ADVANCED FUEL CELL SYSTEM CONTROL THROUGH STATE SPACE MODELING

Molten carbonate fuel cells provide a promising technology for the operation of future stationary power plants. In order to enhance service life, a detailed understanding of the dynamical behavior of such fuel cell systems is necessary. In particular, fast load changes shall be simulated, (resp., optimized) without risking material stress due to the extreme temperature differences usually accompanying fast load changes. Fast load changes are important for daily operations in order to react on varying demands. Material stress may lead to irreparable damage of the fuel cell stack. For these contradicting goals, a family of hierarchically ordered mathematical models has been developed with the aim of simulating and optimizing the temporal and spatial dynamical behavior of the gas streams, chemical reactions, and potential fields within the fuel cells. Altogether, the most complicated system, which is investigated in the present paper, results in a Pareto-optimal control problem with constraints in form of a huge system of 28 partial differential algebraic equations and ordinary integro-differential algebraic equations and boundary conditions which are themselves partly given by an ordinary differential algebraic system of dimension 9. The PDEs are of parabolic and hyperbolic type; some are degenerate. Moreover, the variables involved in the different submodels of this fully coupled multiphysical system live on considerably different time scales. Optimal control results are presented for a compromise between sufficiently fast load changes and sufficiently small temperature differences within the cell's solid part by means of a specially tailored formulation of a chain of optimal control problems. This procedure benefits from the different time scales of the state variables and keeps the problem manageable and computable despite its tremendous complexity and scale, although standard numerical methods are employed.

Dynamic Operation and Simulation of Post-Combustion CO2 Capture

Compact steam bottoming cycles: Model validation with plant data and evaluation of control strategies for fast load changes

Electrolysis plants producing green hydrogen often face fluctuating renewable power availability and prices. Proton-Exchange-Membrane (PEM) electrolysis technology offers a potential solution, as fast dynamic load changes are possible. With expeditious adjustments to the power availability, a PEM plant can contribute to grid stability while using economically attractive excess power. Alternatively, adapting to fluctuating product demands can reduce the required energy for intermediate storage of hydrogen in liquid form or in pressure tanks.To consistently operate the plant at the optimal load point, precise monitoring of plant performance, integrity, and state is vital. A digital twin running concurrently with the plant increases the available information of the stack data, as well as it simultaneously offers a platform to engage in anomaly detection and diagnosis processes. The goal is to increase reliability, availability, and maintainability, which is made possible through data provided by virtual sensors (calculated sensor values from the digital twin).With a digital twin, critical states of non-measurable conditions in a PEM cell, such as hydrogen crossover, temperature gradients, or the state of degradation, can be determined and addressed in real-time. With all additional information accessible, the digital twin can visualize plant operation and helps in determining efficient transitions between operating points, augmenting plant operation and optimally utilizing the PEM plant’s load flexibility.To leverage these advantages, a digital twin is developed for PEM electrolysis plants. Its structure consists of a dynamic plant model, an interface to the plant, and a state estimation algorithm. The modelling focus lies on the PEM stacks, for which a detailed dynamic multi-physics model is developed. It is structured into the submodels of mass transport, voltage, temperature, and pressure, which combine into an equation-based model solved by a DAE solver. Main features are the membrane discretization for mass transport via the Stefan-Maxwell equations and the one-dimensionally resolved temperature profile across the cell. The voltage model is represented in form of an equivalent circuit, modelling the electric effects of each individual cell layer.Validation and results of the dynamic model are shown, especially highlighting the interaction and dependencies between the sub-models. The mass transport model shows non-linear concentration profiles of crossover components inside the membrane. Consequently, an assessment of the different positions of additional recombination catalyst layers inside the membrane is presented, including the influence of different operating conditions and dynamic loads. Following, temperature profiles across the cell and dynamic voltage responses for operation are shown. All results are discussed in the context of a simulated PEM electrolysis plant in dynamic operation, which is especially expedient concerning automatic load change and automatic start-up strategies.

