Slow and fast dynamics of a natural gas hydrogen reformer

It has been known for some time that fuel cells operate in multiple time scales due to phenomena of different nature that govern their dynamics (electrical, chemical, mechanical, electrochemical, thermodynamic). It is expected that multi-time scales will be presented in the hydrogen gas reformer (produces hydrogen from hydrogen rich fuels) due to its complex chemical and physical nature. In this paper, we show how to present a linearized hydrogen gas reformer dynamic model in the coordinates in which slow and fast variables are explicitly defined and exactly separated. This result is important in its own right to get a better understanding of slow and fast dynamics of particular variables, study their interactions, and as well for designing reduced-order controllers and estimators for the hydrogen gas reformer that will independently operate in different time scales.     

Order reduction via balancing and suboptimal control of a fuel cell – Reformer system

In this paper we first perform system balancing of an eighth-order mathematical model of a polymer electrolyte membrane fuel cell (PEMFC) dynamic coupled with a tenth-order mathematical model of a hydrogen gas reformer. Based on that information we determine reduced-order mathematical models of the original eighteen-order model by eliminating state variables that have negligible contribution to the model dynamics. Having obtained the reduced-order models, we study their step and impulse responses, and compare them to those of the original full-order model. In addition, we design corresponding suboptimal feedback controllers based on the reduced-order models. Comparing the obtained suboptimal controllers (that require a reduced number (only six or even five) of feedback loops making them easy for implementation) we find that their suboptimal performances are very close to the optimal performance of the full-state optimal feedback controller. It is important to emphasize that the full-order state feedback controller requires the same number of the feedback loops as the dimension of the original full-order state space model (in this case eighteen), which makes it complex and sometimes impractical to implement.     

Identification in closed‐loop operation of models for collective pitch robust controller design

To achieve load reduction and power optimization, wind turbine controllers design requires the availability of reliable control‐oriented linear models. These are needed for model‐based controller design. Model identification of wind turbine while operating in closed loop is an appropriate solution that has recently shown its capabilities when linear time‐invariant controllers and complicated control structures are present. However, the collective pitch control loop, one of the most important wind turbine loops, uses non‐linear controllers. Typically, this non‐linear controller is a combination of a linear controller and a gain scheduling. This paper presents a new algorithm for identification in closed‐loop operation that allows the use of this kind of non‐linear controllers. The algorithm is applied for identification the collective pitch demand to generator speed of a wind turbine at various operating points. The obtained models are presented and discussed from a control point of view. The validity of these models is illustrated by their use for the design of a linear fix robust controller. The performance based on simulation data of this linear controller is similar to that obtained with simulations based on a linear controller with gain scheduling, but its design and implementation is much simpler. Copyright © 2012 John Wiley & Sons, Ltd.     

Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation

In this paper, a novel system analysis and controller design method for the air supply of proton exchange membrane (PEM) fuel cell systems is proposed. Firstly, a class of nonlinear systems with specific structures are introduced. In further analysis, the introduced system can be divided into two parts: one is fast and include disturbances and uncertainty, and the other is relatively slow. We change the introduced system into an equivalent cascade system. Some state variables of the first subsystem are acted as the inputs of the second subsystem. Furthermore, the similarities between the air supply system and the equivalent cascade system are proved, and a cascade controller is proposed based on uncertainty and disturbance estimation (UDE) and Lyapunov method. Moreover, we implement the algorithm in the air supply system for PEM fuel cells. Experimental results show the effectiveness of the proposed method.     

Suboptimal level controller for steam generators in pressurizedwater reactors

The authors consider the design of a suboptimal water-level controller for steam generators in large pressurized water reactors using linear output feedback control. A methodology for feasibility analysis and linear output feedback control design is developed through eigenvalue dynamics. The proposed controller is a linear, constant, partial state feedback law. The controlled system has the following desirable features: (a) the controller is independent of disturbance, (b) the water level returns to its prespecified level value following a step disturbance, (c) the controlled system is asymptotically stable, and (d) transient response is similar to the transient response of an optimal complete state feedback controller. An example illustrates the applicability and the effectiveness of the proposed techniques     

Design of linear controllers applied to an ethanol steam reformer for PEM fuel cell applications

This paper focuses on the design of a controller for a low temperature ethanol steam reformer for the production of hydrogen to feed a protonic exchange membrane (PEM) fuel cell. It describes different control structures for the reformer and treats the control structure selection of this multiple input multiple output (MIMO) system. For each considered control structure, decentralised 2 × 2 controllers with proportional integral (PI) control actions in each control loop are implemented. The tuning of the PI parameters and the performance evaluation of the different controllers are based on a non-linear simulation model. For the validation and comparison of the considered controllers, the dynamic response for different setpoint changes and initial conditions is analysed, as well as the behaviour of the controlled system against disturbances.     

