光储独立直流微电网的协同控制策略研究

针对由光伏、蓄电池及可变负载组成的独立直流微电网,提出电压和电流分段式协同控制策略。该控制策略将能量管理划分为4种工作模式,采用最大功率点跟踪控制充分利用太阳能,将蓄电池作为支撑单元,当光伏模块不能稳定直流母线电压的时候,蓄电池才工作,从而降低蓄电池的切换频率。为了防止过充,将蓄电池充电分为恒流充电和恒压充电两种模式,从而增加蓄电池的使用寿命。建立Matlab仿真模型,其仿真结果验证所提控制策略的可行性。     

An inverse‐time low‐impedance protection design for feeders in active distribution networks

One of the major issues associated with active distribution networks (ADNs) is to devise an appropriate protection scheme that works successfully in different operation modes. This paper describes the design of an inverse‐time low‐impedance (ITLI) protection scheme with the aid of the advanced measurement technologies in ADNs. The scheme detects faults and calculates tripping time by using the magnitude ratio of the maximum load impedance to the measured impedance. ITLI protection is immune to varying fault current caused by the flexible operation modes and able to automatically adjust fault‐tripping time according to the fault severity. With the existing communication infrastructures, an event‐triggered adaptive setting scheme updates the settings of ITLI relays in real time. The setting method not only enhances the detecting capability but also provides higher reliability and sensitivity before, during, and after events in ADNs, such as tap position adjustment, DGs fluctuation, and network structure change. Besides, an acceleration method based on the definite‐time grading technique is presented to reduce the impact of infeeds and fault resistance. The effectiveness of the proposed protection scheme is demonstrated in a 12.47‐kV active distribution network established by PSCAD/EMTDC. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于分段迭代的电力谐波神经网络分析方法

为了提高谐波和间谐波分析的速度、精度和抗噪性能,将基于分段迭代的增强型Adaline神经网络应用于电力系统谐波和间谐波分析。该网络在加汉宁窗双谱线插值FFT算法的基础上,将采样数据按采样时间分段,依次用各段对应的误差信息来调整增强型Adaline神经网络的参数。该方法结合一点迭代法和全部点迭代法的优点,既将各时段内的误差进行平均,减少噪声对参数调整的影响,又充分保留误差中包含的谐波和间谐波信息,提高网络的精度。另外,根据参数估计误差和频率对误差函数一阶偏导之间的关系,提出修正信号幅值最大分量对应的频率调整量的处理方式,提高网络的实时性和精度。仿真结果验证了分析结论的正确性。     

光伏系统MPPT的改进模糊控制

为减少光伏系统因外部条件变化而造成的功率损失,减小最大功率点(MPP)处的振荡,并且便于计算机软件实现,采用基于改进模糊控制的最大功率点跟踪(MPPT)技术。在光伏电池工程用数学模型的基础上,分析太阳能发电中的最大功率点原理;在跟踪过程各阶段引入不同的权重,设计了模糊控制规则,并且增加了PI控制环节以改善模糊控制。Matlab/Simulink仿真结果表明,改进的模糊控制光伏系统具有良好的动态性能和稳态性能,在最大功率点处输出功率稳定,提高了能量转化效率。     

基于改进蜻蜓算法的光伏全局最大功率追踪

光伏阵列的P-U特性曲线在局部遮蔽条件下呈现多峰现象,针对传统最大功率点跟踪方法易陷入局部极值、群智能算法跟随速度慢的问题,提出一种基于蜻蜓算法和扰动观察法的改进最大功率点跟踪算法.该算法通过优化算法角色,引入Lévy飞行模式加快算法的收敛速度并提高全局搜索能力;结合扰动观察法,提出种群密度的概念,制定最优局部搜索策略...     

内置式永磁同步电机效率优化控制策略

以效率优化作为内置式永磁同步电机(IPMSM)驱动系统控制目标,研究了IPMSM的最大转矩电流比控制(MTPA)系统,并分析了MTPA控制的不足。在传统效率优化控制算法基础上充分考虑分析铜耗、铁耗和杂散损耗影响,并考虑参数变化的二次补偿,提出新的损耗最小化控制策略,并对其实际应用进行了工程化简,兼顾了效率优化精度和工程实现性。采用MATLAB软件建立了系统仿真模型,分析对比了以上两种控制策略效率优化效果,仿真结果证明了该策略的有效性。     

基于熵权-层次分析法综合指标的电网关键节点辨识

电网关键节点的辨识是目前电力系统安全稳定运行的重要指导内容之一。为科学合理辨识电网关键节点,文中首先计及电网线路负载率等级,基于泰尔熵理论考虑潮流变化的分布不均衡性,提出节点状态关键度指标;然后为使评估结果更符合复杂网络与实际电网结构模型,文中提出最大流传输贡献介数和接近中心性指标;最后结合熵权法和层次分析法对指标进行权重分配,得到既兼顾电网状态变化和电网结构,又结合主观经验并考虑客观数据的关键节点评估综合指标,从而准确辨识电网关键节点。通过IEEE 39节点系统进行测试,验证综合指标的可行性和实用性。     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Nanosatellite electrical power system architectures: Models,simulations, and tests

This paper presents four of the most employed nanosatellite's Electrical Power System (EPS) architectures, comparing their efficiency through simulations and experiments. Every circuit architecture has been mathematically modeled in order to discuss the solar panel control technique and the overall architecture efficiency. Solar panels and EPS components have been analytically modeled and tested in order to comprehend their impact on the EPS efficiency. A test stand has been proposed to evaluate the circuits, emulating the solar irradiance and the nanosatellite power consumption. The following electrical power systems have been designed, implemented, and tested: the directly coupled architecture, the very low dropout (VLDO) voltage regulator architecture, the maximum power point tracking (MPPT) with an integrated circuit, and the MPPT architecture with a discrete boost regulator. A case study has been presented, testing all the EPS architectures according to the Floripa-Sat I (1U CubeSat) power consumption profile. Experiments results have shown that, although the MPPT boost regulator architecture harvest more energy, it is the VLDO architecture that presents the best overall efficiency.     

光伏阵列最大功率点跟踪控制方法综述

光伏发电系统的运行需要快速准确地进行最大功率点跟踪(MPPT),但目前很多最大功率点跟踪方法跟踪不够准确,从而导致了光伏系统的功率损失,为此综述了光伏阵列最大功率点跟踪的各种方法,包括日益成熟、改进和优化策略较多的扰动观察法和电导增量法,并总结了两种方法应用的局限性和需要注意的问题。从最大功率点跟踪的控制原理和发展历程出发,归纳了基于优化数学模型、扰动自寻优、智能处理方法及输出端控制等4类方法,分别说明了各种跟踪控制方法的优点和不足之处,并指出具体选择方法时需要统筹考虑跟踪方法实现的难易程度、经济成本、传感器类型、跟踪速度与精度的协调以及应用领域等各种因素。最后探讨了最大功率点跟踪控制方法的发展思路,对该领域今后的研究方向做了展望,指出单级式光伏逆变系统中的最大功率点跟踪己成为国内外光伏领域的一个研究热点。