基于PSO算法的电液伺服调节环节参数辨识

鉴于汽轮机电液伺服调节环节大量存在的非线性环节,并且常规辨识方法很难对调速系统中大量存在的非线性环节参数进行辨识,从而难以得到准确的数学模型,本研究将粒子群优化算法引入参数辨识研究中,针对算法易早熟收敛的缺点,采用了基于双层进化的多粒子群优化算法,同时,通过现场实验研究对参数辨识的方法及效果进行验证.试验结果表明,利用多粒子群优化算法对建立的汽轮机电液调节系统执行环节的参数进行辨识能取得理想效果,满足工程应用的需求.     

水轮机引水系统精细化模型参数辨识研究

由于传统的水轮机调速建模在引水系统部分无法较为准确地辨识参数,针对水力损失函数复杂的模型机理结构,通过黑箱辨识与曲线拟合的方法,搭建了水力损失函数精细化模型。通过改进型的粒子群算法对模型参数进行辨识,改善了粒子群算法收敛性与容易陷入局部最优等问题并用算例验证了模型与方法的有效性。     

基于改进型引力算法的汽轮机调速系统参数辨识

为了解决传统汽轮机调速系统参数辨识方法周期长、适应性差和人工参与度过高等问题,提出了一种基于引力搜索算法(GSA)的改进型辨识方法(VGSA)。该方法在保留粒子群算法"记忆"特性的基础上,根据粒子的适应度,对算法中的引力系数进行动态调整,使得粒子搜索空间随迭代过程而逐步缩小,从而大大提高了粒子的寻优效率。以某600MW火力发电机组的汽轮机调速系统为研究对象,利用改进型引力搜索算法进行了多参数辨识。相较改进前的引力搜索算法(IGSA)的结果表明,本文提出的改进型引力搜索算法VGSA在速度和精度上都明显优于IGSA算法。该方法为汽轮机调速系统的参数辨识提供了一种新的有效手段。     

600MW汽轮机调速系统试验及辨识研究

以某电厂6号机组(600MW)为研究对象,为对其调速器系统模型参数进行辨识,设计并实施了相关的试验。在辨识过程中,针对常规参数辨识方法在进行汽轮机调速系统模型参数辨识时所遇到的困难,采用了一种基于遗传算法的模型参数辨识方法,并利用Matlab及其simulink工具箱予以实现。结果表明,该方法较为适用于汽轮机调速系统模型参数的辨识,辨识所得到的模型也达到了较高的仿真精度。     

基于改进粒子群算法的水轮机调速系统建模

针对电力系统稳定计算分析软件中水轮机调速系统模型过于简单、粗略的问题,建立了水轮机调速系统非线性模型,并提出参数实测与改进的粒子群智能优化算法结合的模型辨识方法,获得了调速器模型参数、水轮机-引水道模型参数.现场实测数据的模型仿真结果验证了该模型辨识方法的准确性,该模型优于电力系统稳定计算软件中的模型,更符合实际.     

混合Box-Jenkins模型交替辨识及在电厂脱硝系统中的应用

混合的Box-Jenkins模型能够较好地表征含噪声干扰系统的特性,针对该模型提出了基于粒子群优化算法的过程模型与噪声模型交替估计辨识方法,避免了常规方法直接对过程模型和噪声模型共同辨识容易陷入局部最优的缺陷。仿真试验表明:交替估计算法可以达到对混合Box-Jenkins模型的精确辨识,其误差约为常规辨识的1/10。为验证方法的实用性,以某电厂机组烟气脱硝系统为对象,建立混合Box-Jenkins模型,利用粒子群算法进行交替辨识,所得过程模型与实际输出基本一致,取得了较好的参数辨识效果,该方法可应用到工业过程中这类系统的参数辨识。     

基于遗传粒子群算法的光伏并网逆变器参数辨识

在并网光伏发电系统模型基础上,通过分析逆变器控制器结构,确定待辨识参数。提出一种基于遗传粒子群(GAPSO)算法的光伏并网逆变器参数辨识方法,同步辨识各控制参数。辨识结果与遗传算法和粒子群算法辨识结果的对比表明,GAPSO参数优化模型在辨识精度和收敛速度方面具有明显的优越性。最后对参数辨识模型的泛化能力进行评价,比较了3种不同扰动情况下的仿真曲线与测试曲线,验证了模型的适用性和准确性。     

超临界机组汽轮机调速系统模型参数确定的新方法

汽轮机调速系统模型参数的确定,对各种热力发电机组的仿真,控制系统的设计及电力系统动态研究具有重大意义.通过蒸汽发电机组有效热平衡数据计算出汽轮机模型参数,得出各种不同工况下参数的变化规律,比实测法更方便简捷实用.对600MW超临界机组汽轮机调速系统的模型参数进行分析计算,并用该模型针对特殊的阶跃响应作出仿真和分析.     

