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Abstract The present work focuses on the numerical simulation of Moderate or Intense Low oxygen Dilution combustion condition, using the Partially-Stirred Reactor model for turbulence-chemistry interactions. The Partially-Stirred Reactor model assumes that reactions are confined in a specific region of the computational cell, whose mass fraction depends both on the mixing and the chemical time scales. Therefore, the appropriate choice of mixing and chemical time scales becomes crucial to ensure the accuracy of the numerical simulation prediction. Results show that the most appropriate choice for mixing time scale in Moderate or Intense Low oxygen Dilution combustion regime is to use a dynamic evaluation, in which the ratio between the variance of mixture fraction and its dissipation rate is adopted, rather than global estimations based on Kolmogorov or integral mixing scales. This is supported by the validation of the numerical results against experimental profiles of temperature and species mass fractions, available from measurements on the Adelaide Jet in Hot Co-flow burner. Different approaches for chemical time scale evaluation are also compared, using the species formation rates, the reaction rates and the eigenvalues of the formation rate Jacobian matrix. Different co-flow oxygen dilution levels and Reynolds numbers are considered in the validation work, to evaluate the applicability of Partially-Stirred Reactor approach over a wide range of operating conditions. Moreover, the influence of specifying uniform and non-uniform boundary conditions for the chemical scalars is assessed. The present work sheds light on the key mechanisms of turbulence-chemistry interactions in advanced combustion regimes. At the same time, it provides essential information to advance the predictive nature of computational tools used by scientists and engineers, to support the development of new technologies.

Abstract In Concentrated Solar Power Plants, steam turbines controlled with standard Proportional Integrative Derivative (PID) methods may suffer from performance downgrading in power generation when the steam conditions deviate from nominal ones. An enhancement of standard steam turbine controller can be the key to achieve optimal performance also in non-nominal steam conditions. This paper presents the improvement of the PID control concept by exploiting Fuzzy Logic, an artificial intelligence technique that allows taking into account the human experience and knowledge on the system behavior. A real Concentrated Solar Power Plant has been modeled focusing on generated power control loop, its stability and performance analysis, knowledge useful to design a Fuzzy Inference System. A fuzzy logic controller is proposed to continuously adapt the PID parameters, to improve the steam turbine governor action. Its performance is compared to the classical PID tuned according to three different approaches. The fuzzy logic PID controller extends the simplicity of PID and adapts the control action to actual operating condition by providing the system with a sort of “decision-making skill”. The possibility to design implementable algorithms on a Programmable Logic Controller, which have stringent computational speed and memory requirements, has been explicitly taken into account in the developed work, through the minimization of the controller complexity with a reduced number of fuzzy sets and fuzzy rules within the fuzzy inference system.

In-situ biomethanisation reduces the CO2 in biogas to CH4 via direct H2 injection into an anaerobic digester, but volumetric methane production (VMP) is limited by organic loading. Ex-situ biomethanisation, where gaseous substrates are fed to pure or mixed cultures of hydrogenotrophic methanogens, offers higher VMP but requires an additional reactor and supply of essential nutrients. This work combined the two approaches in a novel hybrid application achieving simultaneous in-situ and ex-situ biomethanisation within an organically-loaded anaerobic digester receiving supplementary biogas. Conventional stirred-tank digesters were first acclimated to H2 addition, increasing biogas methane content from 50% to 95% and VMP from 0.86 to 1.51 L L-1 day-1 at a moderate loading rate of 3 g organic chemical oxygen demand per L per day (g CODorg L-1 day-1). Externally-produced biogas was then added to demonstrate simultaneous biomethanisation of endogenous and imported CO2. This further increased VMP to 2.76 L L-1 day-1 without affecting organic substrate degradation. In-situ CO2 reduction can alter digester pH by reducing bicarbonate buffering: the combined process operated stably at around pH 8.0 with 3-5% CO2 in the headspace. Microbial community analysis indicated the process was mediated by bacterial syntrophic acetate oxidation and highly enriched hydrogenotrophic methanogenic archaea (up to 97% of the archaeal population). This approach presents the opportunity to retrofit a single digester for H2 injection to convert and upgrade biogas from several others, minimising capital and operating costs by utilising both existing infrastructure and waste-derived feedstock nutrients for simultaneous biogas upgrading and power-to-methane.

Abstract Wind power technology is one of the cleanest electricity generation technologies that are expected to have a substantial share in the future electricity mix. Nonetheless, the expected increase in the market share of wind technology has led to an increasing concern of the availability, production capacity and geographical concentration of the metals required for the technology, especially the rear earth elements (REE) neodymium (Nd) and the far less abundant dysprosium (Dy), and the impacts associated with their production. Moreover, Nd and Dy are coproduced with other rare earth metals mainly from iron, titanium, zirconium, and thorium deposits. Consequently, an increase in the demand for Nd and Dy in wind power technology and in their traditional applications may lead to an increase in the production of the host metals and other companion REE, with possible implications on their supply and demand. In this regard, we have used a dynamic material flow and stock model to study the impacts of the increasing demand for Nd and Dy on the supply and demand of the host metals and other companion REE. In one scenario, when the supply of Dy is covered by all current and expected producing deposits, the increase in the demand for Dy leads to an oversupply of 255 Gg of total REE and an oversupply of the coproduced REE Nd, La, Ce and Y. In the second and third scenarios, however, when the supply of Dy is covered by critical REE rich deposits or Dy rich deposits, the increase in Dy demand results in an oversupply of Ce and Y only, while the demand for Nd and La exceeds their supply. In the case of an oversupply of REEs, the environmental impacts associated with the REEs production should be allocated to Dy and consequently to the technologies that utilize the metal. The results also show that very large quantities of thorium will be co-produced as a result of the demand for Dy. The thorium would need to be carefully disposed of, or significant thorium applications would need to be found.

