Dynamic Operation and Simulation of Post-Combustion CO2 Capture

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.

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

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.

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.

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

Lifetime analysis of the steam generator of a solar tower plant

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.

ADVANCED FUEL CELL SYSTEM CONTROL THROUGH STATE SPACE MODELING

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.

Electrical distribution system suffers from various problems like reactive power burden, unbalanced loading, voltage regulation and harmonic distortion. Though DSTATCOMS are ideal solutions for such systems, they are not popular because of the cost and complexity of control involved. Phase wise balanced reactive power compensations are required for fast changing loads needing dynamic power factor correcting devices leading to terminal voltage stabilization. Static Var compensators (SVCs) remain ideal choice for such loads in practice due to low cost and simple control strategy. These SVCs, while correcting power factor, inject harmonics into the lines causing serious concerns about quality of the distribution line supplies at PCC. This paper proposes to minimize the harmonics injected into the distribution systems by the operation of TSC-TCR type SVC used in conjunction with fast changing loads at LV distribution level. Fuzzy logic system and ANN is used to solve this nonlinear problem, giving optimum triggering delay angles used to trigger switches in TCR. The scheme with artificial neural network (ANN) is attractive and can be used at distribution level where load harmonics are within limits.

The term carbon dioxide capture and storage (CCS) refers to a range of technologies that can reduce CO2 emissions from fossil fuels enabling the continued use of this fuel type without compromising the security of electricity supply. The technologies applicable to CCS differ in many key aspects; the stage of the electricity generation process at which the CO2 is captured, the CO2 capture process, efficiency, availability and matureness of the technology. The integration of these technologies into power plants results in a reduction in power generation efficiency, which remains one of the major issues for the commercial implementation of CCS. Among the possible technologies, the focus of this thesis is on post-combustion capture as it is a known technology, is readily available and it can be retrofitted to existing power plants. This thesis is concerned with the development of new carbon capture processes that require less energy for CO2 separation and are, at the same time, more environmentally friendly. Prior to the development of any new process, the current state of the art needs to be analysed and updated in order to set realistic targets for the new technology and benchmark the potential of the newly developed processes. Therefore, part of the work of this thesis is a thorough benchmarking exercise in which updated baselines for the performance of conventional post-combustion capture processes are given. The new process concepts developed in this thesis are based on the combination of enhanced absorption and enhanced desorption, two effects encountered in capture processes that are based on precipitating amino acid solvents. For this purpose, the conceptual design methodology has been followed with a specific target of energy reduction set to (at least) 30% of a conventional MEA process.

Post-combustion carbon capture process modeling, simulation, and assessment of synergistic effect of solvents

For the dual three-phase interior permanent magnet synchronous machines (DT-IPMSMs), open-phase fault can cause current unbalance and degrade the drive performance. This article proposes a fault tolerant maximum torque per ampere (FT-MTPA) control for DT-IPMSMs, which can maximize the ratio of the average torque to the stator current and minimize the fault-induced torque ripple. In the proposed approach, optimal FT-MTPA solution is derived and theoretically proven, and current rms is considered as one design constraint to ensure the equivalent loss to the healthy condition. The proposed FT-MTPA control ensures the smooth switching between fault tolerant control and healthy control without inducing noticeable torque ripple. Compared with existing methods, the proposed approach is computation-efficient and fast in achieving the FT-MTPA control, which is critical to practical applications with fast changing loads. Moreover, this article derives the optimal solution from the faulty MTPA model with fault induced terms considered to ensure high torque. Experiments and comparisons with existing methods are conducted to evaluate the proposed approach on a laboratory DT-IPMSM.