大型风电场失速型机组等值建模的研究

对于风电场中失速型机组的多机等值,采用异步发电机的机电暂态模型求解发电机组的等值电气参数,利用基于传递函数概念的参数辨识方法及最小二乘法求解发电机组的动态等值参数。利用系统等值得结果对一实例进行仿真,结果表明了等值方法的有效性和正确性,为今后研究风电场与电网之间的相互影响提供了良好的模型基础。     

基于混合蛙跳算法的油纸绝缘变压器拓展德拜等值电路参数求解

为了更好地研究变压器油纸绝缘老化状态与拓展德拜等值电路参数之间的相关性,根据实测回复电压特征量参数等值电路模型,建立求解等值电路参数的数学模型,并将该模型转化为非线性优化问题,利用混合蛙跳算法的全局信息交换和局部深度搜索特性对拓展德拜等值电路参数进行参数辨识。通过两台变压器的辨识结果表明,与粒子群算法相比,由混合蛙跳算法辨识的电路参数计算获得的回复电压值与测量值具有更高的重合度,并能够准确地反映变压器油纸绝缘状态。     

实现柴油机全程电子调速PID参数整定的仿真研究

在电控LPG-柴油双燃料发动机试验的基础上，建立了全程电子调速器模型。通过动态调整油泵齿条位置实现对柴油机突变负载下转速的闭环控制，从而保证在不同工况下转速的稳定性。同时，模型实现了不同负载下，对PID参数进行整定，并将整定后的PID参数用于LR6105双燃料发动机的参数整定试验。经试验验证，此仿真模型能降低转速波动率，从而减少大量调试工作。     

压气机动态模型的建立及喘振过程分析

在SIMULINK环境中,建立了压气机动态数学模型。为了模拟压气机喘振和旋转失速现象,压气机特性图被延伸到负流量区域,还考虑到了气体通过压气机的延迟。模拟了压气机的喘振过程,并对压气机压力信号进行FFT变换,检测了压气机喘振。仿真结果表明:模型能预测压气机喘振过程中压力、流量和转速的振荡频率和振幅;压缩系统的转动惯量、稳压室容积等结构参数影响喘振特性;模型动态调节特性好,可用于压气机控制系统模型,具有广泛实用性。     

大型抽水蓄能机组一次调频性能优化

为提高抽水蓄能机组一次调频能力、改善机组运行品质、提高电能质量,通过数学建模仿真研究和现场实际运行试验相结合,对机组进行一次调频试验,并采用Cohen-Coon法优化调节参数,考察机组在不同调节参数下运行时的一次调频响应特性。结果表明,优化后的参数使蓄能机组在一次调频时的调节性能和响应特性得到了较大改善,系统响应速度明显加快,性能指标更优。     

Wind turbine robust disturbance accommodating control using non-smooth H∞ optimization

Disturbance accommodating control (DAC) has been developed in the last decades for wind turbines to control the rotor/generator speed and to reduce structural loads. The method allows accommodating unknown disturbance effects by using the combination of disturbance observers and disturbance rejection controllers. The actual main problem of DAC is to define suitable disturbance observer and controller gain matrices to achieve the desired overall performance including turbine speed regulation in combination with structural load mitigation. The disturbance rejection controller is often designed and tuned separately for individual applications and operating conditions. The closed-loop system stability and uncertainties due to the use of the linearized reduced-order model in controller synthesis procedure are not fully considered. This paper introduces a method to design DAC by optimizing the observer and controller parameters simultaneously to guarantee system performance respecting to structural loads mitigation, power regulation, and robustness. To eliminate the rotor speed control steady-state error due to model uncertainties, partial integral action is included. Simulation results using NREL reference wind turbine models show that the proposed method successfully regulates the rotor speed without error despite the presence of the model uncertainties. Structural loads are also reduced using proposed method compared to DAC designed by Kronecker product method. The proposed approach is able to define a stable and robust DAC controller by solving a non-smooth H_∞ optimization problem with structure and stability constraints.     