This special edition to be published in Applied Energy brings together a range of papers that explore the complex, multi-dimensional and inter-related issues associated with the supply or value chains that make up energy systems and how a focus on them can bring new insights for energy security in a low carbon transition.\ud \ud Dealing with the trilemma of maintaining energy security, reducing greenhouse gas emissions and maintaining affordability for economies and end users are key issues for all countries, but there are synergies and trade-offs in simultaneously dealing with these different objectives. Currently, industrialised energy systems are dominated by supply chains based on fossil fuels and these, for the most part, have been effective in enabling energy security and affordability. However, they are increasingly struggling to do this, particularly in respect to efforts to tackle climate change, given that the energy sector is responsible for around two-thirds of the global greenhouse gas emissions [1]. A key challenge is therefore how to decarbonise energy systems, whilst also ensuring energy security and affordability. This special issue, through a focus on supply chains, particularly considers the interactions and relationships between energy security and decarbonisation.\ud \ud Energy security is a property of energy systems and their ability to withstand short-term shocks and longer-term stresses depends on other important system properties including resilience, robustness, flexibility and stability [2]. Energy systems are essentially a supply chain comprising of multiple and interrelated sub-chains based around different fuels, technologies, infrastructures, and actors, operating at different scales and locations – from extraction/imports and conversion through to end use [3]. These supply chains have become increasingly globalised and are influenced by the on-going shifts in global supply and demand. Thus the aim of this special issue is to explore and discuss how to enable the development of a secure and sustainable energy system through a better understanding of both existing and emerging low carbon energy supply chains as well as of new approaches to the design and management of energy systems. In part, because moving from a system dominated by fossil fuels to one based on low carbon creates a new set of risks and uncertainties for energy security as well as new opportunities.\ud \ud A large number of submissions from over 18 countries were received for this special edition and 16 papers were accepted after peer review. These address a variety of issues and we have chosen to discuss the findings under two key themes, although many of the papers cut across these: (1) Insights from, and for, supply chain analysis. (2) Insights for energy security and its management. We then provide in (3) a summary of insights and research gaps. Table 1 provides a snapshot of the areas covered by the papers showing: theme (s); empirical domains; and geographical coverage.

Abstract Many organizations in the world are interested in waste management problems and their potential solutions. In order to solve these problems, a Japanese venture company has developed an innovative thermal decomposer for organic wastes called ERCM (Earth-Resource-Ceramic-Machine). The ERCM reactor employs electron injected air to promote the thermal decomposition reaction, while the effect of electron injection into air has not yet been clarified. An experimental work was performed using a fixed bed reactor to explore the effects of different parameters of electron injection into air, the reaction temperature and different feedstock on the syngas generation. The main purpose of this study is to clarify the phenomena occurring in the ERCM reactor where a direct current electric field is produced in the flame reaction zone to enhance the thermal decomposition of wastes. In this regard, a mathematical model for simulating the thermal decomposition of solid waste in the presence of an electric field have been developed. The equations of aero-thermochemistry are coupled to the balance equations for densities of charged species, and the Poisson equation for the electrical potential is solved. The model was validated by the experimental data and showed a good agreement. The results showed that the electric field significantly improves the stabilization of the flame. From the release behavior of CO and CO2, it is noted that the electron injection would affect the char combustion process significantly. Finally the effect of the flame reaction zone generated by the field induced ion wind on the thermal decomposition was investigated.

AbstractThe UK government heat strategy is partially based on decarbonisation pathways from the UK MARKAL energy system model. We review how heat provision is represented in UK MARKAL, identifying a number of shortcomings and areas for improvement. We present a completely revised model with improved estimations of future heat demands and a consistent representation of all heat generation technologies. This model represents all heat delivery infrastructure for the first time and uses dynamic growth constraints to improve the modelling of transitions according to innovation theory. Our revised model incorporates a simplified housing stock model, which is used produce highly-refined decarbonisation pathways for residential heat provision. We compare this disaggregated model against an aggregated equivalent, which is similar to the existing approach in UK MARKAL. Disaggregating does not greatly change the total residential fuel consumption in two scenarios, so the benefits of disaggregation will likely be limited if the focus of a study is elsewhere. Yet for studies of residential heat, disaggregation enables us to vary consumer behaviour and government policies on different house types, as well as highlighting different technology trends across the stock, in comparison with previous aggregated versions of the model.