As a part of various research projects, a methanation pilot plant with a slurry bubble column reactor (SBCR) was commissioned and operated. The plant has a nominal load of a 100 kW methane output (lower calorific value) with a reactor diameter of 260 mm and a reactor length of 2500 mm. First experimental data on the steady-state and dynamic operation of catalytic CO2 methanation are presented. Steady-state results from laboratory-scale studies (<1 kW methane output) published previously were confirmed qualitatively at the pilot plant eliminating wall effects unavoidable in small-scale reactors. As predicted, high H2/CO2 ratios increase CO2 conversion, but excess H2 apparently promotes decomposition of the liquid phase (dibenzyltoluene) used in the bubble column reactor. Additionally, due to the increased reactor dimensions compared to laboratory equipment, it was now possible to observe a thermal response of the SBCR under conditions of rapid gas load changes characteristic of envisaged power-to-gas applications with volatile renewable electricity. As the predicted robustness of the SBCR-concept toward a dynamic operation with fast load changes was demonstrated successfully, it offers an attractive alternative to the established fixed-bed methanation technologies with their inherent limitations on dynamic operability.

The load-following capabilities of power plants became increasingly important in recent years as a means of ensuring a reliable operation of future power systems. In this work, we propose a generic approach, based on reachability analysis, to rigorously verify the safety of critical components that often pose limitations on the flexibility of conventional power plants to perform fast load changes. The proposed reachability algorithm makes it possible to compute the bounds of all possible trajectories for a range of operating conditions while simultaneously meeting the practical requirements of a real power plant. As an example, we consider the verification of the water level inside a drum unit. In contrast to previous work, our results are based on measurement data of a realistic configuration of a boiler system located within a 450 MW combined cycle plant in Germany. We use an abstract model which considers the modelling errors to ensure that all dynamic behaviors of the process are replicated by the abstraction. Through the implementation of our abstract model, we formally guarantee that the water level inside the drum always remains within safe limits for load changes equivalent to 40 MW which, as a result, exploits the power plant's adaptability and load-following capabilities.

Optimization of boiler control to improve the load-following capability of power-plant units

The growing attention to the reduction of fossil fuels dependency in the energy sector has led to an increase in the efforts to improve the renewable energy sources exploitation. Wind and solar generation is constantly growing worldwide but their fully exploitation is strictly dependent on the availability of efficient electrical storage systems. In this context, hydrogen production, by the means of electrolysis processes powered by renewable generators, is an important option which is gaining increasing attention both from academia and industrial side. The conversion of hydrogen into electricity can be realized using fuel cells. However, these systems are not suitable for fast load changes. This aspect limits fuel cells’ ability to smooth out overgeneration issues. In this paper, an innovative closed-loop Brayton cycle integrated with an electrolyser is presented and described. The whole system is conceived as an electrical storage device in which the closed-loop Brayton cycle represents the discharging phase of the electrical energy converted and stored into hydrogen. The paper analyses this novel cycle under the thermodynamic point of view performing the optimization of the main parameters and evaluating its efficiency and performance in comparison with others electrical storage devices. The innovative contribution of the paper, compared to available literature, lies in the valorisation of the oxygen stream (usually discharged into the ambient) from the electrolyser in the Brayton cycle and in the recovery of the water vapour from the gas turbine.

Improving combustion and lowering NO emissions of an industrial coal swirl burner by optimizing its nozzle structure

Regardless its significant potential for generating renewable energy, Moroccan government prohibited the injection of production surplus into the low voltage (LV) network because it still lack the implementing decreases, that represents one of the principal challenges for residential self-production in the country. The focus of this paper work is to introduce and analyze a novel fast MPPT strategy applied in an improved grid-connected Residential PV system respecting the current legislative framework in Morocco, which allow to the consumer being an actor in the energy transition towards a low-carbon society by reducing his dependence to the electrical grid and managing his own energy consumption efficiently by a good switching between photovoltaic (PV) source and the grid and therefore making a framework of smart residence management system. The overall system is designed to improve the energy control performance with two techniques: the first one uses a novel high performance controller to track the maximum power point (MPP) of a photovoltaic array under fast irradiation and load changes. Among the advantages of this proposed controller is the stability of its output voltage with fast response speed to the required parameters. The second one uses a Power Factor Correction (PFC) circuit to ensure the power quality regulation in the grid side via a predictive current control method. Finally, the stability of a closed-loop system is simulated and analyzed using commercial software offering sufficient conditions to validate a practical stability and robustness of the proposed overall designed system.

