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At least 163 records · Page 9

Exploring the Interface of Skin-Layered Titanium Fibers for Electrochemical Water Splitting

Water electrolysis is the key to a decarbonized energy system, as it enables the conversion and storage of renewably generated intermittent electricity in the form of hydrogen. However, reliability challenges arising from titanium-based porous transport layers (PTLs) have hitherto restricted the deployment of next-generation water-splitting devices. Here, it is shown for the first time how PTLs can be adapted so that their interface remains well protected and resistant to corrosion across ˜4000 h under real electrolysis conditions. It is also demonstrated that the malfunctioning of unprotected PTLs is a result triggered by additional fatal degradation mechanisms over the anodic catalyst layer beyond the impacts expected from iridium oxide stability. Now, superior durability and efficiency in water electrolyzers can be achieved over extended periods of operation with less-expensive PTLs with proper protection, which can be explained by the detailed reconstruction of the interface between the different elements, materials, layers, and components presented in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using waste CO 2 from corn ethanol biorefineries for additional ethanol production: life‐cycle analysis

Abstract Corn ethanol plants generate high‐purity carbon dioxide (CO 2 ) while producing ethanol. If that CO 2 could be converted into ethanol by carbon capture and utilization technologies it would be possible to increase ethanol production more than 37% without additional corn grain inputs. Gas fermentation processes use microbes to convert carbon‐containing gases into ethanol and so have the potential to be used with the CO 2 from biorefineries for this purpose. However, as CO 2 utilization technologies for converting thermodynamically stable CO 2 are typically energy intensive, it is necessary to evaluate the related life‐cycle greenhouse gas (GHG) emissions (carbon intensities or CIs) to see whether there are actual emission reduction benefits. In this study, we evaluate the CIs of ethanol produced from high‐purity CO 2 in corn ethanol plants by gas fermentation plus electrochemical reduction. Our analysis shows that the sources of electricity and hydrogen are key drivers of CO 2 ‐based ethanol's GHG emissions. With wind electricity, the design cases show the potential of near‐zero CI ethanol (1.1 g CO 2 e/MJ), but that can increase to up to 331–531 g CO 2 e/MJ when today's U.S. Midwest electricity mix is used. To avoid the renewable electricity intermittency issue, we considered a power purchase agreement option using wind electricity 40% of the time and using the regional mix for the rest, which provides a 42% GHG emission reduction from the CI of gasoline. © 2020 The Authors and UChicago Argonne, LLC, Operator of Argonne National Laboratory. Biofuels, Bioproducts and Biorefining published by Society of Chemical Industry and John Wiley & Sons, Ltd.

09 BIOMASS FUELS↗

Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m −3 ) and negligible self‐discharge that makes them uniquely suited as compact, stand‐alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi‐cycle efficiency and high‐levelized cost of storage. In this study, a model is developed to predict the pulverization limit or R crit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy‐efficient manufacturing process (solid‐state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of R crit on hydration and dehydration kinetics is also investigated.

25 ENERGY STORAGE↗

Cryogenic energy storage: Standalone design, rigorous optimization and techno-economic analysis

Energy storage allows flexible use and management of excess electricity and intermittently available renewable energy. Cryogenic energy storage (CES) is a promising storage alternative with a high technology readiness level and maturity, but the round-trip efficiency is often moderate and the Levelized Cost of Storage (LCOS) remains high. The complex flowsheets with intricate thermodynamics at cryogenic temperatures as well as the presence of multiple loops and refrigeration cycles pose considerable challenges for rigorous model-based design and optimization of CES systems. We present an optimization strategy that couples rigorous process simulation and Bayesian optimization with flowsheet decomposition and identification of hidden coupling constraints to optimally design standalone CES systems. Further refinement is done via a local search using the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. Here our results indicate that it is possible to achieve more than 52% round-trip efficiency and an LCOS of $153/MWh for a standalone 100 MW/400 MWh CES system limited to short-term storage with daily charging–discharging. However, a detailed techno-economic assessment reveals that the LCOS considering total capital investment may exceed $267/MWh when all direct and indirect costs of installation and operation are considered.

