新能源微电网不确定性负荷规划方法研究

为提高新能源微电网负荷预测及规划能力,提出基于串行集成学习和负载自适应均衡配置的新能源微电网不确定性负荷规划方法.构建新能源微电网不确定性负荷的线性空间融合模型,通过重组非线性时间序列,完成新能源微电网不确定性负荷的输出时间序列分析.采用串行集成学习方式调节新能源微电网不确定性负荷稳定性,结合负载均衡调度法完成新能源微...     

A robust nonlinear stabilizer as a controller for improving transient stability in micro-grids

This paper proposes a parametric-Lyapunov approach to the design of a stabilizer aimed at improving the transient stability of micro-grids (MGs). This strategy is applied to electronically-interfaced distributed resources (EI-DRs) operating with a unified control configuration applicable to all operational modes (i.e. grid-connected mode, islanded mode, and mode transitions). The proposed approach employs a simple structure compared with other nonlinear controllers, allowing ready implementation of the stabilizer. A new parametric-Lyapunov function is proposed rendering the proposed stabilizer more effective in damping system transition transients. The robustness of the proposed stabilizer is also verified based on both time-domain simulations and mathematical proofs, and an ultimate bound has been derived for the frequency transition transients. The proposed stabilizer operates by deploying solely local information and there are no needs for communication links. The deteriorating effects of the primary resource delays on the transient stability are also treated analytically. Finally, the effectiveness of the proposed stabilizer is evaluated through time-domain simulations and compared with the recently-developed stabilizers performed on a multi-resource MG.     

液压马达式汽车主动稳定杆系统建模与控制

以液压马达式主动稳定杆系统为研究对象,推导得到了液压马达式主动稳定杆的非线性动力学模型。利用线性化反馈的滑模控制方法设计了其控制器,并利用Lyapunov理论对控制系统的稳定性进行了证明。通过CarSim和MATLAB/Simulink对主动稳定杆系统进行了联合仿真,得出安装液压马达式主动稳定杆系统的车辆在双移线工况下运行的响应曲线。为了验证设计的控制方法,进行了实车试验。结果表明,与被动稳定杆相比,主动稳定杆系统具有较好的抗侧倾特性以及乘坐舒适性。     

基于电流解耦控制的光伏并网系统仿真分析

光伏并网发电是太阳能利用的重要途径,而并网逆变器结构的选择和控制策略的改进是其研究的重点。在PSCAD/EMTDC平台上搭建了单级三相光伏并网系统的仿真模型,仿真模型中的并网逆变器采用双闭环的控制策略,其中电流内环根据非线性控制理论中反馈线性化的思想,实现电流的解耦控制,电压功率外环采用PI控制。仿真结果表明:该控制策略不仅控制精度高,稳定工作域大,并且必要时能在一定范围内对配网的无功进行调节,提高配网稳定性。     

Modeling,control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method

Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current–voltage or power–voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.     

Nonlinear dynamic buckling and stability of autonomous structural systems

A general approach for the nonlinear dynamic buckling and stability of dissipative or nondissipative structural systems governed by autonomous ordinary differential equations (ODEs) is presented. Geometrically imperfect systems with or without symmetric imperfections, as well as statically stable systems, which, in addition to a monotonically rising (stable) equilibrium path exhibit an unstable complementary path, are considered. The role of the dynamic buckling mechanism of the basin of attraction of a stable equilibrium point (on the prebuckling path), as well as the inset (stable) and outset (unstable) manifolds of a saddle (on a physical or complementary unstable path), are comprehensively explained. A static energy criterion for determining dynamic buckling loads for vanishing (but nonzero) damping and lower bound estimates of exact dynamic buckling loads are presented. Metastability, loading discontinuity and chaos-like phenomena are also revealed. The analysis is supplemented by two illustrative models of practical engineering importance.     