Load control of a wind-hydrogen stand-alone power system

A new generation of load controllers enable stand-alone power systems (SAPS) to use one or many standard (grid connected) wind turbines. The controllers use fuzzy logic software algorithms. The strategy is to use the control loads to balance the flow of active power in the system and hence control system frequency. The dynamic supply of reactive power by a synchronous compensator maintains the system voltage within the limits specified in EN50160. The resistive controller loads produce a certain amount of heat that is exchanged down to the end user (hot water). It was decided to investigate the implementation of a hydrogen subsystem into the SAPS that can work in parallel with the Distributed Intelligent Load Controller (DILC). The hydrogen subsystem can then function as energy storage on long-term basis and an active load controller on short-term basis.     

Fuzzy Predictive Supervisory Control Based on Genetic Algorithms for Gas Turbines of Combined Cycle Power Plants

This work presents a novel design and development of a fuzzy predictive supervisory controller, based on genetic algorithms (GA), for gas turbines of combined cycle units. The control design is based on an objective function that represents the economic and regulatory performance of a gas turbine by using a dynamic optimal set-point for the regulatory level. A fuzzy model is considered in order to characterize the nonlinear behavior of the gas turbine, which is used in two supervisory control systems. The first fuzzy supervisory control design includes a fuzzy model, where its parameters are held constant for the successive predictions. For the second fuzzy supervisory control design, its parameters are updated in each prediction and its nonlinear optimization problem is solved using GAs. The proposed fuzzy supervisory controllers are compared against a supervisory controller based on linear models and a regulatory controller with constant optimal set-points. Results indicate that the fuzzy GA predictive supervisory controller captures adequately the nonlinearities of the process, which, in turn, provides a promising approach to improve the performance of the combined cycle unit.     

Design of the PID temperature controller for an alkaline electrolysis system with time delays

Electrolysis systems use proportional–integral–derivative (PID) temperature controllers to maintain stack temperatures around set points. However, because of heat transfer delays in electrolysis systems, the manual tuning of PID temperature controllers is time-consuming, and temperature oscillations often occur. This paper focuses on the design of the PID temperature controller for an alkaline electrolysis system to achieve fast and stable temperature control. A thermal dynamic model of an electrolysis system is established in the frequency domain for controller designs. Based on this model, the temperature stability is analysed by the root distribution, and the PID parameters are optimized considering the temperature overshoot and the settling time. The performance of the optimal PID controllers is experimentally verified. Furthermore, the simulation results show that the before-stack temperature should be used as the feedback variable for small lab-scale systems to suppress stack temperature fluctuations, and the after-stack temperature should be used for larger systems to improve the economy. This study helps ensure the temperature stability and control of electrolysis systems.     

A robust hybrid current control for permanent-magnet synchronous motor drive

Recently, the permanent-magnet synchronous motor (PMSM) has found widespread utilization in modern adjustable AC drives. This is achieved by using current-controlled voltage source inverter (VSI) systems. Because of its ease of implementation, fast current control response and inherent peak current-limiting capability, hysteresis current control is considered as the simplest technique used to control the motor currents for an AC machine. On the other hand, the ramp comparator controller has some advantages, such as limiting maximum inverter switching frequency to the carrier triangular waveform frequency and producing well-defined harmonics. In order to take advantage of the position features of both these two controllers, this paper presents the design and software implementation of a hybrid current controller. The proposed intelligent controller is a simultaneous combination and contribution of the hysteresis current controller and the ramp comparator. Comparisons using simulations on a 0.9-kW PMSM confirm that the proposed hybrid current controller gives better performance and has the advantage of conceptual simplicity. In particular, harmonic spectra of the stator current, obtained using a fast Fourier transform (FFT), are used for comparison purposes.     

