考虑新能源不确定性的互联电网交换功率鲁棒优化模型

高比例新能源及其不确定性增加了多区域交流互联系统交换功率控制的难度,为保证区域间联络线传输功率的协调分布及其波动相对均衡,提出了一种考虑互联电网外特性的交换功率稳定控制模型。考虑互联系统自动发电控制(AGC)参与因子与联络线潮流分布的关联关系,推导并构建了互联系统AGC下的潮流模型。进而,以联络线功率波动幅值最小为目标函数,建立了基于鲁棒优化的区域交换功率稳定控制模型,并提出了一种基于松弛法的协同演化算法对该模型进行求解。以双IEEE 14节点和IEEE 118节点测试系统为例进行仿真分析,将无优化与鲁棒优化计算结果进行对比,结果表明鲁棒优化可以有效应对新能源随机出力的影响,对于外特性的稳定性具有明显改善效果,并验证了所提算法的有效性和实用性。     

计及天然气管网压力能消纳的电动汽车换电池集中充电-配送策略

针对城市天然气管网压力能利用率低以及“集中充电,统一配送”模式下的换电池调度问题,提出考虑天然气管网压力能发电的换电池集中充电-配送优化策略。采用?分析法构建了天然气压力能发电模型,结合电池放电深度和充放电区间对电池寿命的影响,设计了分组类别下的配送车和换电池调度策略。考虑配送车行驶时的电能转换效率和受到的空气阻力、滚动阻力等物理因素,建立了配送车非线性能耗模型。在此基础上,计及软时间窗、配送车载重和续航里程等约束,以运输成本和时间惩罚成本最低为目标进行优化调度。算例分析表明：所提策略对城市天然气管网压力能的消纳水平高,实现了天然气压力能回收利用与换电池调度的有机结合,为天然气压力能在电动汽车换电模式下的高效消纳提供了参考。     

基于分布式拟牛顿法的交流微电网经济运行控制

针对含多撑网逆变器的交流微电网,提出一种基于分布式拟牛顿法的经济运行控制策略,该策略包括电压和无功功率调节器以及频率和有功功率调节器两部分。采用稀疏通信网络交换相邻逆变器的信息,基于等耗量微增率准则,采用拟牛顿法根据本地和相邻节点的信息估算有功功率和无功功率的最优分配量。在电压和无功功率调节器中,无功功率的估算值可作为电流源型逆变器的参考值,或用于产生电压源型逆变器的电压修正项,实现无功功率的最优分配和电压控制。在频率和有功功率调节器中,有功功率的估算值可作为电流源型逆变器的参考值,或用于产生电压源型逆变器的频率修正项,实现有功功率的最优分配和频率控制。6节点交流微电网的仿真结果表明,所提控制策略在实现高质量电压和频率控制的同时,能够实现系统的最优经济运行,具有“即插即用”的能力,且对通信链路故障有较高的鲁棒性。     

虚拟惯量控制响应延时对控制效果的影响分析

电力电子接口电源通过虚拟惯量控制模拟同步机惯量响应,但控制过程存在响应延时。全面分析了延时对虚拟惯量控制效果的影响,发现延时并非越小越好。虚拟惯量控制可以降低频率变化率和最大频差两个指标。响应延时增大,扰动后短时间内平均频率变化率变大,但是,最大频差先下降后上升,并在某个延时取值处获得最优值。而且延时增大时调频功率峰值和能量峰值均降低,控制成本更小。虚拟惯量控制的目标不同时,对延时的要求不同。分析结论有助于更加全面地认识虚拟惯量控制的效果并指导实际应用。     

基于改进代价敏感直推式支持向量机的发电企业 滥用市场力识别

随着现货市场的加速推进,准确地实时识别滥用市场力行为是电力市场违规行为管理的一项关键性任务。将改进的支持向量机与变分不等式求解算法结合,实现了在只有少量发电企业有标签数据情形下仍可以准确实时地识别发电企业滥用市场力行为。首先,结合电力市场实际情况,构造了滥用市场力识别指标体系,并基于电力市场高维数据的特点对数据进行降维。其次,针对发电企业有标签数据占总体数据小部分及数据不平衡的特点,提出了基于改进代价敏感直推式支持向量机的发电企业滥用市场力识别方法。然后,考虑到半监督算法求解时间较长,将求解问题转化为高效的变分不等式求解问题,并使用定制近邻法进行求解。最后,利用UCI数据集、电力市场仿真数据及实际电力市场数据进行试验。结果表明,该识别方法可以将滥用市场力的发电企业快速有效地识别出来。     

海战场态势生成技术发展综述

未来的战争必将是多兵种、多域联合作战,战场态势作为未来联合作战的重要支撑,旨在为联合作战提供精准、高效的统一态势图,而如何将多平台、同/异构传感器信息及其他情报信息与战场环境融合生成准确可靠的战场态势是亟需解决的技术难题。鉴于现代海战场对高精度、强实时、全要素战场态势图的迫切需求,对海战场态势生成技术进行了综述。首先梳理了海上态势生成项目的发展历程及能力水平;然后详细介绍了通用作战图/通用战术图等典型项目,在态势生成部分中通过态势图的要素组成、态势生成流程及关键技术对态势生成技术进行了阐述;最后对未来海战场态势生成技术的发展趋势进行了预测,希望可以为态势生成相关研究提供参考。     