Design and implementation of a new modified sliding mode controller for grid-connected inverter to controlling the voltage and frequency

As the output power of a microgrid with renewable energy sources should be regulated based on the grid conditions, using robust controllers to share and balance the power in order to regulate the voltage and frequency of microgrid is critical. Therefore a proper control system is necessary for updating the reference signals and determining the proportion of each inverter in the microgrid control. This paper proposes a new adaptive method which is robust while the conditions are changing. This controller is based on a modified sliding mode controller which provides adapting conditions in linear and nonlinear loads. The performance of the proposed method is validated by representing the simulation results and experimental lab results.     

基于ＰＩＤ控制算法的直流微网容错控制方法研究

构建直流微网容错控制对象模型,调节直流微电网的输出回路参数;以输出功率、直流微网的 参考电压、弱电网下系统惯性响应特征等为约束参量,构建直流微网容错控制目标函数,在不同电网强度下 进行直流微网容错控制的参数自整定性调节,采用无功环比例积分控制方法进行直流微网容错寻优分析, 建立模糊 ＰＩＤ控制模型,采用变结构的模糊 ＰＩＤ控制方法进行直流微网容错控制过程中的自适应加权学习 和误差反馈调节,实现直流微网容错控制改进设计。仿真结果表明,采用该方法进行直流微网控制的容错 性能较好,输出稳定性较强,具有较好的直流微网输出增益。     

Adaptive nonlinear control using input normalized neural networks

An adaptive feedback linearization technique combined with the neural network is addressed to control uncertain nonlinear systems. The neural network-based adaptive control theory has been widely studied. However, the stability analysis of the closed-loop system with the neural network is rather complicated and difficult to understand, and sometimes unnecessary assumptions are involved. As a result, unnecessary assumptions for stability analysis are avoided by using the neural network with input normalization technique. The ultimate boundedness of the tracking error is simply proved by the Lyapunov stability theory. A new simple update law as an adaptive nonlinear control is derived by the simplification of the input normalized neural network assuming the variation of the uncertain term is sufficiently small.     

基于零力矩点的车辆侧倾评价指标及侧倾控制研究

为了使车辆的行驶状态和稳定程度更为便捷的显现出来，以及对系统研发初期的效果进行评价，需要引入一个比较准确的评价指标，使其可以判断并量化车辆的侧倾稳定性，因此将零力矩点(Zero-moment point,ZMP)的概念引入到车辆的侧倾评价体系之中，通过对车辆侧倾模型以及刚性车辆模型零力矩点的推导，从而来预测车辆的侧倾倾向，并得出车辆的侧倾指数y_zmp，根据其侧倾指数y_zmp算出侧倾指标s；再通过与其他现有侧倾评价指标的对比与转换，从而证明该指标的准确性以及有效性。之后，再以某19座商用车为例，建立整车模型，并设计H_∞鲁棒控制的算法对半主动横向稳定杆的侧倾刚度进行实时调节，最后通过Trucksim和Simulink联合仿真来验证两种控制方法的有效性，同时，以侧倾指标来对比判断鲁棒控制算法的半主动横向稳定杆与被动横向稳定杆、模糊PID控制的半主动横向稳定杆对于侧倾运动的改善效果。根据仿真结果显示，半主动横向稳定杆相对于被动横向稳定杆来说，其在各个侧倾参数上都有明显的降低，并且相较于模糊PID控制的半主动横向稳定杆，H     

Delay-tolerant distributed voltage control for multiple smart loads in AC microgrids

