Multivariable robust PID control for a PEMFC system

This paper proposes robust proportional-integral-derivative (PID) control for a proton exchange membrane fuel cell (PEMFC) system. We model a PEMFC as a multivariable system, and apply identification techniques to obtain the system’s transfer function matrices, where system variations and disturbances are regarded as uncertainties. Because robust control can cope with system uncertainties and disturbances, it has been successfully applied to improve the stability, performance, and efficiency of PEMFC systems in previous studies. However, the resulting robust controllers might be too complicated for hardware implementation. On the other hand, PID control has been widely applicable to engineering practices because of its simple structure, but it lacks stability analysis for systems with uncertainties. Therefore, by combining the merits of robust control and PID control, we design robust PID controllers for the PEMFC system. Based on evaluation of stability, performance, and efficiencies, the proposed robust PID controllers are shown to be effective.     

Multivariable robust control of a proton exchange membrane fuel cell system

This paper applies multivariable robust control strategies to a proton exchange membrane fuel cell (PEMFC) system. From the system point of view, a PEMFC can be modeled as a two-input-two-output system, where the inputs are air and hydrogen flow rates and the outputs are cell voltage and current. By fixing the output resistance, we aimed to control the cell voltage output by regulating the air and hydrogen flow rates. Due to the nonlinear characteristics of this system, multivariable robust controllers were designed to provide robust performance and to reduce the hydrogen consumption of this system. The study was carried out in three parts. Firstly, the PEMFC system was modeled as multivariable transfer function matrices using identification techniques, with the un-modeled dynamics treated as system uncertainties and disturbances. Secondly, robust control algorithms were utilized to design multivariable H_∞ controllers to deal with system uncertainty and performance requirements. Finally, the designed robust controllers were implemented to control the air and hydrogen flow rates. From the experimental results, multivariable robust control is shown to provide steady output responses and significantly reduce hydrogen consumption.     

Study of a deaerator location in triple-pressure reheat combined power cycle

Deaerator is an essential open feed water heater in the steam bottoming cycle to improve the efficiency and also to remove the dissolved gasses from the feed water. Heat recovery steam generator (HRSG) plays a key role on the performance of the combined cycle (CC). In this work, attention has been focused to improve the performance of a triple pressure (TP) CC with a deaerator location. In this work, two options for deaerator location, one at condenser (deaerator–condenser) and the other in between low pressure (LP) and intermediate pressure (IP) heaters have been studied to increase the heat recovery from the gas turbine exhaust. The compressor pressure ratio is not fixed initially and evaluated from HRSG inlet condition. The LP and IP in HRSG have been evaluated from the local flue gas temperature to get the minimum possible temperature difference in the heaters. The results show that the deaerator placed in between the LP and IP heaters, gives high efficiency compared to a deaerator–condenser arrangement. The optimum conditions for the HRSG, deaerator and steam reheater are evaluated through the thermodynamic study. The results are validated by comparing with the published results.     

Adaptive control of a fuel cell-microturbine hybrid power plant

The composition of natural gas may vary significantly, and load power varies randomly. Traditional control design approaches consider a fixed operating point in the hope that the resulting controller is robust enough to stabilize the system for different operating conditions. On the other hand, adaptive control incorporates the time-varying dynamical properties of the model and considers the disturbances acting at the fuel cell-microturbine hybrid power plant. It may be possible to identify the parameters of the adaptive controller. This scheme is called direct adaptive control, because we are going to obtain directly the required controller parameters through their estimation in an appropriately redefined plant model. An adaptive minimum variance controller is developed in this paper.     

Multivariable adaptive control for a thermal generator

A digital control system using the optimal control has been developed for a thermal power generator. In order to increase the generator control performance for improving the power system stability, this system supplies the excitation system directly with control signals and provides the governor system with control signals and supplemental control signals for a conventional governor. The system utilizes adaptive control for changes in generator nonlinear characteristics, as well as in power system characteristics. The principles and application of this system are described and results of simulation tests using a 1000 MVA thermal power plant model on a high-reliability AC/DC electric power system simulator are presented. The results verify the performance of this system, as well as the applicability of the system to actual plants     

Robust control and analysis of a wind-diesel hybrid power plant

The aim of this paper is twofold: first to present multivariable frequency domain techniques as a tool for controller design and dynamic analysis of an autonomous wind-diesel power system; and secondly to study how robust model based controllers can be designed for such systems. Dynamic system analyses using multivariable frequency domain techniques are verified against detailed nonlinear simulation studies. The results are encouraging in the sense that the main conclusions in terms of robust stability and performance agree very well with the simulation results. It is also shown that improved performance of the system can be achieved using simple model based controllers     

