Matteo Gazzani

Using Hydrogen as Gas Turbine Fuel: Premixed Versus Diffusive Flame Combustors

This work aims at estimating the efficiency gain resulting from using lean premixed combustors in hydrogen-fired combined cycles with respect to diffusive flame combustors with significant inert dilution to limit NOx emissions. The analysis is carried out by considering a hydrogen-fired, specifically tailored gas turbine whose features are representative of a state-of-the-art natural gas–fired F-class gas turbine. The comparison between diffusion flame and lean premixed combustion is carried out considering nitrogen and steam as diluents, as well as different stoichiometric flame temperatures and pressure drops. Results show that the adoption of lean premixed combustors allows us to significantly reduce the efficiency decay resulting from inert dilution. Combined cycle efficiency slightly reduces from 58.5%–57.9% when combustor pressure drops vary in the range 3%–10%. Such efficiency values are comparatively higher than those achieved by diffusive flame combustor with inert dilution. Finally, the study investigated the effects of decreasing the maximum operating blade temperature so as to cope with possible degradation mechanisms induced by hydrogen combustion.

A low-energy chilled ammonia process exploiting controlled solid formation for post-combustion CO2 capture

A new ammonia-based process for CO2 capture from flue gas has been developed, which utilizes the formation of solid ammonium bicarbonate to increase the CO2 concentration in the regeneration section of the process. Precipitation, separation, and dissolution of the solid phase are realized in a dedicated process section, while the packed absorption and desorption columns remain free of solids. Additionally, the CO2 wash section applies solid formation to enable a reduction of the wash water consumption. A rigorous performance assessment employing the SPECCA index (Specific Primary Energy Consumption for CO2 Avoided) has been implemented to allow for a comparison of the overall energy penalty between the new process and a standard ammonia-based capture process without solid formation. A thorough understanding of the relevant solid-solid-liquid-vapor phase equilibria and an accurate modeling of them have enabled the synthesis of the process, and have inspired the development of the optimization algorithm used to screen a wide range of operating conditions in equilibrium-based process simulations. Under the assumptions on which the analysis is based, the new process with controlled solid formation achieved a SPECCA of 2.43 MJ kgCO2-1, corresponding to a reduction of 17% compared to the process without solid formation (with a SPECCA of 2.93 MJ kgCO2-1). Ways forward to confirm this significant improvement, and to increase the accuracy of the optimization are also discussed.

Economic and environmental impact of photovoltaic and wind energy high penetration towards the achievement of the Italian 20-20-20 targets

The paper presents an analysis of the operating parameters of the Combined Cycle Gas Turbine (CCGT) systems in Italy in the years from 2006 to 2013, studying the environmental and economic impact of renewable energy sources spread on CCGT. Variable Renewable Energy (VRE) sources development, electricity demand reduction and CCGT overcapacity have affected the CCGT systems that have had to operate at partial load, experiencing several rump-up/down cycles in a day. The consequent increase of CO2 emission and costs have to be considered in a RES high penetration future scenario. The paper aims to evaluate the net avoided emissions by RES and the cost that Italy have incurred to avoid to emit a tonne of CO2. To reach the high penetration of RES targets the attention is switching from the problem of adding more renewable energy installations to the problem of managing the whole “green” electricity production in a smarter way. Considering all the indirect effects caused by RES on the electricity system is essential for everyone who wants to analyse future scenarios.

MO-MCS: An Efficient Multi-objective Optimization Algorithm for the Optimization of Temperature/Pressure Swing Adsorption Cycles

The optimization of cyclic adsorption processes is a challenging task, and has aroused interest in the context of optimizing CO2 capture processes, where the optimization problem typically involves conflicting objectives, such as energy demand and productivity, and nonlinear constraints which enforce the separation targets. In this contribution we propose a revised version of the multilevel coordinate search algorithm, which can cope with nonlinear constraints and multiple objectives. The algorithm is tested for two different temperature swing adsorption cycles and computational results show that MO-MCS performs better than several publicly available multi-objective methods.

Modeling for optimal operation of PEM fuel cells and electrolyzers

This contribution presents and analyzes modeling and minimum cost operation of proton exchange membrane (PEM) fuel cells and electrolyzers. First, detailed thermoelectric models of the electrochemical technologies based on a first-principle approach are presented. Then, as the detailed nonlinear models developed are intractable for use in online optimal control computation, a mixed integer linear program (MILP) is formulated with a piecewise affine approximation of the conversion efficiency and linear temperature dynamics for the devices. The outputs of the simplified linear models are compared with the detailed ones, when optimally producing and consuming a fixed quantity of hydrogen gas. Comparisons are performed for a variety of price scenarios and efficiency approximations, for both the fuel cell and electrolyzer.

On the optimal design of forward osmosis desalination systems with NH3-CO2-H2O solutions

Membrane-based forward osmosis, especially when NH3–CO2–H2O mixtures are adopted as draw solutions, is a promising new process for clean water production, including seawater desalination and wastewater treatment. In such a process, water is first removed from the feed (e.g. seawater) by exploiting the osmotic pressure difference between the feed and the draw solution, which are at the two sides of the membrane; in a second step, drinkable water is produced by treating the water-rich draw solution in a distillation column. Accordingly, the main energy requirement is thermal energy for the reboiler. In order to enable a robust performance evaluation of forward osmosis systems, developing a comprehensive simulation framework that couples a rigorous distillation model and a reliable thermodynamic model for electrolyte solutions with an optimization routine is needed. With this work, we aim at satisfying this need by providing (i) a comprehensive analysis of forward osmosis-based systems, with special emphasis on the recovery of the draw solution and the connected energy demand, and (ii) a systematic approach to the design and operation of such processes. Ternary phase diagrams of NH3–CO2–H2O are used to characterize the system in terms of osmotic pressure, thermal separation energy and pressure in the distillation column. An optimization routine is then developed to minimize the equivalent energy and the membrane area specific to the water produced: different Pareto curves along with the associated trends in the design variables are identified and explained. Finally, forward osmosis is compared to reverse osmosis and thermal desalination plants.

