基于萤火虫算法的主动配电网优化调度

主动配电网为高渗透率分布式可再生能源接入提供了有效途径。针对风能等可再生能源所固有的间歇性、波动性与随机性引起的功率波动问题,在配电网中引入储能系统作为可控负荷,建立包含风能与储能系统的主动配电网调度模型,该模型以储能系统的出力为变量;分别以平滑混合毛功率和混合净功率为目标,有效避免可再生能源接入对配电网造成的冲击。提出改进萤火虫算法求解主动配电网优化调度问题。仿真算例验证了所提模型与算法的有效性。     

Optimal design of lattice wave digital fractional‐order Butterworth filter

This letter presents the design of digital fractional‐order Butterworth filter (DFOBF) of order (n+α) , where n is an integer, and α ∈ (0,1) , from the perspective of optimal realization. The magnitude–frequency characteristic of the DFOBF is optimally modeled using the computationally efficient lattice wave digital filters (LWDFs). Design examples for the third‐ and fifth‐order LWDF‐DFOBFs with various values of n, α_, and cut‐off frequencies are presented.     

Optimal analog active filter design using craziness‐based particle swarm optimization algorithm

Because of the manufacturing constraints, the optimal selection of passive component values for the design of analog active filter is very critical. As the search on possible combinations in preferred values for capacitors and resistors is an exhaustive process, it has to be automated with high accuracy within short computation time. Evolutionary computation may be an attractive alternative for automatic selection of optimal discrete component values such as resistors and capacitors for analog active filter design. This paper presents an efficient evolutionary optimization approach for optimal analog filter design considering different topologies and manufacturing series by selecting their component values. The evolutionary optimization technique employed is craziness‐based particle swarm optimization (CRPSO). PSO is very simple in concept, easy to implement and computationally efficient algorithm with two main advantages: fast convergence and only a few control parameters. However, the performance of PSO depends on its control parameters and may be influenced by premature convergence and stagnation problem. To overcome these problems, the PSO algorithm has been modified to CRPSO and is used for the selection of optimal passive component values of fourth‐order Butterworth low‐pass analog active filter and second‐order state variable low‐pass filter, respectively. CRPSO performs the dual task of efficiently selecting the component values as well as minimizing the total design errors of low‐pass active filters. The component values of the filters are selected in such a way so that they become E12/E24/E96 series compatible. The simulation results prove that CRPSO efficiently minimizes the total design error with respect to previously used optimization techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

基于改进萤火虫算法的分布式电源优化配置

在分析分布式电源特性的基础上,建立了含分布式电源的购电成本最小、网损费用最小、投资成本最小以及电压稳定裕度最大的多目标优化模型,能够比较实际、科学地反映DG规划布局。在此基础上,应用超效率数据包分析评价方法,明确各目标函数的权重组合方案,将DG多目标规划问题转换成单目标规划问题。鉴于传统萤火虫算法具有容易早熟、过度依赖控制参数的缺陷,将混沌搜索策略和全局思想融入到萤火虫算法,提出了一种改进型萤火虫算法;并将其应用于解决分布式电源的规划问题。通过算例验证所提算法具有良好的实用性和适应性,并且也验证了所提模型的实际意义。     

基于自适应采样算法及数据处理的过程层设备时延优化设计

智能变电站与传统变电站相比,二次保护系统中增加了过程层设备合并单元及智能终端,引起了保护设备动作时间变慢。提出将合并单元的单一插值采样算法改为同步采样算法与插值算法相结合,基于同步状态自适应调整采样算法,减小了合并单元内部采样数据的处理时延。针对智能终端的CPU插件进行了改进,由FPGA完成GOOSE组播过滤、网络风暴功能,CPU负责处理GOOSE的接收与发送,同时采用MOSFET光电耦合继电器作为启动继电器,通过优化设计减少了智能终端的出口时间。基于上述设计,研制了新型过程层装置,并对比开展了动模仿真及静模仿真验证。仿真试验结果表明,新研制的过程层装置配合线路保护装置的整体动作时间相比优化前减少3 ms,能够满足GB/T-14285标准对继电保护装置整组动作时间的要求。     

基于MOFA算法的微网系统优化调度

针对大规模电动汽车入网给微电网带来的影响,在并网运行方式下,以微电网运行成本、环境治理成本和电动汽车用户充放电成本的综合效益为目标,考虑电动汽车的时空分布特性,提出了分时电价下电动汽车有序充放电的调度方案。建立了包含风、光、储、燃料电池、微型燃气轮机、电动汽车及负荷的微网系统多目标经济调度模型,采用多目标萤火虫（MOFA）算法对调度模型进行求解,并与多目标粒子群优化（MOPSO）算法进行对比。基于MATLAB平台,以某典型微电网系统为例进行仿真,调度周期为一天,算例结果验证了所提方案、模型和算法的有效性。     