Resonance characteristics of distributed solar collector fields

In practice the outlet temperature of a distributed collector field is usually regulated by a feedforward controller combined with a simple PI based feedback loop. Such systems give oscillatory performance, even though the controller design is aimed to give aperiodic responses. Through the use of a nonlinear computer model of a distributed collector field, the performance of simple PI based controllers on such systems is analyzed and investigated. Using experimental results obtained from both the computer model and the plant in question, the dynamics of the collector field are found to contain resonance characteristics. It is demonstrated that the main reason for the oscillatory performance of PI based control schemes are these characteristics and not, as previously thought, the variability of system dynamics. Furthermore, it is shown that these simple controllers are wholly inadequate for the purpose of achieving fast well-damped responses on this system.     

Modeling and control of air stream and hydrogen flow with recirculation in a PEM fuel cell system—II. Linear and adaptive nonlinear control

In this part of the paper, linear and nonlinear multivariable controllers are designed for the air stream and hydrogen flow with recirculation in a proton exchange membrane (PEM) fuel cell system. The focus of the model is to obtain the desired transient performance of air stoichiometric ratio, cathode inlet pressure, and pressure difference between the anode and the cathode. Based on linearization of the nonlinear dynamic model in the first part of this paper, the coupling between control inputs and performance is analyzed first. The phase relationship between the stack voltage and water transport in frequency domain is meaningful to the future humidity estimation and active purge operation. Then, linear quadratic Gaussian (LQG) algorithm based on observer feedback is used for set-point tracking, and a model-predictive controller (MPC) with an on-line neural network identifier is also designed to improve robustness. Compared with decentralized PI controllers, the multivariable controllers improve the transient response and shows better disturbance rejection capability.     

Output-feedback voltage tracking control for input-constrained PEM fuel cell systems

An output-feedback voltage control system for nonlinear PEM fuel cells is presented. For voltage tracking around equilibrium operating points, the controller design minimizes the energy ratio between tracking error and normalized command while hydrogen and oxygen flowrates satisfy specified magnitude constraints and closed-loop poles meet desired placement constraints. Time response simulations based on Ballard 5 kW PEM fuel cell system parameters verify the design. Simulated controllers constructed numerically via the linear matrix inequality algorithm elaborate relationships between designed input flowrate and voltage tracking error. With controller design based on the same nominal input flowrate constraints, the achieved voltage tracking capability is comparable to our published state-feedback design study. To reduce voltage tracking error under fixed external resistance, gas flowrate magnitude constraints must be relaxed, requiring more fuel energy to manipulate the system variables for operation away from equilibrium conditions. Whereas state-feedback designs depend on internal state variables which are not always measurable, output-feedback control using only voltage tracking error as measurement simplifies practical implementation.     

Simultaneous frequency and voltage control of wind-diesel power systems using energy storage

This paper presents a new scheme for smoothing out the voltage and frequency fluctuations simultaneously in a hybrid wind-diesel system using a super conducting magnetic energy storage (SMES) unit. The SMES unit located at induction generators' terminal bus, uses local measurements for exchanging real and reactive powers simultaneously in four quadrants. Complete model of the hybrid wind-diesel-SMES system is developed and is used for eigenvalue analysis and design of controllers. Computer simulation results illustrate the positive impact of the SMES unit on the quality of the supply and furthermore some modifications of the controller design are proposed. © 1998 John Wiley & Sons, Ltd.     

Temperature and hydrogen flow rate controls of diesel autothermal reformer for 3.6 kW PEM fuel cell system with autoignition delay time analysis

In this paper catalyst temperature and hydrogen flow rate controls are an area of interest for autothermal reforming (ATR) of diesel fuel to provide continuous and necessary hydrogen flow to the on-board fuel cell vehicle system. ATR control system design is important to ensure proper and stable performance of fuel processor and fuel cell stack. Fast system response is required for varying load changes in the on-board fuel cell system. To cope with control objectives, a combination of PI and PID controllers are proposed to keep the controlled variables on their setpoints. ATR catalyst temperature is controlled with feedback PID controller through variable OCR (oxygen to carbon ratio) manipulation and kept to the setpoint value of 900 °C. Additionally diesel auto-ignition delay time is implemented through fuel flow rate delay to avoid complete oxidation of fuel. Hydrogen flow rate to the fuel cell stack is kept to setpoint of required hydrogen flow rate according to fuel cell load current using PI controller. An integrated dynamic model of fuel processor and fuel cell stack is also developed to check the fuel cell voltage. Product gas composition of 35, 18 and 4% is achieved for hydrogen, nitrogen, and carbon dioxide, respectively. The results show fast response capabilities of fuel processor following the fuel cell load change and successfully fulfills the control objectives.     

