基于知识引导的自适应动态多模态差分进化算法

为充分利用问题求解过程知识,提升动态多模态优化算法的计算资源利用效率,提出一种基于知识引导的自适应动态多模态差分进化算法.首先,利用自组织映射神经网络实现种群自聚类,形成稳定的小生境;然后,通过对种群全局知识和个体邻域知识的综合学习,设计一种基于知识引导的自适应差分进化算法,在对种群进化状态进行实时监测和分析的基础上,逐层递进地引导不同种群个体自适应地选择最符合当前进化需求的变异方式,提升种群搜索效率,平衡种群多样性与收敛性;最后,针对问题动态特性,设计一种基于历史动态过程知识引导的自适应动态响应机制,通过对历史寻优经验的自适应学习,预测生成新环境下的潜在精英个体,引导种群实现精准快速的多峰定位.实验结果表明,所提出算法能够有效解决动态多模态优化问题,且在不同动态环境设置下其求解性能均优于对比算法.     

DBST: a lightweight block cipher based on dynamic S-box

IoT devices have been widely used with the advent of 5G. These devices contain a large amount of private data during transmission. It is primely important for ensuring their security. Therefore, we proposed a lightweight block cipher based on dynamic S-box named DBST. It is introduced for devices with limited hardware resources and high throughput requirements. DBST is a 128-bit block cipher supporting 64-bit key, which is based on a new generalized Feistel variant structure. It retains the consistency and significantly boosts the diffusion of the traditional Feistel structure. The SubColumns of round function is implemented by combining bit-slice technology with subkeys. The S-box is dynamically associated with the key. It has been demonstrated that DBST has a good avalanche effect, low hardware area, and high throughput. Our S-box has been proven to have fewer differential features than RECTANGLE S-box. The security analysis of DBST reveals that it can against impossible differential attack, differential attack, linear attack, and other types of attacks.     

配电网电压不平衡时MMC控制策略研究

基于柔直技术的交直流混合配电网在促进配电网低碳化转型、提升供电可靠性等方面具有显著优势。模块化多电平变换器(MMC)具有扩展能力强、输出电压等级高等优势,为构建多电压等级、多层次、交直流混联的配电网提供有效的解决方案。结合我国配电网70%以上的故障是由电压不平衡所导致的现状,展开配电网电压不平衡时MMC控制策略的研究有广阔的学术研究意义和工程应用价值。因此,在理论分析的基础上利用PSCAD仿真软件和RTDS半实物平台搭建电网电压不平衡时的仿真模型,验证了所研究的电压不平衡时MMC控制策略的有效性。     

计及主/被动需求响应下基于合作博弈的微网–配电网协调优化调度

随着含高比例可再生能源的并网型微网不断增加,微网与配电网的交互更加紧密。为解决两者作为不同利益主体双方利益分配问题,提出一种计及主/被动需求响应下基于合作博弈的微网-配电网协调优化模型。首先,考虑消费者心理学,建立了基于Logistic模糊函数的电负荷主动需求响应模型。然后,建立了以最优热电比为目标的热负荷被动需求响应模型。最后,微网与配电网作为参与者组成合作联盟,以讨价还价理论为核心,各自利益与联盟利益最大化为目标,协商确定了交互电价与交互功率,用改进的Shapley分配法分配了组成联盟后的额外收益,并通过基于参数自学习的自适应二次变异差分进化算法对其求解。通过算例分析对比可知,用户、微网、配电网三方利益均有所提升,证明了所提方案的合理性。     

电厂飞灰对SO2电化学传感器测量准确度的影响

针对监测火电厂周围空气污染物时,SO2电化学气体传感器出现测量不准和使用寿命较短等问题,以山西省朔州市某煤矸石发电厂飞灰为研究对象,在分析飞灰形貌特征的基础上,通过理论计算得到飞灰沉降速度和不同时间沉积量,通过实验测试飞灰对SO2传感器测量误差的影响。研究结果表明:飞灰直径分布范围4~10 μm,飞灰沉降速度2.25×10–3 m/s, 1天沉积量为1.55 mg;飞灰沉积时间会影响传感器测量误差,沉积时间越长,传感器中气体扩散面积s和扩散系数K减小,传感器测量误差越大;飞灰沉积条件下气体质量浓度越大,气体到达工作电极区域速度越快,在有限响应时间内检测到的有效SO2质量浓度越高,传感器测量误差越小;在飞灰较多环境下使用SO2电化学传感器时,建议加装孔径小于4 μm透气滤膜防尘并定期清理沉积飞灰。     

光储一体化耦合制氢系统控制策略及仿真分析

针对光伏制氢系统受环境影响导致光伏出力波动性强、制氢效果不理想等问题,在光储耦合制氢系统模型基础之上,以提升光伏发电质量、平滑制氢以及增强系统稳定性为目的,采用了一种基于稳压控制的光储一体化耦合制氢系统控制策略。该控制策略包括光伏系统的最大功率点跟踪（MPPT）控制,电化学储能系统自适应协调控制等,可在实现最大光资源利用的同时,保证母线电压稳定以及制氢平滑性,通过仿真验证了该控制策略的有效性。     

MC/DC Test Data Generation Algorithm Based on Whale Genetic Algorithm

The automatic generation of test data is a key step in realizing automated testing. Most automated testing tools for unit testing only provide test case execution drivers and cannot generate test data that meets coverage requirements. This paper presents an improved Whale Genetic Algorithm for generating test data required for unit testing MC/DC coverage. The proposed algorithm introduces an elite retention strategy to avoid the genetic algorithm from falling into iterative degradation. At the same time, the mutation threshold of the whale algorithm is introduced to balance the global exploration and local search capabilities of the genetic algorithm. The threshold is dynamically adjusted according to the diversity and evolution stage of current population, which positively guides the evolution of the population. Finally, an improved crossover strategy is proposed to accelerate the convergence of the algorithm. The improved whale genetic algorithm is compared with genetic algorithm, whale algorithm and particle swarm algorithm on two benchmark programs. The results show that the proposed algorithm is faster for test data generation than comparison methods and can provide better coverage with fewer evaluations, and has great advantages in generating test data.     

中国农村能源发展关键问题

近年来,中国农村能源供应保障能力不断增强,能源结构调整成效明显,但是也存在一些问题：农村废弃物能源化利用率低制约了资源综合利用和环境保护,农村能源消费层次低和电气化水平不高制约了城乡快速融合发展和农村地区能源消费升级,农村能源社会化服务体系建设滞后制约了农村能源有效供给和高效服务的社会公平。针对中国农村能源发展面临的问题和挑战,聚焦农村生活用能,梳理分析了中国农村能源发展基本情况。针对中国国情的特殊性和不同区域具体特点,通过对农村废弃物能源化利用、农村能源电气化应用、农村能源服务体系建设等关键问题研究,提出了促进中国农村能源科学发展的措施建议。