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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.

Abstract This paper presents a novel multi-time-stage input–output-based modeling framework for simulating the dynamics of bioenergy supply chains. One of the key assumptions used in the model is that the production level at the next time-stage of each segment of the energy supply chain adjusts to the output surplus or deficit relative to targets at the current time period. Furthermore, unlike conventional input–output models, the technology matrix in this approach need not be square, and thus can include coefficients denoting flows of environmental goods, such as natural resources or pollutants. Introducing a feedback control term enables the system to regulate the dynamics, thus extending the model further. This is an important feature since the uncontrolled dynamic model exhibits oscillatory or unstable behavior under some conditions; in principle, the control term allows such undesirable characteristics to be suppressed. Numerical simulations of a simple, two-sector case study are given to illustrate dynamic behavior under different scenarios. Although the case study uses only a hypothetical system, preliminary comparisons are made between the simulation results and some broad trends seen in real bioenergy systems. Finally, some of the main policy implications of the model are discussed based on the general dynamic characteristics seen in the case study. In particular, insights from control theory can be used to develop policy interventions to impart desirable dynamic characteristics to nascent or emerging biofuel supply chains. These interventions can be used to guide the growth of bioenergy supplies along final demand trajectories with minimal fluctuation and no instability.

Abstract 3D printing technologies are being called on to revolutionize the manufacturing industry of the energy sector, especially when involving functional materials and complete devices. These additive manufacturing technologies show competitive advantages over conventional processes, however only a few studies have assessed their environmental implications. In this work, the environmental performance of a Solid Oxide Fuel Cell stack produced using a novel 3D printing approach is conducted for the first time using Life Cycle Assessment. In addition, a comparative study with conventional manufacturing methods is carried out. The results reveal that the production of the 3D printing materials has the highest environmental impact (between 50% and 98%) in half of the categories studied. In contrast, the end-of-life stage represents less than 1% of the total impact. End-of-life scenarios are also presented and discussed, indicating that a recycling rate of 70% for Nickel and YSZ materials performs better than the defined landfill and incineration disposal scenarios. Furthermore, 3D printing shows the best overall environmental performance compared to other conventional methods. The main improvement is seen in the material production stage, where a savings ranging from 37% to 97% (depending on the category analysed) is observed. This is mainly due to the use of a ceramic material for the interconnects instead of Chromium-based alloys used in a more conventional approach. Finally, it was observed that the energy required for 3D printing in the manufacturing stage is a sensible parameter to the environmental performance of the SOFC 3D printing technology.

Abstract In recent years, distributed energy systems (DESs) have been recognized as a promising option for sustainable development of future energy systems, and their application has increased rapidly with supportive policies and financial incentives. With growing concerns on global warming and depletion of fossil fuels, design optimization of DESs through economic assessments for short-run benefits only is not sufficient, while application of exergy principles can improve the efficiency in energy resource use for long-run sustainability of energy supply. The innovation of this paper is to investigate exergy in DES design to attain rational use of energy resources including renewables by considering energy qualities of supply and demand. By using low-temperature sources for low-quality thermal demand, the waste of high-quality energy can be reduced, and the overall exergy efficiency can be increased. The goal of the design optimization problem is to determine types, numbers and sizes of energy devices in DESs to reduce the total annual cost and increase the overall exergy efficiency. Based on a pre-established DES superstructure with multiple energy devices such as combined heat and power and PV, a multi-objective linear problem is formulated. In modeling of energy devices, the novelty is that the entire available size ranges and the variation of their efficiencies, capital and operation and maintenance costs with sizes are considered. The operation of energy devices is modeled based on previous work on DES operation optimization. By minimizing a weighted sum of the total annual cost and primary exergy input, the problem is solved by branch-and-cut. Numerical results show that the Pareto frontier provides good balancing solutions for planners based on economic and sustainability priorities. The total annual cost and primary exergy input of DESs with optimized configurations are reduced by 21–36% as compared with conventional energy supply systems, where grid power is used for the electricity demand, and gas-fired boilers and electric chillers fed by grid power for thermal demand. A sensitivity analysis is also carried out to analyze the influence of energy prices and energy demand variation on the optimized DES configurations.

Abstract Widespread electrification, i.e., switching direct fossil fuel end-uses to electricity, coupled with renewable power use is essential to achieve aggressive greenhouse gas and criteria pollutant emission reduction targets. Few have investigated the requisite electric grid infrastructure transformation and technology path coupled with spatial and temporal resolution of criteria pollutant emissions for assessing air quality impacts. In this study, we analyze grid and emission impacts of electrifying end-use sectors while decarbonizing power generation, using detailed modeling of infrastructure stocks and economic dispatch of the electric utility grid network. Results show that decarbonizing power supply without electrifying end-use sectors can reduce total greenhouse gas emissions by only 2 percent, while partial electrification of end-use sectors alongside decarbonizing electricity generation yields up to 20.3 percent greenhouse gas emission reductions compared to 1990 levels. Spatially and temporally resolved criteria pollutant emissions portend certain scenarios that improve air quality more than others, requiring consideration of spatial and temporal emission perturbations dictated by specific electrification end-uses and power generation technology dynamics for meeting the increased electric demand.