A MILP model for the design of multi-energy systems with long-term energy storage

Abstract Optimal design and operation of multi-energy systems involving seasonal energy storage are often hindered by the complexity of the optimization problem. Indeed, the description of seasonal cycles requires a year-long time horizon, while the system operation calls for an hour resolution; this turns into a large number of decision variables, especially binaries. This work presents a novel mixed integer linear program methodology that allows considering a year time horizon with hour resolution whilst significantly reducing the complexity of the optimization problem. The validity of the proposed technique is tested by considering a simple system that can be solved in a reasonable computational time without resorting to design days. Findings show that the proposed approach provides results in good agreement with the full-size optimization, allowing to correctly size the energy storage and operate the system with a long-term policy, while significantly simplifying the optimization problem.

A Time-series-based approach for robust design of multi-energy systems with energy storage

Abstract This work proposes a mixed-integer linear program approach to consider the uncertainty of input data in the optimal design of distributed multi-energy systems involving both conventional and renewable-based conversion technologies, as well as storage units. The design procedure determines the minimum-cost combination of technology selection, size and operation. Traditionally, distributed multi-energy systems are designed using deterministic optimization methods, implying that the input data are known when the system optimization is performed. However, such input data are commonly affected by significant uncertainty, making the deterministic solution possibly suboptimal or even unfeasible. Recently, both robust and stochastic optimization have been applied to the optimal design of multi-energy systems. Nevertheless, when including energy storage in the analysis, the traditional techniques are complicated by the short- and long-term evolution of the input data of the underlying optimization problem, as well as their complex interactions. Moreover, the analysis of the uncertainties characterizing such input data for the optimal design of multi-energy systems, as well as the evaluation of their impact on the system design, have been investigated in little details. The approach proposed in this work is based on the analysis of the historical time-series representing the input data of the mixed-integer linear program for different years. First, the most important input data in terms of optimality and robustness of the system design are identified. Moreover, the most relevant features of the corresponding time-series are determined and assessed. Then, this information is used to build a custom set of input data which translates into a system design able to guarantee both security of supply and cost optimality.

Multi-Objective Optimization of a Pressure-Temperature Swing Adsorption Process for Biogas Upgrading

Abstract Biomethane has been proven to be a valuable alternative to replace fossil fuels. In order to reduce the energetic cost of production, biogas upgrading technologies have to be improved. In this contribution, a temperature/pressure swing adsorption process is proposed to remove CO2 from the biogas flow, exploiting a non-conventional material and a suitable adsorption cycle. In such processes, the optimization is a particularly challenging task as it typically involves conflicting objectives, such as energy efficiency and productivity, and non-linear constraints, which enforce the separation targets.

High Efficiency SOFC Power Cycles With Indirect Natural Gas Reforming and CO2 Capture

Driven by the search for the highest theoretical efficiency, several studies have investigated in the last years the adoption of fuel cells in the field of power production from natural gas with CO2 capture. Most of the proposed power cycles rely on high temperature fuel cells, namely Solid Oxide Fuel Cells (SOFC) and Molten Carbonate Fuel Cells (MCFC), based on the concept of hybrid fuel cell plus gas turbine cycles. Accordingly, high temperature fuel cells are integrated with a simple or modified Brayton cycle. As far as SOFC are concerned, two main plant solutions can be identified depending on the integration with the natural gas reforming/shift section: (i) systems where natural gas is — partially or totally — internally reformed in the fuel cell and (ii) systems where natural gas is reformed before the fuel cell and the cell is fed with a high hydrogen syngas. In both cases, CO2 can be separated downstream the fuel cell via a range of available technologies, e.g. chemical or physical separation processes, oxy-combustion and cryogenic methods.Following a literature review on very promising plant configurations, this work investigates the advantages and limits of adopting an external natural gas conversion section with respect to the plant efficiency. As a reference plant we considered a power cycle proposed by Adams and Barton [8], whose performance is the highest found in literature for SOFC-based power cycles, with 82% LHV electrical efficiency. It is based on a pre-reforming concept where fuel is reformed ahead the SOFC which thus works with a high hydrogen content fuel. This plant was firstly reproduced considering all the ideal assumptions proposed by the original authors. As second step, the simulations were focused on revising the power cycle, implementing a complete set of assumptions about component losses and more conservative operating conditions about fuel cell voltage, heat exchangers minimum temperature differences, maximum steam temperature, turbomachinery efficiency, component pressure losses and other adjustments.Considering the consequent modifications with respect to the original layout, the net electric efficiency changes to around 66% LHV with nearly complete (95%+) CO2 capture, a still remarkable but less attractive value, while requiring a very complex and demanding heat exchangers network. Detailed results are presented in terms of energy and material balances of the proposed cycles. All the simulations have been carried out with the proprietary code GS, developed by the GECOS group at Politecnico di Milano.Copyright