基于电压的自治微电网分布式协调控制

针对自治微电网中频率与有功需求没有直接联系的情况,结合不同微电源的特点,给出了以本地节点电压作为调节目标实现有功(无功)平衡的分布式控制策略。有功可控的主动式电源以其有功输出来调节节点电压,实现了电压水平在长时间尺度下的稳定;电压源模式的储能式电源维持其节点电压幅度和相位稳定,保证电压水平的短期稳定和无功平衡;工作在有功调压模式的储能式电源以其有功输出来维持其节点电压水平的短期稳定;清洁能源有功输出跟随外部有功输入。利用储能式电源电压设定与其储能水平的反比关系,实现储能式电源充放电的分布式控制。给出了基于上述控制策略的单元控制方法,并以仿真验证了控制策略和单元控制的有效性。     

Basic concept and decentralized autonomous control of super‐distributed energy systems

New small‐scale dispersed generation systems, such as fuel cells and micro gas turbines, have made remarkable advances lately and they will be applied practically in the near future. Although a large number of researches on the introduction of small‐scale dispersed generation systems have been carried out, only a small number of small‐scale dispersed generation systems are considered in these researches. Therefore, little is known about problems to be solved when a large number of small‐scale dispersed generation systems are introduced into electric power systems. This paper deals with a super‐distributed energy system that consists of a great number of dispersed generation systems such as fuel cells, micro gas turbines, and so on. The behavior of a customer with a dispersed generation system is simulated as the Ising model in statistical mechanics. The necessity of a distribution network in super‐distributed energy systems is discussed based on the Ising model. The feasibility of decentralized autonomous control using vicinity information is also investigated on the basis of stability analysis of the Hopfield neural network model. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(1): 43–55, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10368     

基于下垂控制的低压微电网故障控制策略

下垂控制的分布式电源(Distributed Generation, DG)接入孤岛微电网时,可在故障时呈现电压源特性以维持母线电压稳定。针对低压线路与DG对短路电流贡献能力较弱的特点,分析了非故障与对称故障时DG输出功率与母线电压的关系。提出了故障时根据输出阻抗以设置有功、无功输出参考值与改进的下垂控制策略,解决了故障时电压骤降与频率波动对输出功率的影响。计及DG输出电流受限的情况下,实现了故障时以最大功率输出并尽可能提高母线电压的目的。仿真算例结果验证了所提方法的有效性。     

基于模糊单神经元PI的微电网频率自适应控制

在采用下垂控制策略的传统微电网中存在母线频率随负载增大而下降的问题,为确保母线频率不偏移标准频率,需要采取频率恢复控制策略。目前实现频率恢复的常用方法是基于比例-积分(PI)的控制策略。由于微电网网络结构和系统参数存在变化,PI控制可能无法满足频率控制快速响应、恢复的需求。为解决该问题,文中提出在第二层控制微电网中央控制器中使用单神经元自适应PI控制算法作为频率恢复算法,实现频率无差控制。为进一步增强系统的鲁棒性、加快频率的恢复,使用模糊控制器对单神经元PI控制器的神经元比例系数进行在线优化,并通过仿真与固定神经元比例系数的单神经元自适应PI控制进行对比,证明了所提改进控制策略可改善频率恢复控制的暂态性能,加快微电网的频率恢复。     

Adaptive intelligent techniques for microgrid control systems: A survey

This paper introduces a survey on the adaptive and intelligent methods that have been applied to microgrids systems. Interestingly, the adaptive technique is effectively exercised in various control issues including stability, tracking error, and parameter uncertainties. Adaptive control has been extremely developed by using intelligent algorithms to automatically tune the control parameters namely fuzzy logic, particle swarm optimization, bacterial search algorithm, and etc. The objective is to evaluate and classify the design control methods and evaluation algorithms for the microgrid systems to maintain stability, reliability, and load variations by adjusting the controller parameters especially in standalone operation mode. The stability of islanded microgrids are constantly impacted by the related loads. A significant part of the research on an islanded microgrid involves droop control technique. In normal operation, distributed generation units and storage units provide power quality control. Once a shutdown is occurred, microgrid can be isolated from the main grid and operate in a local grid to support the local loads. Thus, distributed generations co-operate storage units to sustain the stability of the islanded microgrid.     

基于ZigBee的微网控制策略研究与实现

良好的微网控制策略是解决分布式电源并网的重要方法。在研究微网控制策略的基础上,提出了利用物联网的技术和手段对相应的功能进行设计和实现的方案。介绍了微网的运行方法,选用了Droop控制方法作为微网的并网控制策略,并采用无线传感网络技术对其功能进行了实现。     

神经网络PI自适应控制及其应用

:基于传统PID控制和人工神经网络技术 ,提出一种神经网络PI自适应控制策略 ,并把它用于一电液非线性伺服系统的位置控制 .仿真研究结果表明 ,所提出的神经网络PI自适应控制策略可行 ,对改善非线性伺服控制系统的鲁棒性和动静态特性具有积极作用     

基于有限时间一致性的微网分布式二次控制

针对孤岛运行模式下的微电网一次控制采用下垂控制易受到线路阻抗特性、微网拓扑结构等因素的干扰,造成频率与电压的波动以及功率难以比例分配的问题,提出一种基于有限时间一致性的微电网分布式二次控制策略来实现频率与电压无静差调节以及功率按比例分配的控制目标.所提控制策略结合多智能体理论来构建微电网的分布式控制结构,各分布式电源仅...     