基于FPGA实现高插入CIC滤波器

为了产生调制信号的码元速率能在大范围内实时可变,采用插值滤波技术——多级积分梳状滤波器。在分析多级CIC滤波器的结构和特性的基础上,阐述了一种利用Hogenauer＂剪除＂理论实现多级CIC滤波器的高效FPGA实现方法,并通过XILINX的时序仿真分析验证了该方法的正确性和可行性,实际中可以推广应用。     

Variable Taylor realization and improved approximation of FIR fractional delay systems

A modular realization, based on the Taylor structure, is proposed for a maximally flat fractional delay FIR systems. The realization enjoys independence of the multiplier coefficients to changes of the system order, availability of closed-form formulas and recurrence for the multiplier coefficients, requirement of one less multiplier coefficient compared to the direct-form realizations, and existence of schemes for efficient variable delay and order implementations. It is shown that for a variable delay structure, the coefficient updating operation can be performed efficiently using a simple recurrence, and the transient effects can be mitigated to at most two samples. A modified form of the structure with enhanced modularity is also proposed for odd-order systems. Two variable delay schemes are proposed for this modified structure: A transient-free scheme and a scheme that provides to gradually improve the approximations during the transient phase. A method is also proposed for improved approximation under a fixed total number of variable multiplier coefficients. © 1998 John Wiley & Sons, Ltd.     

基于萤火虫算法的分布式电源优化配置研究

为了充分发挥分布式电源的优势,在研究分布式电网潮流特性的基础上,提出了以网络损耗最小和运行最经济为主要目标的分布式电源运行目标函数。并利用改进后的萤火虫算法对函数进行了求解探索。仿真证明,利用更迭域自适应方法改进后的萤火虫算法可有效地解决多目标复杂模型,寻优速度和算法收敛性明显好于单一算法,能够很好地解决分布式电源的定容和定址等优化配置问题。     

改进萤火虫算法在路径规划中的应用

为了保证移动机器人路径规划的解的多样性,提出了小生境萤火虫算法(NFA)。首先,根据环境特点,建立合理的路径规划模型,将萤火虫算法(FA)的目标函数设置为移动步数,并重新设计了亮度公式、初始化方式和萤火虫移动方式;其次,在FA的基础上,引入小生境技术,并在小生境种群间加入共享信息。仿真实验表明,NFA一次运行可得到多个最优路径。相比FA,NFA的移动步数和目标函数均值分别减少了7.14%、6.76%,萤火虫亮度均值增加了8.33%;相比GA,NFA的移动步数和目标函数均值分别减少了7.14%、9.79%。结果表明NFA在算法性能上更优。     

一种无源滤波器的优化设计方法

在分析传统无源滤波器设计的基础上,提出了基于随机权重的遗传算法来求解无源滤波器参数的方案,从谐波抑制、经济指标、无功功率补偿等多目标综合优化无源滤波器参数,通过编程实现了无源滤波器参数的优化。同时,提出用“滤波效益”指标来衡量谐波抑制的性能。并由滤波性能、经济性和无功补偿三方面,分别对优化设计和传统设计所得到的无源滤波器参数进行了实验对比研究。实验结果验证了无源滤波器多目标参数优化设计的合理性。     

基于多目标粒子群算法的无源电力滤波器优化设计

综合考虑滤波装置的总费用、谐波电压畸变率和谐波电流残留率等设计目标,提出一种基于改进多目标粒子群算法的无源滤波器优化设计新方法.改进了传统的粒子群算法,引入快速排序法构造非支配集、精英集归档技术和拥挤度算子概念,提高了算法的寻优速度和精度.最后通过对具体工程算例的计算,表明了该方法的优越性和有效性.     

基于改进萤火虫算法的含DG配电网重构方法

为了更好地解决含DG的配电网重构问题,建立了以系统损耗、负荷均衡、电压偏差为目标的重构模型,并利用改进萤火虫算法进行寻优计算。针对传统萤火虫算法中存在的早熟收敛、过度依赖控制参数等缺陷,引入了惯性权重,利用混沌理论对算法参数进行调整,使算法兼顾全局搜索与局部搜索能力的均衡。同时将精英保留策略融入到萤火虫算法当中,加快了算法收敛的速度。为了减少网络重构中出现的大量不可行解,对网络拓扑进行了简化操作,缩短了编码维数,提高了寻优效率。最后通过算例分析,验证了该算法的有效性与实用性。     

