Robust control for fuel cell–microturbine hybrid power plant using biomass

A system showing great promise is the integration of gasification with a fuel cell. The emerging high-temperature fuel cells produce very high-temperature exhaust gases that can either be used directly in a combined-cycle or to drive a gas turbine. A high-temperature fuel cell–microturbine combination has the potential to achieve up to 60% efficiency and near-zero emissions. Fuel flexibility enables the use of low-cost indigenous fuels, renewables, and waste materials. The characteristics of gas from biomass gasification may vary significantly. 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, robust control incorporates the uncertain parameters of the model.     

质子交换膜燃料电池的自适应模糊恒功率控制

质子交换膜燃料电池作为一种高效的绿色环保电源而受到越来越多关注。维持燃料电池的正确运行需要良好的控制系统。文章在建立质子交换膜燃料电池数学模型和仿真平台的基础上,针对恒功率燃料电池设计了自适应模糊控制器。仿真结果表明,该自适应模糊控制器可以控制质子交换膜燃料电池实现恒功率输     

Model-based power control strategy development of a fuel cell hybrid vehicle

An integrated procedure for math modeling and power control strategy design for a fuel cell hybrid vehicle (FCHV) is presented in this paper. Dynamic math model of the powertrain is constructed firstly, which includes four modules: fuel cell engine, DC/DC inverter, motor-driver, and power battery. Based on the mathematic model, a power control principle is designed, which uses full-states closed-loop feedback algorithm. To implement full-states feedback, a Luenberger state observer is designed to estimate open circuit voltage (OCV) of the battery, which make the control principle not sensitive to the battery SOC (state of charge) estimated error. Full-states feedback controller is then designed through analyzing step responding of the powertrain and test data. At last of the paper, the results of simulation and field test are illustrated. The results show that the power control strategy designed takes into account the performance and economy characteristics of components of the FCHV powertrain and achieves the control object excellently.     

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     

Adaptive maximum power point tracking control of fuel cell power plants

A fuel cell's output power depends nonlinearly on the applied current or voltage, and there exists a unique maximum power point (MPP). This paper reports a first attempt to trace MPPs by an extremum seeking controller. The locus of MPPs varies nonlinearly with the unpredictable variations in the fuel cell's operation conditions. Thus, a maximum power point tracking (MPPT) controller is needed to continuously deliver the highest possible power to the load when variations in operation conditions occur. A two-loop cascade controller with an intermediate converter is designed to operate fuel cell power plants at their MPPs. The outer loop uses an adaptive extremum seeking algorithm to estimate the real-time MPP, and then gives the estimated value to the inner loop as the set-point, at which the inner loop forces the fuel cell to operate. The proposed MPPT control system provides a simple and robust control law that can keep the fuel cell working at MPPs in real time. Simulation shows that this control approach can yield satisfactory results in terms of robustness toward variations in fuel cell operation conditions.     

Energy control of supercapacitor/fuel cell hybrid power source

This paper deals with a flatness based control principle in a hybrid system utilizing a fuel cell as a main power source and a supercapacitor as an auxiliary power source. The control strategy is based on regulation of the dc bus capacitor energy and, consequently, voltage regulation. The proposed control algorithm does not use a commutation algorithm when the operating mode changes with the load power variation and, thus, avoids chattering effects. Using the flatness based control method, the fuel cell dynamic and its delivered power is perfectly controlled, and the fuel cell can operate in a safe condition. In the hybrid system, the supercapacitor functions during transient energy delivery or during energy recovery situations. To validate the proposed method, the control algorithms are executed in dSPACE hardware, while analogical current loops regulators are employed in the experimental environment. The experimental results prove the validity of the proposed approach.     

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.     

Optimal control in the power management of fuel cell hybrid vehicles

Several types of power management strategies have been developed to improve the fuel economy of fuel cell hybrid vehicles (FCHVs). Optimal control based on the Minimum Principle provides the necessary optimality conditions which minimize fuel consumption and optimize the power distribution between power sources while the vehicle is being driven. In the optimal control scheme, the costate is an equivalent parameter between fuel usage and electric usage. The optimal trajectory of the costate can be derived from one of the necessary conditions. In this paper, an optimal control scheme based on the Minimum Principle is proposed for cases without a state constraint and for those with a state constraint. The conditions in which a variable costate can be replaced with a constant costate are presented. The simulation results with constant costates are compared to those with variable costates in order to prove that variable costates can be replaced with constant costates when using the proposed optimal control scheme.     

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.     

Exergy analysis of a cryogenic hydrogen fuel power plant

An advanced cycle for the thermodynamic conversion of energy, which is particularly relevant in applications involving the use of cryogenic fuels and oxidants, is analysed by an exergy balance approach. This allows a check on which components are responsible for the largest irreversibilities and opens the way to further plant optimisation.     