25 ENERGY STORAGE↗

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bipolar Membranes for Ion Management in (Photo)Electrochemical Energy Conversion

Conspectus (Photo)electrochemical energy conversion is important in the development of a carbon-neutral energy economy because it can provide a pathway for mitigating the intermittency of renewable energy sources such as wind and solar. In order to operate efficiently, these technologies, which include photoelectrochemical cells, water and CO 2 electrolyzers, fuel cells, and redox flow batteries, require fast charge transfer kinetics at the electrode/electrolyte interface as well as robust ion management in the electrolyte. In conventional electrolyzers and fuel cells, the electrolyte is strongly acidic or basic and ionic current is carried by H + or OH – ions. In contrast, photoelectrodes and electrocatalysts for water splitting are often studied in buffered solutions. The question of ion balance in these systems led us to analyze the polarization losses due to ion concentration gradients in cells that employed various buffer–membrane combinations. Continuously driving the buffer ions across an ionomer membrane not only lowers the buffer capacity of an aqueous electrolyte but also introduces pH gradients that result in significant energy losses. To address the problem, we and other groups have studied the use of reverse-biased bipolar membranes (BPMs) in (photo)electrolytic cells. BPMs consist of an anion exchange layer (AEL) laminated with a cation exchange layer (CEL) and are usually equipped with a catalytic layer in between to accelerate the water dissociation reaction. At the AEL/CEL interface, water dissociates into protons and hydroxide ions, which replenish those consumed at the cathode and anode. Compared to conventional water electrolyzers with proton/anion exchange membranes (PEM/AEM), BPM electrolyzers provide the unique advantage of continuously operating the cathode and anode under different pH conditions, which is desirable when the two electrode reactions have different pH requirements. BPMs also enable the use of buffered electrolytes at pH values that are optimized for electrode stability and product selectivity in applications such as CO 2 electrolysis. Product crossover losses and CO 2 pumping can be dramatically reduced in BPM-based CO 2 electrolyzers, relative to conventional alkaline membranes, by electrostatic repulsion (of anionic products) and electroosmotic drag (for neutral products). BPM-based gas fed CO 2 electrolyzers can achieve high current density, but they suffer from low Faradaic efficiency (FE) due to the acidic local environment of the CEL. This problem can be mitigated by adding an aqueous buffering layer or by creating a weak acid cation exchange film on the CEL face of the membrane. The use of BPMs in fuel cells and redox flow batteries offers some interesting advantages. Configurations with both reverse and forward bias have been studied, but forward bias has been favored due to material compatibility, reaction kinetics, and thermodynamic considerations. The net reaction at the AEL/CEL interface is the acid–base neutralization reaction, which has a high inherent reaction rate constant, but in the BPM is limited to a nanometric space-charge layer and requires efficient catalysis to achieve high current density. Understanding the mechanism of the acid–base neutralization and the opposite process, the water dissociation reaction, will be essential for improving the performance of forward-biased BPMs. In conclusion, this Account reviews our current understanding of the working mechanisms of BPMs and discusses how we can use them to effectively manage ions for various (photo)electrochemical applications.

Yan, Zhifei↗

Toward High-Voltage Cathodes for Zinc-Ion Batteries: Discovery Pipeline and Material Design Rules

Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.

electrodes↗

A High-Rate Lithium Manganese Oxide-Hydrogen Battery

Rechargeable hydrogen gas batteries show promises for the integration of renewable yet intermittent solar and wind electricity into the grid energy storage. Here, we describe a rechargeable, high-rate, and long-life hydrogen gas battery that exploits a nanostructured lithium manganese oxide cathode and a hydrogen gas anode in an aqueous electrolyte. The proposed lithium manganese oxide-hydrogen battery shows a discharge potential of ~1.3 V, a remarkable rate of 50 C with Coulombic efficiency of ~99.8%, and a robust cycle life. A systematic electrochemical study demonstrates the significance of the electrocatalytic hydrogen gas anode and reveals the charge storage mechanism of the lithium manganese oxide-hydrogen battery. This work provides opportunities for the development of new rechargeable hydrogen batteries for the future grid-scale energy storage.