Control strategy of a wind turbine drive by an integrated model

In this paper, an integrated equivalent circuit is defined to analyse the operation of a wind generator–rectifier system connected to a DC link, with the electric machine consisting of a surface‐mounted permanent magnet synchronous generator (SPMG) directly coupled to the wind turbine. Such circuit is defined by integrating the models related to the electromechanical equations implemented into a Simulink® code, where the SPMG parameters are derived by the elaboration of sequences of magnetostatic FEM analyses. The integrated equivalent circuit can be very useful to examine the wind generator dynamics because of wind speed variations, and to analyse the influence of the electromechanical parameters on the energy output in order to identify the appropriate control strategies involving the regulation of the rotor speed, the DC link current and the blade pitch angle. In particular, a sensorless algorithm is implemented to estimate the main mechanical quantities (output torque and rotor speed) and to determine the wind speed by means of only electrical measurements. The comparison with an anemometer‐based solution shows that similar performances can be achieved in different operating conditions. The control strategies set up by the circuit model are verified on a 20 kW‐rated SPMG with outer rotor, comparing the sensor and sensorless approaches in terms of capability of energy production, dynamic promptness and sensitivity to parameter disturbances, also with wind turbulence. Copyright © 2008 John Wiley & Sons, Ltd.     

Simulating Feedback Linearization control of wind turbines using high‐order models

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.     

Identification and control of a DC motor using back-propagationneural networks

An artificial-neural-network (ANN)-based high-performance speed-control system for a DC motor is introduced. The rotor speed of the DC motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed, especially when motor and load parameters are unknown. The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The trained neural-network identifier is combined with a desired reference model to achieve trajectory control of speed. The performances of the identification and control algorithms are evaluated by simulating them on a typical DC motor model. It is shown that a DC motor can be successfully controlled using an ANN     

Steady‐state model of a variable speed vapor compression system using R134a as working fluid

This paper presents a steady‐state physical model for a variable speed vapor compression system. Its development and validation for a wide range of operating conditions are presented. The model requires as input parameters: compressor speed, static superheating degree and volumetric flow rates and temperatures of secondary fluids at the evaporator and condenser inlet. Using these input parameters, which can be easily obtained in this kind of facility, the model predicts the operating pressures, the temperature of secondary fluids at the evaporator and condenser outlet, the evaporator and condenser thermal capacities, the electric power consumed by the compressor and the coefficient of performance, COP. The experimental validation of the model has been carried out with 177 tests using R134a as working fluid, concluding that the model can predict the energetic performance of a variable speed vapor compression chiller with an error lower than ±10%. Copyright © 2009 John Wiley & Sons, Ltd.     

水轮机水门的分数阶PID控制策略研究

针对水轮机调速系统的强非线性及易受各种内外部干扰影响,基于分数阶PID控制策略提出了一种新型的水门非线性控制器。通过对水轮机水门开度模型进行反馈线性化,结合分数阶PID控制理论约束自定义的控制变量,且利用遗传算法在线调节控制器的参数。仿真结果证明,与常规PID控制方式相比,所设计的水门分数阶PID控制器能有效地阻尼系统振荡,调速系统的鲁棒性得到较好的改善。     

Thermal performance analysis of a direct-expansion solar-assisted heat pump water heater

A direct-expansion solar-assisted heat pump water heater (DX-SAHPWH) is described, which can supply hot water for domestic use during the whole year. The system mainly employs a bare flat-plate collector/evaporator with a surface area of 4.2 m², an electrical rotary-type hermetic compressor, a hot water tank with the volume of 150 L and a thermostatic expansion valve. R-22 is used as working fluid in the system. A simulation model based on lumped and distributed parameter approach is developed to predict the thermal performance of the system. Given the structure parameters, meteorological parameters, time step and final water temperature, the numerical model can output operational parameters, such as heat capacity, system COP and collector efficiency. Comparisons between the simulation results and the experimental measurements show that the model is able to give satisfactory predictions. The effect of various parameters, including solar radiation, ambient temperature, wind speed and compressor speed, has been analyzed on the thermal performance of the system.