Model-based optimal control of a hybrid power generation system consisting of photovoltaic arrays and fuel cells

Hybrid renewable energy systems are expected to become competitive to conventional power generation systems in the near future and, thus, optimization of their operation is of particular interest. In this work, a hybrid power generation system is studied consisting of the following main components: photovoltaic array (PV), electrolyser, metal hydride tanks, and proton exchange membrane fuel cells (PEMFC). The key advantage of the hybrid system compared to stand-alone photovoltaic systems is that it can store efficiently solar energy by transforming it to hydrogen, which is the fuel supplied to the fuel cell. However, decision making regarding the operation of this system is a rather complicated task. A complete framework is proposed for managing such systems that is based on a rolling time horizon philosophy.     

Adaptive energy management for fuel cell hybrid power system with power slope constraint and variable horizon speed prediction

An adaptive energy management strategy (EMS) is proposed to improve the economy and reliability of the fuel cell vehicle. Firstly, a variable horizon speed prediction method based on the principal component analysis and the K-means clustering is constructed. Then, an adaptive equivalent consumption minimization strategy (AECMS) with power slope constraints was designed to minimize the hydrogen consumption while ensuring reliability. Finally, a proportional-integral controller is used to track the air flow and pressure of the fuel cell engine (FCE) under energy distribution. Simulation results under West Virginia University Suburban (WVUSUB) show that the proposed strategy can improve the speed prediction accuracy by 2.80% and 25.57%, and reduce the hydrogen consumption by 2.79% and 2.66%, respectively, compared with the fixed 12 s and 15 s horizon. Moreover, the control error of oxygen excess ratio and the cathode pressure under energy distribution are 0.0102 (0.51%) and 189.4 Pa (0.0935%), respectively, indicating better reliability than the strategy without constraint.     

Power decoupling control of a solid oxide fuel cell and micro gas turbine hybrid power system

Solid Oxide Fuel Cell (SOFC) integrated into Micro Gas Turbine (MGT) is a multivariable nonlinear and strong coupling system. To enable the SOFC and MGT hybrid power system to follow the load profile accurately, this paper proposes a self-tuning PID decoupling controller based on a modified output-input feedback (OIF) Elman neural network model to track the MGT output power and SOFC output power. During the modeling, in order to avoid getting into a local minimum, an improved particle swarm optimization (PSO) algorithm is employed to optimize the weights of the OIF Elman neural network. Using the modified OIF Elman neural network identifier, the SOFC/MGT hybrid system is identified on-line, and the parameters of the PID controller are tuned automatically. Furthermore, the corresponding decoupling control law is achieved by the conventional PID control algorithm. The validity and accuracy of the decoupling controller are tested by simulations in MATLAB environment. The simulation results verify that the proposed control strategy can achieve favorable control performance with regard to various load disturbances.     

Degradation-oriented real-time power control of fuel cell hybrid vehicles under uncertain driving conditions

This work provides a real-time power allocation algorithm to address uncertain actual driving situations for fuel cell hybrid vehicles. To predict the vehicle speed under nondeterministic driving conditions, a fusion prediction model is developed based on the advantages of the Markov chain and neural network. The optimal power splitting decision in each receding horizon is then solved using the Pontryagin's minimum principle (PMP) method, considering fuel consumption, State of Charge (SOC), and performance degradation. A degradation model of electrochemical active surface area (ECSA) based on Pt catalyst dissolution was developed. Then the effect of the energy management algorithm on fuel cell degradation was evaluated using the degradation model. Compared with the two conventional real-time power splitting strategies, the approach suggested in this research can better reduce the fuel consumption and maintain the stability of battery SOC with a lower fluctuation while taking into account the degradation of the fuel cell.     

Thermo-economic modeling of an indirectly coupled solid oxide fuel cell/gas turbine hybrid power plant

Power generation using gas turbine (GT) power plants operating on the Brayton cycle suffers from low efficiencies, resulting in poor fuel to power conversion. A solid oxide fuel cell (SOFC) is proposed for integration into a 10 MW gas turbine power plant, operating at 30% efficiency, in order to improve system efficiencies and economics. The SOFC system is indirectly coupled to the gas turbine power plant, paying careful attention to minimize the disruption to the GT operation. A thermo-economic model is developed for the hybrid power plant, and predicts an optimized power output of 20.6 MW at 49.9% efficiency. The model also predicts a break-even per-unit energy cost of USD 4.65 ¢ kWh⁻¹ for the hybrid system based on futuristic mass generation SOFC costs. This shows that SOFCs may be indirectly integrated into existing GT power systems to improve their thermodynamic and economic performance.     

