塔克(KKT)条件将模型等效转化为单层决策模型。算例结果表明,所提方法通过主动重构技术协调局部电压调节资源,可实现可再生能源接入下配电网的电压安全运行控制。