Analogue filter group delay optimization using a stochastic approach

An analogue filter group delay response is optimized using an all‐pass network connected in the cascade of the filter. This contribution introduces an original method of all‐pass network correction designing of using a random‐based approach. The main objective of the method is the calculation of an optimal all‐pass network order and optimal coefficients of its transfer function. To realize this objective it is necessary to find minima of so‐called optimization spaces. The spaces definition provides an important generalization of the optimization task. The original stochastic approach is used to find the mentioned minima of the spaces. The minima can be detected using several probability densities. The method combines advantages of a numerical approach with rigorous analytical pre‐processing. Compared to current optimization methods, the described approach provides very good convergence, velocity and especially independence from the initial estimation of the all‐pass network transfer function coefficients. The original objective function ensures absolutely stable convergence in the multidimensional optimization spaces. This objective function was developed with regard to properties of the analogue filters. The designed method is illustrated by a few practical optimizations. A well‐known circuit simulator, Micro‐Cap, is used as a comparative system because of its relatively good optimization algorithm. All the presented original algorithms and functions are debugged in the MATLAB^® environment. Copyright © 2009 John Wiley & Sons, Ltd.     

考虑群延迟和暂态时延的短窗低通滤波器设计

为采用基于采样值和正弦信号模型的快速保护算法,并防止重采样环节的频率混叠,智能变电站的数字化保护需要数字低通滤波器配合。提出一种基于Tukey窗函数,并且同时考虑滤波器幅频特性和群延迟、暂态时延的低通滤波器设计方法。该方法首先确定窗函数时域宽度Tc和截止频率fc,再根据采样频率fs和固定不变的fc,确定滤波器的长度N≤2fs/fc,最后根据N和fc得到完整的滤波器系数。通过理论分析、数字仿真和静态实验,研究了所设计滤波器的幅频特性、群延迟和暂态时延。对采用所设计滤波器的母线保护进行RTDS实验,通过对比表明,按所提方法设计的滤波器在群延迟和暂态时延性能上明显优于传统窗函数法设计的滤波器,降低了滤波器环节对保护速动性的影响。     

基于改进遗传算法的无源滤波器设计

利用遗传算法对无源滤波器电路参数进行全局优化并对算法进行改进。在标准遗传算法的基础上,引入了自适应的遗传操作和最优保存策略。相对于经典滤波器设计方法,可不依赖先验知识而获得近似最优解,自动化程度高。仿真结果表明改进后的算法性能良好。     

基于混合粒子群算法的配电网滤波器优化配置研究

将人工萤火虫算法、禁忌算法与粒子群算法相结合,提出一种混合粒子群算法,并将其应用到电力系统滤波器优化配置中,用于减轻电网谐波污染。建立滤波器的基本模型,以滤波器投资最少为目标函数,采用混合粒子群算法进行寻优,得到滤波器相应优化参数。通过IEEE实例仿真分析,验证了所提改进算法及模型的正确可行性。     

Optimal approximation of asymmetric type fractional-order bandpass Butterworth filter using decomposition technique

In this letter, the optimal rational approximation of fractional-order bandpass Butterworth filter (FOBBF) is presented. The transfer function of the FOBBF is decomposed into a multiplication of first-order and second-order terms. As a result, the design stability conditions can be easily satisfied using only the variable boundary constraints. The proposed technique generalizes the symmetric fractional-order roll-off characteristic as only a special case of the asymmetric one. Several examples are presented to validate the modeling efficacy.     

天牛须搜索算法实现小波滤波器直接频域逼近

针对频域法构造小波滤波器方法较少、稳定性无法保证、逼近精度不高等问题,基于天牛须搜索算法提出了一种小波滤波器直接频域逼近方法.首先根据小波滤波器电路的基本要求设计逼近有理式,然后加入电路实现所需的稳定性、正实性和初值为零的约束条件,建立小波滤波器逼近的频域优化模型.再以高斯小波和Marr小波为例,使用天牛须搜索算法求解...     

改进遗传算法在混合有源滤波器的研究

针对混合有源滤波器设计中无源滤波器的重要性,采用改进遗传算法,对无源滤波器的成本、无功补偿和滤波效果三个方面进行参数优化,得到多组最优目标,改善了以往遗传算法存在的早熟等问题,而且选取优化后的三组无源滤波器参数应用到混合有源滤波器,通过Matlab对其滤波效果进行了仿真,并将其滤波效果分别与优化前的滤波效果进行了比较,结果表明,经过优化的混合有源滤波器的滤波效果总体上均比参数优化前的效果好,而且可以根据谐波实际情况来调整无源滤波器的参数,并都相应的减小了有源滤波器容量,提高了混合滤波器的性价比。