城市集中供热系统节能技术及热力站控制系统的分析

从提高锅炉运行效率、优化供热管网布局、增强整体供热系统的保温性能和解决水力失调问题等方面介绍了城市集中供热系统的节能优化措施,并分析了集中供热的热力站的设计方式。分析认为,相关工作人员应从设计、产热源以及二次网的直埋技术等方面对城市集中供热系统节能技术及热力站控制系统进行优化,从而提高城市集中供热的能力。     

基于Modbus现场总线的热力站监控系统

概述了基于Mo(1bus现场总线的热力站监控系统的整体架构,介绍了总线控制器和Modbus现场总线的技术.特点,并分主站和从站阐述了热力站监控系统的实现过程.热力站监控系统运用Modbus现场总线接口,建立现场总线控制器和组态软件的通讯连接,最终实现热力站数据的实时监测和远程控制.     

采用Micro2080 Controller与MCGS的热力站自控系统设计

为实现热力换热站的无人值守自动运行功能,设计出热力站自动控制系统。采用Micro2080Controller进行热交换站的压力、温度、流量等模拟量信号采集,并对变频器、电动阀门开度、循环泵、补水泵实施控制。采用昆仑通态MCGS实时显示热力参数,并方便的进行系统参数设置和调控。将开发的系统应用到热力交换站,实现了热力交换站的自动补水恒压控制,通过人机界面实现了循环泵和电动阀的控制,以流程画面显示的方式实时显示各项参数,保证了系统稳定可靠运行。     

热力管道泄漏检测系统设计

针对目前供热管道泄漏诊断滞后的问题,介绍了负压波泄漏检测原理,分析了影响定位精确度的主要因素:负压波速度和时间差,以及热网管道沿程温差对负压波速度的影响关系,在此基础上给出了热网管道泄漏故障诊断系统的总体框架。采用GPS授时方式,设计了各热力站高精度的同步数据采集系统,给出了热力站数据采集系统的软硬件设计,实现了故障诊断中心、各热力站数据采集设备的时钟同步。实验结果表明,采集设备的时间同步误差为毫秒级,符合负压波诊断泄漏故障的时间同步要求。     

基于DE-SVM的柴油机气门故障诊断方法及应用

针对柴油机故障诊断样本少的实际问题,结合支持向量机的特性和微分进化算法良好的全局优化性能,提出了一种微分进化算法优化支持向量机方法.利用柴油机气门振动信号实测数据,经小波变换作为诊断模型的故障特征,建立了基于微分进化算法优化支持向量机的柴油机气门间隙故障诊断模型,并与反向传播神经网络算法、基于遗传算法优化支持向量机和基于粒子群优化支持向量机的模型相比较,结果表明:应用微分进化算法优化支持向量机比其他三种算法具有更优性能,能够有效地进行柴油机的故障诊断.     

双端口RAM在PROFIBUS_DP智能从站中的应用研究

在PROFIBUS_DP智能从站设计中,通信的实时性、可靠性是一个重要的衡量指标。本文介绍了双端口RAM IDT7132在PROFIBUS_DP智能从站中的应用。对提高PROFIBUS_DP智能从站通信的实时性、可靠性提供了思路。     

智能站设计在变电二次继电保护中的作用

分析了智能站设计在变电二次机电保护过程中的重要作用,探讨了智能站设计的主要概念以及变电站二次机电保护的主要过程,并分析了智能站设计的相关要素,提出了智能站设计的主要对策和相关注意事项.希望能够为相关工作人员开展智能站设计工作起到一些参考和借鉴作用,从而进一步提升我国变电站二次继电保护水平,保障相关供电系统的安全运行,促进我国电力事业的快速发展.     