基于自适应ANN的孤岛微网群电压频率分布式协同控制

针对孤岛微网群稳定运行难度大,电压频率控制极为复杂的问题,本文提出了一种适用于含多逆变器分布式电源(distributed generations, DGs)微网群(microgrid cluster, MGC)的智能电压频率协同控制方法。首先,该方法利用Lyapunov理论和基于逆变器DG的动态特性设计了基于模型化的控制器;然后,利用人工神经网络(Artificial Neural Network, ANN)来近似上述动态特性,从而得到不需要DG参数先验信息的智能控制器,此外,所提控制器不需要使用电压和电流PI控制器;最后,通过不同场景下的仿真分析,验证了所提控制器的有效性,另外,本文还利用Lyapunov分析,证明了跟踪误差和神经网络权值最终一致有界,从而可实现了较好的电压和频率动态调节。     

基于智能多代理的能量协调控制在直流微网中的应用

提出一种基于智能多代理技术的能量协调控制方法,用于直流微网的能量管理与电压控制.对直流微网的架构进行设计,实现对光伏电池、燃料电池及蓄电池的数学建模.设计了一个2层的智能多代理系统,对直流微网的并网、解列,以及光伏电池、燃料电池、负荷及蓄电池的能量管理进行协调控制.从微源和负荷各种状态中提取了8个特征量及13种不同动作作为神经网络的输入和输出参数,训练并实现了控制中心Agent的决策器.通过MATLAB/Simulink仿真对光照变化、并网时负荷增加后断网及孤岛时负荷增加后并网这3种算例进行分析,验证了该智能多代理能量协调控制策略的可行性.     

基于固定时间一致性算法的孤岛微电网分布式容错二次控制策略

随着微电网信息侧和物理侧的耦合日益紧密,软件密集型控制器和电力电子设备的大规模应用增加了微电网遭受攻击和故障的可能性,从而影响微电网的稳定运行。为此,针对孤岛交流微电网控制通道中潜在的执行器故障和传感器故障,提出了一种基于固定时间一致性算法的分布式容错二次控制策略。首先,建立了同时计及执行器故障和传感器故障的下垂控制模型。其次,分别设计了上层分布式一致性控制算法和下层本地容错控制算法,分析了控制器对未知故障的抑制机理,从理论上证明了所提分布式容错二次控制策略的固定时间收敛特性,并进一步观测了传感器故障信号的波形。最后,算例仿真结果验证了所提控制策略的有效性。     

智能配电系统分区电压控制技术研究综述

配电系统电压控制已经成为配电运行控制系统中最重要的功能之一。有效的电压控制可以降低线损,改善馈线电压水平以及提高系统安全性。在对DG接入配电系统带来的复杂电压波动问题产生的原因进行分析的基础上,分析配电系统电压控制的主要手段,指出分层电压控制是智能配电系统中广泛使用的电压控制方案,而其中的分区电压控制层是提高系统电压质量、提升系统电压调节速度、保障系统电压稳定的中坚环节,同时也是连接中央电压控制和本地电压控制的关键环节。继而对分区电压控制在微网和主动配电网中的研究成果进行针对性的回顾与评述。最后对智能配电系统分区电压控制技术发展方向进行了展望。     

基于协同强化学习的微电网分布式两级电压优化控制

由于微电网中分布式电源组成复杂,运行模式多样,孤岛微电网的电压恢复控制面临着不确定性干扰的影响。为此,针对不确定性干扰下微电网的二级电压恢复控制问题,提出了一种基于协同强化学习的微电网分布式两级电压优化控制方法,实现孤岛模式下微电网的电压调节控制。首先构建孤岛微电网分布式一致性协同电压控制算法,并建立李雅普诺夫函数稳定性判定方法。其次根据控制器性能与控制器增益参数的关系,求解孤岛微电网电压控制器增益上界,并根据控制器增益参数上界限制强化学习智能体动作集。随后,采用强化学习算法优化二级控制器增益参数,给出相应的强化学习智能体状态集、协同全局奖励函数。最后在Matlab/Simulink上通过仿真实验验证了所提出的控制方法的有效性和适应性。     

基于模型预测控制算法的多风储直流微电网分布式电压二次控制策略

针对含多组风储单元的直流微电网中蓄电池的电压优化控制问题,提出了一种基于模型预测控制算法的分布式电压二次控制策略.设计了一种多步长预测一致性模型作为电压预测模型,通过目标函数最小化求解预测系数,得到最优电压二次控制补偿量加入一次控制中,将传统一致性算法中比例积分控制器下的偏差调节问题转化为模型预测控制器下的电压跟踪问题进行求解,从而实现对直流母线电压动态响应的滚动优化.该方法有效解决了传统一致性算法下电压控制策略瞬态特性差和部分工况下存在控制误差等问题,并通过MATLAB/Simulink仿真平台搭建模型验证了不同工况下所提策略的有效性和优越性.     