小型化低功耗机载显示器图形系统设计与实现

为了满足机载显示器图形生成系统的小尺寸、低功耗需求,提出了一种基于龙芯2K1000的全国产图形生成与处理方案。该方案以2K1000为核心构建硬件平台,使用2K1000内部集成的中央处理器、图形处理器、显示控制器,以及外部的内存实现图形的计算生成和双缓存显示,配合国产可编程逻辑器件实现图形与外视频的叠加显示及机载通信总线扩展。软件上采用航空专用的国产天脉操作系统,基于天脉操作系统设计了关键的图形显示驱动、帧存驱动、显示控制器驱动。实验结果表明,在输出1 024 pixel×768 pixel分辨率显示时,典型机载图形画面帧率达到35 frame/s,整体功耗约10 W。该方案扩展性强、功耗低,满足实时显示需求,在机载显示器领域有着广泛的应用空间。     

Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

In this article, energy efficient ensemble clustering method (EECM) with black widow optimization (EECM-BWO) algorithm is proposed for effective data transmission with the help of real time flood disaster monitoring wireless sensor network (WSN). Initially, unified scalable ensemble clustering algorithm based on ensemble generation and consensus function is proposed for selecting the optimal routing path among the node using BWO algorithm. Then, biologically inspired routing black widow spiders optimization algorithm is proposed to trade off the nodes energy level, self-organization, and self-configuration in the WSN. The simulation is performed using NS2 simulator for validating the performance of the proposed EECM-BWO method. Here, in node, low delay achieves 24.07%, 72.58%, 51.36%, 81.75%, 77.74%, high packet delivery ratio achieves 70.83%, 53.93%, 90.23%, 43.58%, 24.58%, low packet drop attains 77.93%, 72.76%, 61.56%, 51.87%, 34.35%, low energy consumption attains 75.9%, 52.94%, 65.81%, 58%, 41.2% compared with existing energy-efficient clustering approach consolidated game theory as well as dual-cluster-head mode for WSNs energy-aware clustering by cuckoo optimization approach (EECM-COA), energy-aware clustering-based routing using multi-path reliable transmission with routing and control board (EECM-RCB-MRT), adaptive repair algorithm with temporally ordered routing algorithms for flood control strategy (EECM-AR-TORA-FCS), passive multi-hop clustering algorithm (EECM-PMC), dynamic source routing protocol based on genetic algorithm-bacterial foraging optimization (DSR-GA-BFO).     

Comprehensive summary of solid oxide fuel cell control: a state-of-the-art review

A thermoelectric generation (TEG) system has the weakness of relatively low thermoelectric conversion efficiency caused by heterogeneous temperature distribution (HgTD). Dynamic reconfiguration is an effective technique to improve its overall energy efficiency under HgTD. Nevertheless, numerous combinations of electrical switches make dynamic reconfiguration a complex combinatorial optimization problem. This paper aims to design a novel adaptive coordinated seeker (ACS) based on an optimal configuration strategy for large-scale TEG systems with series–parallel connected modules under HgTDs. To properly balance global exploration and local exploitation, ACS is based on ‘divide-and-conquer’ parallel computing, which synthetically coordinates the local searching capability of tabu search (TS) and the global searching capability of a pelican optimization algorithm (POA) during iterations. In addition, an equivalent re-optimization strategy for a reconfiguration solution obtained by meta-heuristic algorithms (MhAs) is proposed to reduce redundant switching actions caused by the randomness of MhAs. Two case studies are carried out to assess the feasibility and superiority of ACS in comparison with the artificial bee colony algorithm, ant colony optimization, genetic algorithm, particle swarm optimization, simulated annealing algorithm, TS, and POA. Simulation results indicate that ACS can realize fast and stable dynamic reconfiguration of a TEG system under HgTDs. In addition, RTLAB platform-based hardware-in-the-loop experiments are carried out to further validate the hardware implementation feasibility.     

Frequency regularization of a linked wind–diesel system using dual structure fuzzy with ultra-capacitor

Microgrids (μ-grids) are gaining increased interest around the world for supplying cheap and clean energy. In this paper, a μ-grid comprising a wind turbine generator (WTG) and diesel generator (DG) is considered. It is one of most practical and demanding systems suitable for the present energy crisis in isolated or rural areas. However, wind energy is intermittent in nature while load demand changes frequently. Therefore, a µ-grid can experience large frequency and power fluctuations. The speed governor of the DG tries to minimize the frequency and power deviations in µ-grid though its operation is slow and cannot adequately minimize system deviations. The paper proposes a novel arrangement based on a dual structured fuzzy (DSF) whose structure changes according to the switching limit with a reduced rule base. It has the capability to switch between proportional and integral actions and hence improves the frequency regularization of the μ-grid. The proposed strategy is tested in a μ-grid and the results considering step load alteration, load alteration at different instants of time, nonstop changing load request are compared with some of the well published methods to validate the effectiveness and simplicity of the present design. In addition, it shows that ultra-capacitor establishment in a μ-grid has a positive impact in minimizing system deviations with DSF for the studied cases.