Multivariable generalized predictive control of a boiler system

An application of a multiloop generalized predictive control (GPC) scheme to achieve self-tuning control of superheat pressure and steam temperatures in a 200 MW power station drum boiler are presented. Controllers have been designed and evaluated using a detailed nonlinear boiler model which is well established and validated. Results illustrating the performance of the plant with GPC are presented and compared with conventional PI control. The results show that substantial improvements in control can be achieved with the GPC. Steam pressure and temperature variations are greatly reduced, without offsets, and with less controller activity     

大型光伏电站电压故障鲁棒在线诊断模型

当具有一定规模的光伏电站接入区域电网的某一节点后,由于电网和光伏电站运行特性的不确定性,导致电网与光伏电站间产生复杂的相互影响,对并网点电压故障的诊断造成困难。针对该问题,文章提出了基于光伏电站并网点两侧等值阻抗模对比的并网点电压故障在线诊断模型。在考虑光伏电站侧和电网侧等值阻抗模测量不确定性的前提下,基于阻抗模模型建立了并网点电压故障鲁棒M估计在线判别模型;在阻抗模测量尺度的鲁棒标准化基础上,建立了电网侧与电站侧阻抗模差值的鲁棒M估计模型。根据两侧阻抗模的实时测量值,给出了阻抗模测量时刻的最优阻抗模差值判据,并以此为光伏电站并网点电压故障诊断判据。文章建立10机39节点仿真模型并进行仿真计算,仿真结果验证了所提出的基于阻抗模的并网点电压故障鲁棒在线诊断模型的有效性。     

垃圾焚烧发电厂中各种二次污染的控制

概述了垃圾焚烧发电厂的各种二次污染：烟气、灰渣、恶臭、工艺废水及噪声，对与此相关的控制问题进行了分析和讨论，提出了控制二次污染的多种措施。     

Improved load control for a steam cycle combined heat and power plant

The problem of optimum load control of steam power plants has been dealt within many technical papers during the last decades. Deregulation of the power markets and close to the (bio-) fuel source thinking has lead to a trend of small scale combined heat and power plants. These plants are usually operated according to the heat demand and therefore they spend a significant time on partial load. The load control of such plants is in general done by partial arc control. This work applies a hybrid control strategy, which is a combination of partial arc control and sliding pressure control. The method achieves further improvement in performance at partial load. Hybrid control itself is not novel and has earlier been used on traditional coal-fired condensing plants. This has, to the author's knowledge, not earlier been applied on combined heat and power plants. The results show that there is a potential for improved electricity production at a significant part of the load range.     

天然气联合循环电厂的噪声控制

天然气联合循环电厂环保节能,大多安装在经济发达、人口稠密的大、中城市附近,但厂界噪声和周围声环境(主要是居民敏感点)的达标却成了极其突出的问题.本文介绍了厂界噪声和周围声环境的国家标准,以及用户如何对设备制造厂提出设备的噪声限值要求.并以浙江半山天然气联合循环发电工程为例,介绍了在联合循环发电工程建设中对主要噪声源的分析和治理措施,以及工程竣工验收后取得的噪声治理效果.     

Modeling, Simulation, control, and optimization of a geothermal power plant

The main results of the simulation study of a double-flash geothermal plant, including a steam-CO/sub 2/ reboiler-based separation process, are presented. Dynamic models of two-phase, H/sub 2/O-CO/sub 2/ components are derived, and their use for dynamic simulation and operating point optimization is discussed. Control system issues are then considered. On one hand, the simulator is used as an aid to design and test standard level and pressure control loops, whose actual performance would otherwise be difficult to predict due to the high degree of interconnection of the plant components. On the other hand, the control concept for the innovative part of the plant is discussed, recognizing that the control problem and the operating point optimization problems have to be tackled simultaneously. A simple, yet effective, solution for this problem is proposed.     

Application of multi-model control with fuzzy switching to a micro hydro-electrical power plant

Modelling hydraulic turbine generating systems is not an easy task because they are non-linear and uncertain where the operating points are time varying. One way to overcome this problem is to use Takagi–Sugeno (TS) models, which offer the possibility to apply some tools from linear control theory, whereas those models are composed of linear models connected by a fuzzy activation function. This paper presents an approach to model and control a micro hydro power plant considered as a non-linear system using TS fuzzy systems. A TS fuzzy system with local models is used to obtain a global model of the studied plant. Then, to combine efficiency and simplicity of design, PI controllers are synthesised for each considered operating point to be used as conclusion of an electrical load TS Fuzzy controller. The latter ensures the global stability and desired performance despite the change of operating point. The proposed approach (model and controller) is tested on a laboratory prototype, where the obtained results show their efficiency and their capability to ensure good performance despite the non-linear nature of the plant.     