25 ENERGY STORAGE↗

Boosting the performance of reversible solid oxide electrochemical cells with a novel hybrid oxygen electrode, Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ

Solid oxide electrochemical cells (SOECs) stand out as a highly promising clean energy technology that offers several benefits, showing significant potential to play a pivotal role in the transition towards a sustainable and low-carbon energy future. SOECs can efficiently convert the chemical energy stored in fuels to electricity in fuel cell mode, and produce various chemicals from abundant feedstocks (e.g., CO 2 , H 2 O) and intermittent solar/wind-based renewable electricity. Despite extensive efforts that have been devoted to designing novel materials and optimizing SOEC manufacturing processes, aiming to achieve enhanced energy efficiency, the current SOECs still suffer from poor performance, which is mainly due to the sluggish oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) kinetics. To address this challenge, in this work, we have successfully designed an in situ formed hybrid oxygen electrode material (Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ ), which significantly improves the surface oxygen exchange coefficient and bulk oxygen-ion diffusion coefficient, enhancing the OER and ORR electrocatalytic activities. Further, the SOECs equipped with this newly developed oxygen electrode achieved exceptional performance for power generation using both hydrogen and propane as the fuels. At 750 °C, a peak power density of 2.4 W cm -2 was obtained with H 2 as the fuel. Additionally, the SOECs attain unprecedented performance in steam electrolysis mode. A current density of 4.4 A cm -2 was achieved at 1.3 V and 750 °C, which represents the highest performance among all yttria-stabilized zirconia (YSZ) electrolyte-based SOECs. The SOECs also deliver remarkable stability during the accelerated stability testing, highlighting the great potential of Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ as a high-performance oxygen electrode for next generation SOECs.

08 HYDROGEN↗

Stochastic Pricing Game for Aggregated Demand Response Considering Comfort Level

In recent years, demand response (DR) has been explored as a fundamental strategy for demand-side management due to its advantages in mediating intermittency of renewable energy generation, load shifting, etc. To engage customers in DR programs, several deterministic price-based DR strategies have been developed and implemented. However, the stochastic weather conditions and occupants' consumption behaviors often make the deterministic solution less robust to uncertainties. In this paper, with the consideration of the uncertainties, a stochastic Stackelberg game is proposed to model the price-demand negotiation between a distributed system operator and load aggregators, where the virtual battery constraints are extracted from the building thermostatically controlled loads (TCLs)‘ characteristics to guarantee comfortable TCLs' levels. Following the negotiation, a priority-based control method is used to allocate the optimal aggregated power DR profile at the building level and track the power signal. Several groups of experiments have demonstrated the effectiveness and robustness of the stochastic solutions.

Chen, Yang↗

Collaborative Decision Approach for Electricity Pricing-demand Response Stackelberg Game

Demand response programs are considered as a valuable resource in smart grids that provide several advantages of load shifting, peak load reduction, mediating intermittency of renewable energy integration, etc. Flexible price-based incentives have been recognized as a critical strategy in motivating and compensating consumers' load adjustment actions for successful implementation of demand response. Game theoretical approaches, especially Stackelberg games are popularly adopted to model the relationship between electricity price and customers' demand response and solved by the classical centralized backward induction (BI) method. However, the BI method generally requires convexity of the follower's model for necessary optimality conditions, and the computational time of any centralized approach increases sharply with larger problem instances. In this paper, the Stackelberg game of electricity pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is decomposed based on a collaborative optimization (CO) framework, where each LA is treated as a discipline with its own domain constraints (e.g. building temperature control), while the DSO at the system level tries to reduce the solution discrepancy and guide the searching towards optimality. Several groups of comparison experiments have demonstrated the effectiveness of the proposed collaborative decision approach in solving the demand response game.