Abstract The flow past a Bach-type vertical-axis wind or current turbine is simulated using a viscous Discrete-Vortex Method at a Reynolds number of 1500. The main purpose of the study is to evaluate the suitability of Bach-type turbines for use as micro-scale energy harvesters that can be applied to power, for example, sensor nodes of a wireless sensor network. The maximum power coefficient of the turbine operating at a prescribed constant tip-speed ratio is found to be 0.18, which is comparable to the performance of the same turbine at much higher Reynolds numbers, thus indicating only minimal performance penalty for miniaturization. The speed of the turbine has a strong influence on the evolution of vortical flow structures. A new wake-capturing mechanism that boosts the performance of the turbine is discovered from the simulations for a certain range of tip-speed ratios where the vortex shed by the advancing blade helps drive the returning blade. In addition to prescribed rotation, free rotation of a steel Bach-type turbine in water is also investigated. Significant fluctuation in angular velocity over one period of rotation is observed. This speed fluctuation is found to be detrimental to energy extraction, reducing the maximum power coefficient to approximately 0.16. The estimated power generating capacity of a micro-scale turbine indicates that it can significantly extend the life expectancy of a wireless sensor node or even maintain the node in a low-power state indefinitely.

Abstract The distributed generation (DG) of combined heat and power (CHP) for commercial buildings is gaining increased interest, yet real-world installations remain limited. This lack of implementation is due, in part, to the challenging economics associated with volatile utility pricing and potentially high system capital costs. Energy technology application analyses are also faced with insufficient knowledge regarding how to appropriately design (i.e., configure and size) and dispatch (i.e., operate) an integrated CHP system. Existing research efforts to determine a minimum-cost-system design and dispatch do not consider many dynamic performance characteristics of generation and storage technologies. Consequently, we present a mixed-integer nonlinear programming (MINLP) model that prescribes a globally minimum cost system design and dispatch, and that includes off-design hardware performance characteristics for CHP and energy storage that are simplified or not considered in other models. Specifically, we model the maximum turn-down, start up, ramping, and part-load efficiency of power generation technologies, and the time-varying temperature of thermal storage technologies. The consideration of these characteristics can be important in applications for which system capacity, building demand, and/or utility guidelines dictate that the dispatch schedule of the devices varies over time. We demonstrate the impact of neglecting system dynamics by comparing the solution prescribed by a simpler, linear model with that of our MINLP for a case study consisting of a large hotel, located in southern Wisconsin, retrofitted with solid-oxide fuel cells (SOFCs) and a hot water storage tank. The simpler model overestimates the SOFC operational costs and, consequently, underestimates the optimal SOFC capacity by 15%.

Abstract Previous research has shown that a drastic reduction of charging time compared to constant current constant voltage (CC/CV) charging protocol is possible while suppressing degradation causes by combining constant charging and pulse discharging current. However, effects of temperature variation on side reaction and lithium plating and effects of the frequency of pulse current on lithium stripping have not been considered. In fact, charging currents and operating temperatures dominantly affect the cycle life of battery, where both side reaction and lithium plating are competing. In this paper, reduced order electrochemical life models are developed and validated against experimental data collected at different currents and temperatures and then used to find out optimal temperatures at given charging currents with respect to degradation rates. Thereafter, an optimal charging current at different SOCs has been found using nonlinear model predictive control and then the optimal temperature is determined from the relationship obtained by the models, which reduces side reaction rate and lithium plating rate. In addition, pulse discharging current is added to promote the lithium stripping that recovers ions out of the plated lithium, where the amplitude and frequency of the pulse current are optimized using the models. Finally, the proposed charging method and the 1 C CC/CV charging method were tested in Battery-In-the-Loop using a large format pouch type lithium ion battery to compare each other, where 61% and 39% of charging time is reduced up to 80% and 100% SOC, respectively, while the capacity fade is comparable.

Abstract High intensity distributed combustion assists to provide substantial performance improvement for gas turbine applications for our quest to simultaneously seek improved pattern factor, ultra-low emission of NOx and CO, low noise, enhanced stability, fuel flexibility and higher efficiency. In such combustion method, controlled mixing between the injected air, fuel and hot reactive gases from within the combustor prior to mixture ignition must occur to achieve distributed reactions in the entire combustion chamber. Near zero emission of NO and CO has been achieved using methane as the fuel under distributed combustion conditions at high heat (energy) release intensity of 22–36 MW/m3 atm. The conditions to form distributed reaction in the combustor are further investigated through variation of air injection velocity with the output parameters focused on pollutants emission and combustor performance. The isothermal flowfield is examined using particle image velocimetry (PIV) to determine key features associated with the flowfield and its effects on pollutants emission and stability. The results showed higher entrainment and turbulence at increased injection velocity. Increase in injection velocity decreased NO emissions by some 20–48% with minimal impact on CO emission under premixed fuel–air condition. Less than 4 ppm of NO was achieved at an injection velocity of 46 m/s at an equivalence ratio of 0.7 and heat (energy) release intensity of 31.5 MW/m3 atm using normal temperature air. High injection velocity at the same operating condition decreased NO emission by some 20% to 3.2 ppm. Higher injection velocity under preheated inlet air condition further decreased NO to 2 ppm (48% reduction) at an equivalence ratio of 0.5. The results under non-premixed combustion conditions showed similar behavior. The reduction of NO with single injection parameter is attributed to improved distributed reaction condition from direct entrainment and rapid mixing of reactive species present in the combustion zone under high intensity combustion conditions.