A linear quadratic regulator control of a stand-alone PEM fuel cell power plant

This paper introduces a technique based on linear quadratic regulator (LQR) to control the output voltage at the load point versus load variation from a standalone proton exchange membrane (PEM) fuel cell power plant (FCPP) for a group housing use. The controller modifies the optimal gains k _i by minimizing a cost function, and the phase angle of the AC output voltage to control the active and reactive power output from an FCPP to match the terminal load. The control actions are based on feedback signals from the terminal load, output voltage and fuel cell feedback current. The topology chosen for the simulation consists of a 45 kW proton exchange membrane fuel cell (PEMFC), boost type DC/DC converter, a three-phase DC/AC inverter followed by an LC filter. Simulation results show that the proposed control strategy operated at low commutation frequency (2 kHz) offers good performances versus load variations with low total harmonic distortions (THD), which is very useful for high power applications.     

GA-based fuzzy logic control of a solar power plant using distributed collector fields

A novel genetic algorithm (GA) based fuzzy logic control (FLC) system has been developed for the solar power plant, Plataforma Solar de Almería (PSA) at Tabernas, in Almería, Spain. The rule base encompasses an empirical set of 49 “if-then” rules. Chromosomes consisting of 49 genes of 5-bit data are created to link to the rule base. The 5-bit data of each gene represents the stength of the corresponding ‘If-Then’ rule. The GA performs the basic operations of reproduction, crossover and mutation on a pool of chromosomes to search for the best rule base which optimises the response time of the plant to input temperature or power demand by controlling the distributed collector field of the plant. The collect field is essentially an array of parabolic mirrors and oil pipes in which the transversal of solar energy takes place. Simulation results on the plant with an optimised rule-base using the 100th generation of the chromosome show that the proposed GA-FLC scheme gives a better and more robust performance of the plant than other schemes previously implemented.     

The effects of the control system on the thermoeconomic diagnosis of a power plant

Thermoeconomic methodologies represent a powerful tool for the energy system diagnosis when detecting possible malfunctions, localizing them and expressing their effects on the components in terms of thermodynamic and economic quantities. In this article, the role played by the control system in the propagation of malfunctions is analyzed. Its effects are proven to be relevant when the thermoeconomic diagnosis is performed and quantified for a gas turbine based cogeneration plant.     

Nonlinear predictive control with dead-time compensator: Application to a solar power plant

This paper presents the application of a Nonlinear Model Predictive Controller (NMPC) extended with a dead-time compensator (DTC) to the control of a distributed solar collector field. This nonlinear controller uses the Nonlinear Extended Prediction Self-Adaptive Controller (NEPSAC) algorithm. A nonlinear grey-box model of the plant, based on first principles and tuned according to real measurements, is used in the simulation tests. The resulting controller is compared to other architectures based on DTC, showing very good performance for reference tracking and for disturbance rejection.     

Multivariable self-tuning power system stabilizer simulation andimplementation studies

A multi-input multi-output (MIMO) adaptive power system stabilizer which damps dynamic oscillations is presented. The single-input single-output (SISO) pole-shifting adaptive control algorithm is used as the basis. Its extension to the MIMO controller combines and coordinates the stabilizing contributions from both the excitation and governor systems. The advantage of the adaptive feature is that it can track the operating conditions and system structure changes. The proposed stabilizer can be used with hydro and turbogenerators. Computer simulation results show that the adaptive stabilizer improves the damping of power system oscillations     

燃煤机组烟羽治理技术研究

近年来,随着环保的要求越来越严格,各地方环保逐渐要求燃煤电厂消除烟囱"白色烟羽"现象。通过分析"白色烟羽"现象形成的原因,介绍了目前主要的治理技术;并介绍分析某350 MW机组改造实例,采用间接冷凝式的烟羽治理技术使机组经改造后排放达到环保要求,此治理方案可为其他电厂治理烟羽问题提供借鉴。     

锅炉燃烧优化控制系统在火电厂的应用

针对某电厂330 MW机组锅炉上实施燃烧优化闭环控制系统项目,总结燃烧优化项目成功实施的几个重要步骤及实施中应该注意的问题,为此类项目在国内实施提供经验借鉴。