Chen, Yang↗

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗

Potential–Dependent BDAC Adsorption on Zinc Enabling Selective Suppression of Zinc Corrosion for Energy Storage Applications

Utility-scale zinc (Zn) batteries are a promising solution to address the problem of intermittency of renewable energy sources; however, Zn-metal anodes in these batteries suffer from capacity loss due to spontaneous corrosion of the Zn especially when high-surface area anode configurations are employed. Additionally, Zn dendrites are known to form during battery charging limiting the cycle-life of these batteries. Electrolyte additives have been explored that prevent aforementioned issues, but these too come at a cost, i.e., surface-blocking additives polarize the electrode surface leading to loss in the voltaic and energy efficiencies of the battery. In this contribution, a novel electrolyte additive, benzyldimethylhexadecylammonium chloride (BDAC), is investigated for its ability to suppresses corrosion of Zn in an acidic (pH = 3) electrolyte. An attribute of BDAC distinct from previously studied additives is that it selectively suppresses electrochemical activity when the Zn electrode is at its corrosion potential; however, during high-rate Zn deposition (charging) or stripping (discharging), BDAC is essentially deactivated and thus it does not appreciably polarize the electrode surface, thus minimizing voltaic efficiency losses. This selective corrosion suppression behavior is explored using slow-scan voltammetry, which reveals hysteresis implying a potential- or current-dependent BDAC adsorption mechanism in which BDAC reaches higher surface coverages when the partial currents at the Zn surface are low (e.g., at or near the corrosion potential), but BDAC coverage is reduced considerably when the Zn deposition or stripping rates are increased. Numerical simulations of the BDAC diffusion-adsorption process corroborate this mechanism. Ramifications of our approach to the selective suppression of Zn dendrites are discussed.

25 ENERGY STORAGE↗

Catalytic Interconversion of Ammonia and Dinitrogen at Base Metals

Best known as a fertilizer, ammonia is also a carbon-free fuel that produces only benign byproducts, nitrogen and water. Moreover, the synthesis of ammonia from water and nitrogen in the air can be used to store energy from renewable, yet intermittent power sources such as solar and wind. This work develops new molecular electrocatalysts to efficiently extract electrical energy from ammonia, a process which currently is underdeveloped. These studies inspire complementary electrochemical approaches for the synthesis of ammonia from nitrogen by coupling it with the protons ultimately to be derived from acidified water. Careful mechanistic studies that outline the molecular steps involved in these chemical transformations will inform the design of new classes efficient catalysts that interconvert ammonia and nitrogen. Importantly, this study targets molecular electrocatalysts with inexpensive, Earth abundant metals such as iron and copper, consistent with the sustainable use and synthesis of ammonia.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Techno-Economic Analysis of a Thermally Integrated Solid Oxide Fuel Cell and Compressed Air Energy Storage Hybrid System

Natural-gas-fueled solid oxide fuel cell (SOFC) systems have the potential for high-efficiency conversion of carbon to power due to the underlying electrochemical conversion process while readily facilitating carbon capture through the separation of the fuel and oxidant sources. Compressed air energy storage (CAES) technology can potentially store significant quantities of energy for later use with a high round-trip efficiency and lower cost when compared with state-of-the-art battery technology. The base load generation capability of SOFC can be coupled with CAES technology to provide a potentially flexible, low-carbon solution to meet the fluctuating electricity demands imposed by the increasing share of intermittent variable renewable energy (VRE) production. SOFC and CAES can be hybridized through thermal integration to maximize power output during periods of high electrical demand and then store power when either demand is low or renewable generation reduces power prices. The techno-economics of a low-carbon hybrid SOFC and CAES system was developed and investigated in the present study. The proposed hybrid system was found to be cost-competitive with other power-generating base-load facilities when power availability was considered. The hybrid system shows increased resilience to changes in a high VRE grid market scenario.

25 ENERGY STORAGE↗

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