平行流式冷凝器的热力性能研究

对平行流式冷凝器热力性能进行了理论和试验分析,得出了影响平行流式冷凝器热力性能的因素,并提出了优化平行流式冷凝器热力性能的措施,为平行流式冷凝器的优化设计提供了理论参考。     

智能积分伪微分算法在闭式泵控系统中的应用

为解决某闭式泵控系统速度控制超调量大且响应慢的问题,提出了基于智能积分伪微分控制的速度控制方法。首先,建立闭式泵控系统的数学模型;然后,分析了一般控制算法的不足,引出了智能积分伪微分控制算法;最后,实现了闭式泵控系统的速度控制仿真,构建了实验平台。实验结果与仿真结果一致,验证了所提方法的可行性。     

微机在热力站温度控制中的应用

本文介绍了PCS-1热力站可编程控制系统的组成、功能和两种温度控制的算法。该系统实现了对热力站的温度自动控制。     

Design of a fractional order PID controller using GBMO algorithm for load–frequency control with governor saturation consideration

Load–frequency control is one of the most important issues in power system operation. In this paper, a Fractional Order PID (FOPID) controller based on Gases Brownian Motion Optimization (GBMO) is used in order to mitigate frequency and exchanged power deviation in two-area power system with considering governor saturation limit. In a FOPID controller derivative and integrator parts have non-integer orders which should be determined by designer. FOPID controller has more flexibility than PID controller. The GBMO algorithm is a recently introduced search method that has suitable accuracy and convergence rate. Thus, this paper uses the advantages of FOPID controller as well as GBMO algorithm to solve load–frequency control. However, computational load will higher than conventional controllers due to more complexity of design procedure. Also, a GBMO based fuzzy controller is designed and analyzed in detail. The performance of the proposed controller in time domain and its robustness are verified according to comparison with other controllers like GBMO based fuzzy controller and PI controller that used for load–frequency control system in confronting with model parameters variations.     

基于神经网络的火电厂脱硫控制系统研究

以某火电厂 ２×３００MW 机组为研究对象,设计了以石灰石 石膏湿法为工艺基础的烟气脱硫控制系统.对脱硫控制系统中吸收塔的浆液pH值的控制进行了改进,设计了基于神经网络自适应控制器.该控制器能有效提高浆液pH值的控制精度与稳定性.     

Improvement in automatic generation control of two-area electric power systems via a new fuzzy aided optimal PIDN-FOI controller

Automatic generation control (AGC) executes a vital role to supply quality power in an interconnected power system. To cultivate good quality of power supply via preserving area frequency and tie-line power oscillations following consumer's load demand disturbances, the controller designed for AGC of power system should display excellent disturbance rejection expertise. Hence, in this paper, a maiden attempt is made to propose a fuzzy aided integer order proportional integral derivative with filter-fractional order integral (FPIDN-FOI) controller for AGC of multi-area power systems. A more recent intelligent optimization technique termed as imperialist competitive algorithm (ICA) is fruitfully employed for concurrent tuning of various parameters of the proposed controller. It is observed from the simulation results that the proposed FPIDN-FOI controller outperforms the various existing control strategies and PID/PIDN/FPIDN controller designed in the study for five different power system models. Effect of variation in fractional order value of integral on the system performance is analyzed. A sensitivity analysis is conducted to test the robustness of the designed controller under variations in the system parameters, load demands and existence of the system nonlinearities. It is perceived that the proposed controller is robust and executes adequately under variations in system parameters, random load disturbance patterns and nonlinearities.     

Design of a nuclear reactor controller using a model predictive control method

A model predictive controller is designed to control thermal power in a nuclear reactor. The basic concept of the model predictive control is to solve an optimization problem for finite future time steps at current time, to implement only the first optimal control input among the solved control inputs, and to repeat the procedure at each subsequent instant. A controller design model used for designing the model predictive controller is estimated every time step by applying a recursive parameter estimation algorithm. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), was used to verify the proposed controller for a nuclear reactor. It was known that the nuclear power controlled by the proposed controller well tracks the desired power level and the desired axial power distribution.     