Classical state feedback controller for nonlinear systems using mean value theorem: closed loop-FOC of PMSM motor application

The problem of state feedback controllers for a class of Takagi-Sugeno (T-S) Lipschitz nonlinear systems is investigated. A simple systematic and useful synthesis method is proposed based on the use of the differential mean value theorem (DMVT) and convex theory. The proposed design approach is based on the mean value theorem (MVT) to express the nonlinear error dynamics as a convex combination of known matrices with time varying coefficients as linear parameter varying (LPV) systems. Using the Lyapunov theory, stability conditions are obtained and expressed in terms of linear matrix inequalities (LMIs). The controller gains are then obtained by solving linear matrix inequalities. The effectiveness of the proposed approach for closed loop-field oriented control (CL-FOC) of permanent magnet synchronous machine (PMSM) drives is demonstrated through an illustrative simulation for the proof of these approaches. Furthermore, an extension for controller design with parameter uncertainties and perturbation performance is discussed.     

Development of solid oxide fuel cell and battery hybrid power generation system

Solid oxide fuel cell hybrid generation system is the best scheme for the load tracking of off-grid monitoring stations. But there are still potential problems that need to be addressed: preventing fuel starvation and ensuring thermal safety while meeting load tracking in hybrid power generation system. In order to solve these problems, a feasible hybrid power generation system structure scheme is proposed which combined SOFC subsystem and Li-ion battery subsystem. Then a model of the hybrid power generation system is built based on the proposed system structure. On this basis, an adaptive controller, include the adaptive energy management algorithm and current feedforward gas supply strategy, is applied to manage the power-sharing in this hybrid system as well as keep the system operating within the safety constraints. The constraints, including maintaining the bus voltage at the desired level, keeping SOFC operating temperature in safety, and mitigating fuel starvation are explicitly considered. The stability of the proposed energy management algorithm is analyzed. Finally, the developed control algorithm is applied to the hybrid power generation system model, the operation result proves the feasibility of the designed controller strategy for hybrid generation system and effectively prevent fuel starvation and ensure thermal safety.     

The design of turbine-generator optimal controllers including theeffect of torsional modes of oscillation

Optimal linear control has been suggested for designing supplementary signal controllers for turbine-generators. It is shown that the design of the controller should include consideration of the torsional modes of oscillation of the rotor to obtain the best performance. The exciter voltage ceiling is shown to limit the sum of the synchronizing and damping torques. Practical designs normally require that tradeoffs be made. It is shown how advantage would be gained by using the supplementary signal. Normally fed to the speed governor controlling the main steam valve, for a second governor that would merely act on a fast interceptor valve     

Development of hybrid photovoltaic-fuel cell system for stand-alone application

In this paper we present firstly the different hybrid systems with fuel cell. Then, the study is given with a hybrid fuel cell–photovoltaic generator. The role of this system is the production of electricity without interruption in remote areas. It consists generally of a photovoltaic generator (PV), an alkaline water electrolyzer, a storage gas tank, a proton exchange membrane fuel cell (PEMFC), and power conditioning units (PCU) to manage the system operation of the hybrid system. Different topologies are competing for an optimal design of the hybrid photovoltaic–electrolyzer–fuel cell system. The studied system is proposed. PV subsystem work as a primary source, converting solar irradiation into electricity that is given to a DC bus. The second working subsystem is the electrolyzer which produces hydrogen and oxygen from water as a result of an electrochemical process. When there is an excess of solar generation available, the electrolyzer is turned on to begin producing hydrogen which is sent to a storage tank. The produced hydrogen is used by the third working subsystem (the fuel cell stack) which produces electrical energy to supply the DC bus. The modelisation of the global system is given and the obtained results are presented and discussed.     

Fuzzy neural control of a hybrid fuel cell/battery distributed power generation system

An innovative control strategy is proposed of hybrid distributed generation (HDG) systems, including solid oxide fuel cell (SOFC) as the main energy source and battery energy storage as the auxiliary power source. The overall configuration of the HDG system is given, and dynamic models for the SOFC power plant, battery bank and its power electronic interfacing are briefly described, and controller design methodologies for the power conditioning units and fuel cell to control the power flow from the hybrid power plant to the utility grid are presented. To distribute the power between power sources, the fuzzy switching controller has been developed. Then, a Lyapunov based-neuro fuzzy algorithm is presented for designing the controllers of fuel cell power plant, DC/DC and DC/AC converters; to regulate the input fuel flow and meet a desirable output power demand. Simulation results are given to show the overall system performance including load-following and power management of the system.