Adaptive fuzzy finite-time decentralized control for large-scale stochastic nonlinear systems

An adaptive finite-time decentralized control algorithm for a class of large-scale stochastic nonlinear systems is presented. The fuzzy logic system is used to estimate uncertain nonlinearities. One advantage of the developed scheme is that each subsystem only needs to update one adaptive parameter, which alleviates the burden of online estimation. The dynamic surface control method is employed to reduce the “complexity explosion” caused by the repetitive derivation of the intermediate variable function in the backstepping control scheme. A new decentralized controller is designed so that all signals of the controlled system are bounded and the tracking error converges to a small residual set around the origin within a finite time. The simulation results of a numerical example illustrate the effectiveness of the method.     

自适应高通滤波下垂控制的孤岛直流微电网功率分配控制

直流微电网孤岛运行时,由于不匹配线路阻抗及本地负荷因素的影响,传统“电压-功率”下垂控制难以使得各分布式电源按照下垂系数精确分配负荷功率。提出了一种基于自适应高通滤波下垂控制的孤岛直流微电网功率分配控制策略。通过在分布式电源下垂控制中引入采样保持器,根据采样保持器输出结果不断自适应地修改下垂系数,进而减小分布式电源实际输出功率与期望输出功率的偏差,同时高通滤波控制也有效提高了母线电压质量。最后基于 RTDS 仿真平台搭建不同工况下的实验模型,实验结果验证了所设计控制策略的有效性。     

Adaptive identification and control of linear periodic systems using second‐level adaptation

At the present time, there is a great deal of interest in the adaptive control of systems with rapidly varying parameters. Such problems arise in different forms and in many disciplines including finance, sociology, biology, and engineering. In general, these problems are intractable mathematically and the time variations have to be classified in some form to obtain rigorous results. In this paper, we consider the adaptive identification and control of linear systems with periodically varying parameters (referred to as linear time‐varying periodic (LTP) systems). The class of systems with known periodic parameters has been investigated widely since the pioneering work of Floquet and lends itself to rigorous mathematical analysis. However, very little was known until the early years of the last decade concerning the adaptive control of such systems. The problem was introduced by Xu and explored in detail by Narendra and Zhiling in 2006 and 2009, respectively. In 2012, a new method was introduced in adaptive control by Han and Narendra and is referred to as second‐level adaptation. In this paper, the adaptive identification and control of LTP systems using second‐level adaptation is discussed.     

基于数据驱动的孤岛直流微电网二次控制

针对孤岛直流微电网,提出一种数据驱动的无模型二次控制策略.利用直流微电网系统输入、输出的过程数据以及偏格式动态线性化方法建立系统的数据模型.通过设计新型的无模型二次功率和电压控制器,分布式电源按其容量成比例地输出功率,同时使用最大电压补偿的方法恢复系统母线电压.通过数学分析严格证明该直流微电网系统在不同运行条件下是闭环...     

Adaptive backstepping neural control of state‐delayed nonlinear systems with full‐state constraints and unmodeled dynamics

In this paper, the problem of adaptive neural control is discussed for a class of strict‐feedback time‐varying delays nonlinear systems with full‐state constraints and unmodeled dynamics, as well as distributed time‐varying delays. The considered nonlinear system with full‐state constraints is transformed into a nonlinear system without state constraints by introducing a one‐to‐one asymmetric nonlinear mapping. Based on modified backstepping design and using radial basis function neural networks to approximate the unknown smooth nonlinear function and using a dynamic signal to handle dynamic uncertainties, a novel adaptive backstepping control is developed for the transformed system without state constraints. The uncertain terms produced by state time delays and distributed time delays are compensated for by constructing appropriate Lyapunov‐Krasovskii functionals. All signals in the closed‐loop system are proved to be semiglobally uniformly ultimately bounded. A numerical example is provided to illustrate the effectiveness of the proposed design scheme.     

Phase synchronization of autonomous AC grid system with passivity-based control

This paper discusses a ring-coupled buck-type inverter system to harness energy from direct current (DC) sources of electricity. The DC-DC buck converter circuit is modified with an H-bridge to convert the DC input voltage to a usable alternating current (AC) output voltage. Passivity-based control (PBC) with port-controlled Hamiltonian modelling (PCHM) is a method where the system is controlled by considering not only the energy properties of the system but also the inherent physical structure. PBC is applied to achieve stabilization of the AC output voltage to a desired amplitude and frequency. Unsynchronized output voltages in terms of phase angle or frequency can cause detrimental effects on the system. Phase-locked loop (PLL) is employed in the ring structure to maintain synchronization of the AC output voltage of all inverter units in the ring-coupled system.