基于模糊PID的半导体激光器工作温度控制

温度对LD（1aserdiode）发光功率的稳定性影响非常明显,而在LD的应用中需要其输出很稳定的光功率,所以对其工作温度的控制具有重要的现实意义。现采用模糊自整定PID（proportion integral derivative）控制器对半导体激光器LD的工作温度进行控制,并与无温度控制时的LD输出光功率进行比较。通过实验,该方法不但能很好地实现LD输出光功率的稳定,光功率稳定度为0．0304％,而且能使系统很快进入稳定状态。     

不完全微分型PID控制的神经元实现

给出从不完全微分型PID算法派生出的神经元PID控制器，并利用MATLAB／SIMULINK仿真软件对该控制器在某隧道式炉中的应用进行仿真研究。仿真结果表明．不完全微分PID控制的神经元实现不但具有不完全微分型PID控制的优点而且还具有神经元控制的自适应特点。     

Steam temperature controller with LS-SVR-based predictor and PID gain scheduler in thermal power plant

Nonlinearity and time delay in thermal power plant processes during the period of steady state load have been reported to be efficiently compensated for by controlling the open rate of sprays and an angle of burner tilt using a conventional cascade PID controller. However, it is not easy to compensate severe nonlinearity and time delays simultaneously due to feed water and coal flow variations during load changes. This paper introduces advanced method to mitigate these problems. A predictor based on the least square support vector machine for regression (LS-SVR) algorithm is developed to efficiently compensate the nonlinearity in the boiler system, and it enables accurate modeling of the steam temperature by applying LS-SVR algorithm by using one variable, steam temperature, for the superheater and reheater systems. Moreover, the predictor enables to compensate the time delay by generating a prior control action, based on the predicted steam temperature after a certain time interval. An LS-SVR-based predictor is combined with a PID controller that uses a gain scheduler based on an anti-reset windup algorithm to enable more sensitive and efficient steam temperature control during load changes to the boiler system in a thermal power plant. A load-changing simulation is conducted, and the proposed steam temperature controller demonstrates a more stable and efficient performance than a conventional cascade PID controller.     

A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics

In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern.     

基于模糊神经网络PID的复合控制策略

为了结合模糊控制容错力强和神经网络PID在线学习和调整的优点,提出了一种结合模糊控制与神经网络PID控制的复合控制方法,即分别设计模糊控制器和神经网络PID控制器后,再利用权重分配器对这两个控制器进行权重分配来控制被控对象。将该控制策略应用于某火电机组的二级过热器减温水流量系统控制,并在simulink仿真平台进行仿真,仿真实验结果表明:该复合控制策略较传统的模糊控制或神经网络PID控制的上升时间更短,调节时间和超调量更小,稳态性能更好。     

An improved approach for robust control of dynamic voltage restorer and power quality enhancement using grasshopper optimization algorithm

This paper presents a novel contribution of a low complexity control scheme for voltage control of a dynamic voltage restorer (DVR). The scheme proposed utilizes an error-driven proportional–integral–derivative (PID) controller to guarantee better power quality performance in terms of voltage enhancement and stabilization of the buses, energy efficient utilization, and harmonic distortion reduction in a distribution network. This method maintains the load voltage close to or equal to the nominal value in terms of various voltage disturbances such as balanced and unbalanced sag/swell, voltage imbalance, notching, different fault conditions as well as power system harmonic distortion. A grasshopper optimization algorithm (GOA) is used to tune the gain values of the PID controller. In order to validate the effectiveness of the proposed DVR controller, first, a fractional order PID controller was presented and compared with the proposed one. Further, a comparative performance evaluation of four optimization techniques, namely Cuckoo search (CSA), GOA, Flower pollination (FBA), and Grey wolf optimizer (GWO), is presented to compare between the PID and FOPID performance in terms of fault conditions in order to achieve a global minimum error and fast dynamic response of the proposed controller. Second, a comparative analysis of simulation results obtained using the proposed controller and those obtained using an active disturbance rejection controller (ADRC) is presented, and it was found that the performance of the optimal PID is better than the performance of the conventional ADRC. Finally, the effectiveness of the presented DVR with the controller proposed has been assessed by time-domain simulations in the MATLAB/Simulink platform.