With increasing penetration of variable loads and intermittent distributed energy resources (DERs) with uncertainty and variability in distribution systems, the power system gradually inherits some features (e.g., lack of rotating inertia), which leads to the voltage instability in microgrids. As a means to provide stability support for smart grid against high penetration of intermittent DERs, inverter-based smart loads across the distribution grid has been suggested recently. Accordingly, this paper presents a delay-tolerant distributed voltage control scheme based on consensus protocol for multiple-cooperative smart loads through effective demand-side management in ac microgrids, in which the time-delay effect on transmission communication occurred in information exchanges is considered. The proposed distributed voltage control scheme always enables the output voltage of each smart load to be synchronized to their reference value, which improves the robustness of system stability against transmission communication delays. The Lyapunov–Krasovskii functions are employed to analyze the stability of our proposed distributed control scheme, then the delay-independent stability conditions are derived, which allows some large communication delays. Moreover, the sensitivity analysis is developed to show how the time delay affects system dynamics in order to validate the robustness of proposed delay-independent stability conditions. Furthermore, a sparse communication network is employed to implement the proposed distributed control protocols, which thus satisfies the plug-and-play requirement of smart microgrids. Finally, the simulation results of an ac microgrid in MATLAB/SimPowerSystems are presented to demonstrate the effectiveness of the proposed control methodology.     

Rigid Rotor Stability Analysis on Finite Hydrostatic Double-Layer Porous Oil Journal Bearing with Velocity Slip

A theoretical investigation has been carried out for stability characteristics of a finite hydrostatic double-layer porous oil journal bearing considering the effect of Beavers-Joseph velocity slip at the porous film interface. A linearized perturbation method has been used to obtain the threshold of stability in terms of critical mass parameter. The effect of slip parameters, eccentricity ratios, bearing feeding parameter, and slenderness ratio on the stability is investigated. Furthermore, nonlinear transient analysis is carried out to determine the system stability by tracing the journal center locus. Several trajectories of the journal center locus have been obtained for different operating conditions and are depicted with the help of graphics.     

Optimal control in microgrid using multi-agent reinforcement learning

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode.     

废旧晶体硅光伏组件回收技术研究进展

随着全球光伏产业的蓬勃发展,光伏组件作为光伏电站中最关键的部件,面临着大规模的资源流失及重金属在环境中的扩散问题,回收报废光伏组件中所含的二次资源将成为解决环境污染问题、推动光伏行业可持续发展的重要途径。为实现光伏组件的高效拆解和解离,采用热、机械和化学等处理工艺备受研究者们关注。在综合分析太阳能电池回收完整性的基础上,提出了晶体硅光伏组件的两种回收技术路线——废旧组件的电池无损回收路线和成分综合回收路线。对电池无损回收路线中不同的分层工艺进行了深入分析,总结归纳了电池硅片破损的原因,着重讨论了光伏组件低温破碎及高压脉冲破碎最新的研究成果、反应机理等。同时,对废旧光伏组件材料的回收再利用、经济性及环境性分析进行了系统的综述。最后,对废旧光伏组件资源化回收的发展趋势及前景进行了展望,为未来研发更加绿色高效的回收工艺提供参考。     

常见光伏阵列拓扑重构方法综述

针对光伏发电系统中由于环境和光伏系统本身失配造成的输出功率降低问题,将系统拓扑重构技术应用到光伏发电系统中。在应对失配条件时,目前常采用的增加光伏系统输出功率的方法是使用改进的最大功率跟踪方法,然而该类方法已被广泛研究和渐趋成熟,而为了使得光伏系统的输出性能更加优化,对光伏系统拓扑结构的研究已日益受到关注,不同工作环境下对光伏系统的拓扑结构进行重构的方法对于整个光伏系统输出性能的提高有着重大意义。开展了常用光伏阵列拓扑结构重构策略的研究,对其优缺点进行了对比分析,在此基础上,对各种光伏阵列拓扑重构方法进行了评估。研究结果表明,面对不同工作环境时选择合适的光伏阵列拓扑结构,从而可以有效提高光伏阵列的输出特性。     