Lifetime analysis of the steam generator of a solar tower plant

In this paper, a simplified aircraft system model is developed correctly emulating the nonlinear dynamics of complex aircraft models under closed-loop control. The simplified model is based on Dubins models used in optimization algorithms for trajectory control of multiple Unmanned Aeriel Vehicles (UAVs). Algorithms optimizing area coverage for reconnaissance based on UAV capabilities, fuel remaining, and time constraints require simple aircraft models providing ecient solutions in near real-time. However, the simplified models should accurately predict UAV dynamics for proper prediction. For this study, a realistic UAV simulation is developed including nonlinear aerodynamics and kinematics. A UAV autonomous navigation algorithm for waypoint-to-waypoint navigation is derived and integrated in the complex UAV simulation. A simplified system model based Dubins model is developed closely matching the full nonlinear UAV simulation. A Rhumb-line navigation algorithm including a velocity-hold and altitude-hold control system is used for closed-loop control. A navigation system utilizing trajectory planning with Dubins curves is also developed. Both control laws are implemented in a simplified Dubins model and tuned to match the full nonlinear simulation under autonomous control including provisions for head and tail wind conditions. Computer simulations are performed demonstrating waypointto-waypoint navigation with desired final heading trajectories for both the full nonlinear UAV model and the simplified Dubins simulation. Simulation time history analysis is used to verify the accuracy of the simplified model compared to the full nonlinear simulation model.

AC impedance characteristics of a 2 kW PEM fuel cell stack under different operating conditions and load changes

As modern three-phase distribution systems continue to add more nonlinear and fast-changing loads, the need to maintain steady voltage and good power quality has become much more critical. A commonly used solution for these issues is the Unified Power Quality Conditioner (UPQC). It is a custom device that helps the system handle voltage sags, voltage swells, harmonic distortion and unbalanced conditions. The actual performance of a UPQC depends a lot on the control method used to operate it. In this study, two control techniques are compared, fuzzy logic and artificial neural networks (ANN), to understand how well they support voltage regulation and compensation during varying load conditions. The analysis first looks at how the system behaves under induction motor loads and nonlinear loads when no UPQC is present. After that, a UPQC with a basic PI controller is introduced so that it can serve as a reference point. Then the UPQC models controlled by fuzzy logic and by ANN are developed and tested using MATLAB and Simulink. The work focuses on the waveforms of voltage and current, the total harmonic distortion, and how effectively each method maintains system stability when the load changes. The results show that both fuzzy logic and ANN improve the dynamic performance of the system and help bring down the harmonic levels when compared with the traditional PI controller. Among the two methods, the ANN controlled UPQC shows better adaptability and handles sudden load variations more smoothly.

Recently, small solid oxide fuel cell (SOFC) systems have been developed for various applications because of their high performance. In such small generation systems, quick and frequent start-stops are often required. However, it is generally considered that these start-stops with SOFC systems are not preferable because SOFC systems are operated at high temperature. Also, quantitative studies on the thermal behavior of small SOFC systems are limited. The purpose of this paper is to obtain insight into the possibility of using small SOFC systems with quick and frequent start-stops. A simple two-dimensional numerical model for 1kW-class SOFC systems was fabricated to study this problem. The model consists of a cylindrical SOFC stack, a prereformer on the stack, a heat exchanger for exhaust gas, and a thermal insulator that covers the stack and the prereformer. Using this model, first, the characteristics of the power generation efficiency were estimated under various operating conditions. In addition, the validity of the modeling was verified. Next, the start-up dependence on their structure and operating conditions was investigated. Finally, for the cyclic daily start-up and shutdown (DSS) procedure, the total efficiency during a day was calculated when the energy loss during start-stops is considered. As a result of the analysis, the following points were found. First, the validity and accuracy of the modeling was established, and their efficiency under the rated condition becomes 60% (DC/HHV) at a steam-carbon ratio=2.5 and an oxygen utilization=50%. Next, the thickness of the thermal insulator (0.03W∕m∕K) is required to be more than 6cm to reduce the heat loss from the outer surface of the thermal insulator to <5% of the provided fuel energy (2kW) under the rated condition. In this case, it takes ca. 150min to start, if the fuel (methane) flow rate is 3.02NL∕min, which is equivalent to 2kW of heat flow. Finally, for the DSS operation, consisting of repetition of a 16h operation and an 8h stop in a day, the total efficiency decreases by ca. 1.5% from the rated power generation efficiency. Therefore, it is clarified that 1kW-class SOFC systems can be quite suitable even in the case where quick and frequent start-stops are required.