Hydrogen as an activating fuel for a tidal power plant

Ocean tides, as an environmentally clean and inexhaustible natural source of energy, can be used as one alternative for replacing fossil fuels. But because the tides are dependent on the moon phases, which do not always coincide with the time of human activity, tidal projects usually require a special system for the accumulation of energy for off-peak periods. The production of hydrogen by electrolysis can be considered one such system. This paper outlines the method by which hydrogen produced during off-peak tidal power plant operation can be used as an activating fuel to furnish the same plant during the peak-load demands.With our approach (see [1]) the energy of the tide is converted into the energy of compressed air by means of specialized chambers which are put on the ocean bed. Ocean water from the dammed region passes through the chamber where it works as a natural piston compressing air in the upper part of the closure. For the peak periods the compressed air can be heated by combustion of the stored hydrogen, and expanded through high-speed gas turbine generators. For the off-peak periods, the energy of non-heated compressed air is used for the production of the hydrogen fuel. In this case the total electric output of the power plant would be decreased somewhat because the losses of the energy would be taken for the production of the hydrogen fuel.     

Thermo-economic optimization of an indirectly coupled solid oxide fuel cell/gas turbine hybrid power plant

Power generation using gas turbine (GT) power plants operating on the Brayton cycle suffers from low efficiencies, resulting in poor fuel to power conversion. A solid oxide fuel cell (SOFC) is proposed for integration into a 10-MW GT power plant, operating at 30% efficiency, in order to improve system efficiencies and economics. The SOFC system is indirectly coupled to the GT, in order to minimize the disruption to the GT operation. A thermo-economic model is developed to simulate the hybrid power plant and to optimize its performance using the method of Lagrange Multipliers. It predicts an optimized power output of 18.9 MW at 48.5% efficiency, and a breakeven per-unit energy cost of USD 4.54 ¢ kW h⁻¹ for the hybrid system based on futuristic mass generation SOFC costs.     

Single-level optimization of a hybrid SOFC–GT power plant

The detailed synthesis/design optimization of a hybrid solid oxide fuel cell–gas turbine (SOFC–GT) power plant is presented in this paper. In the first part of the paper, the bulk-flow model used to simulate the plant is discussed. The performance of the centrifugal compressors and radial turbine is determined using maps, properly scaled in order to match the values required for mass flow rate and pressure ratio. Compact heat exchangers are simulated using Colburn and friction factor correlations. For the SOFC, the cell voltage versus current density curves (i.e. polarization curves) are generated on the basis of the Nernst potential and overvoltages. Validation of the SOFC polarization curves is accomplished with data available from Siemens Westinghouse. Both the steam–methane pre-reforming and internal reforming processes are modeled assuming the water–gas shift reaction to be equilibrium-controlled and the demethanization reactions to be kinetically controlled. Finally, a thermoeconomic model is developed by introducing capital cost functions for each plant component. The whole plant is first simulated for a fixed configuration. Then, a synthesis/design optimization of the plant is carried out using a traditional single-level approach. The results of the optimization are presented and discussed.     

Innovative configuration of a hybrid nuclear-parabolic trough solar power plant

This paper proposes a combination of a nuclear and a concentrated solar power (CSP) plant. Most of today’s operating nuclear reactor systems are producing saturated steam at relatively low pressure. This, in turn, limits their thermodynamic efficiency. Superheating of nuclear steam with solar thermal energy has the potential to overcome this drawback. An innovative configuration of a hybrid nuclear-CSP plant is assembled and simulated. It brings together a small pressurised water reactor and a parabolic trough solar field. The solar heat is transferred to nuclear steam to raise its temperature. Continuous superheating is provided through molten salts-based thermal energy storage (TES). The results from design point calculations show that solar superheating has the potential to increase nuclear plant electric efficiency significantly. Solar heat to electricity conversion efficiency defined as the ratio of extra generated power to collected solar energy reaches unprecedented rates of 52%. An off-design model was used to simulate 24-h operation for one year by simulating 8760 cases. Due to TES non-stop operation is manageable.     

Multivariable robust control of a power plant deaerator

The design of a robust controller for the deaerator of the Experimental Breeder Reactor-II (EBR-II) that uses the linear quadratic Gaussian with loop transfer recovery (LQG/LTR) procedure is described. At present, classical proportional-integral (PI) controllers are used to control the deaerator. When the operating condition changes, the system is disturbed, or a fault occurs, and the PI controllers may fail to maintain the desired performance. A robust controller that can accommodate system faults and obtain a reasonable behavior for a wide range of model uncertainty was designed. The controller provides the desired performance despite a considerable change in the operating condition, accommodates some of the failures that can occur, and provides the choice of penalizing one variable over another. The design is tested for robustness by varying the system operating conditions and simulating a steam valve failure. The set of nonlinear simulations using the modular modeling system and the advanced continuous simulation language is included