考虑关键非线性特征的集成式电子液压制动系统主缸液压力精确控制

针对具有"电动机+减速机构"形式的解耦式电子液压制动系统（Electro-hydraulic brake system,EHB）展开研究。针对主缸液压力控制过程中出现的爬行、死区和振荡等问题,设计一种考虑关键非线性特征（摩擦、PV特性）的主缸液压力精确控制算法。基于LuGre模型对摩擦非线性进行补偿,设计了压力自适应控制器。针对压力闭环控制在系统死区工作点处出现的问题,采用基于死区补偿的非线性控制方法。结合以上两种方法的优点,设计基于LuGre摩擦模型前馈补偿和死区补偿的联合控制方法,能够在考虑系统关键非线性特征的基础上,精确控制主缸液压力。通过联合仿真（AMESim&Simulink）和硬件在环测试对比验证各闭环控制系统的时频域响应特性,联合控制方法提高了系统的压力动态跟踪精度和响应速度。     

Modified active disturbance rejection control for time-delay systems

Industrial processes are typically nonlinear, time-varying and uncertain, to which active disturbance rejection control (ADRC) has been shown to be an effective solution. The control design becomes even more challenging in the presence of time delay. In this paper, a novel modification of ADRC is proposed so that good disturbance rejection is achieved while maintaining system stability. The proposed design is shown to be more effective than the standard ADRC design for time-delay systems and is also a unified solution for stable, critical stable and unstable systems with time delay. Simulation and test results show the effectiveness and practicality of the proposed design. Linear matrix inequality (LMI) based stability analysis is provided as well.     

Stability analysis of a rotor bearing system due to surface waviness and number of balls

In the paper, the stability analysis of a rigid rotor supported by ball bearings has been studied. In the analytical formulation, the contacts between balls and races are considered as nonlinear springs, whose stiffnesses are obtained by using Hertzian elastic contact deformation theory. The implicit type numerical integration technique Newmark-β with Newton–Raphson method is used to solve the nonlinear differential equations iteratively. The effects of surface waviness and the varying number of balls on stability of rotor bearing system are observed. All results presented in form of fast fourier transformations show that the vibration characteristics of the rotor and its bearings change, when the bearings operate in different regions of their nonlinear load deflection characteristics. From the analysis, it is implied that the number of balls and number of waves in the ball bearing are two important governing parameters affecting its dynamic behavior.     

电液控制的主动横向稳定杆的应用仿真研究

为了改善商用车的侧倾稳定性,设计了一种集液压控制与电机控制的优势于一体,具有较高控制精度和较大反侧倾力矩的电液控制主动横向稳定杆,并以某19座商用车为例,建立了包含转向、俯仰、侧倾,车身垂向运动在内的九自由度整车模型,对其中的主动横向稳定杆设计了一种PID+前馈的控制策略以提高控制精度,减少迟滞,并通过Simulink和Trucksim的联合仿真以验证其有效性。在附着系数为0.8的B级路面上,分别进行鱼钩、方向盘角阶跃和双移线三种不同的工况下的仿真。结果表明,与被动稳定杆相比,提出的这种主动稳定杆能够让车身侧倾角,横摆角速度,侧向加速度和质心侧偏角均有(20~45)%的降低,极大的提高了车辆的侧翻稳定性。     

Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input - delay systems

In this paper a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller has been proposed for a class of nonlinear systems with input-delay in presence of unknown disturbance and uncertainties. In this method, the predictor has been utilized to estimate the future state variables of the controlled system to compensate for the time-varying delay. The T2FNN is used to estimate some unknown nonlinear functions to construct the controller. By introducing a new adaptive compensator for the predictor and controller, the effects of the external disturbance, estimation errors of the unknown nonlinear functions, and future sate estimation errors have been eliminated. In the proposed method, using an appropriate Lyapunov function, the stability analysis as well as the adaptation laws is carried out for the T2FNN parameters in a way that all the signals in the closed-loop system remain bounded and the tracking error converges to zero asymptotically. Moreover, compared to the related existence predictive controllers, as the number of T2FNN estimators are reduced, the computation time in the online applications decreases. In the proposed method, T2FNN is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. The proposed T2FNNP controller is applied to a nonlinear inverted pendulum and single link robot manipulator systems with input time-varying delay and compared with a type-1 fuzzy sliding predictive (T1FSP) controller. Simulation results indicate the efficiency of the proposed T2FNNP controller.