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AbstractAlloy anodes composed of microsized particles receive increasing attention recently, which outperform the nanostructured counterparts in both the manufacturing cost and volumetric energy density. However, the pulverization of particles and fracture of solid electrolyte interphase (SEI) during cycling brings about fast capacity degradation. Herein, it is shown how normally considered fragile SEI can become highly elastic through electrolyte chemistry regulation. Compared to the SEI constructed in classic carbonate electrolyte, the atomic force microscopy tests reveal that the one built in ether‐based electrolyte doubles the maximum elastic strain to accommodate the repeated swelling‐contracting. Such an SEI effectively encapsulates the microsized Sb anodes to prevent the capacity loss from particle isolation. Coupled with an intercalation‐assisted alloying reaction mechanism, a sustained capacity of ≈573 mAh g−1 after 180 cycles at 0.1 A g−1 with outstanding initial Coulombic efficiency is obtained, which is among the highest values achieved in K‐ion batteries. This study emphasizes the significance of building robust SEI, which offers the opportunity to enable stable microsized alloy anodes.

With fewer emissions, higher efficiency, and quicker response than traditional coal-fired thermal power plants, the combined-cycle units (CCUs), as gas-fired generators, have been increasingly adapted in the U.S. power system to enhance the smart grids operations. Meanwhile, due to the inherent uncertainties in the deregulated electricity market, e.g., intermittent renewable energy output, unexpected outages of generators and transmissions, and fluctuating electricity demands, the electricity price is volatile. As a result, this brings challenges for an independent power producer (served in the self-scheduling mode) owning CCUs to maximize the total profit when facing the significant price uncertainties. In this paper, a data-driven risk-averse stochastic self-scheduling approach is presented for the CCUs that participate in the real-time market. The proposed approach does not require the specific distribution of the uncertain real-time price. Instead, a confidence set for the unknown distribution is constructed based on the historical data. The conservatism of the proposed approach is adjustable based on the amount of available data. Finally, numerical studies show the effectiveness of the proposed approach.

202407 bcch ; Others ; National Natural Science Foundation of China ; Published ; 24 months ; Green (AAM)

202409 bcch ; Not applicable ; Others ; The Hong Kong Polytechnic University ; Published ; 24 months ; Green (AAM)

Abstract In this study, a small-scale natural gas liquefaction device was built to verify the feasibility of optimization results of the dual nitrogen expansion natural gas liquefaction process with pre-cooling. From the thermodynamics perspective, the feasibility of using R22 instead of propane as a pre-cooling refrigerant, and nitrogen instead of natural gas as the feed gas was verified. Furthermore, a genetic algorithm was used to optimize the operational parameters of the dual nitrogen expansion liquefaction process. The operational performance and adaptability of the process were evaluated based on sensitivity experiments. The experimental results revealed that the relative error of the key node parameters between the experimental and simulation results was within 10%. Moreover, the experimental device and liquefaction process had a relatively large processing capacity (approximately between 35% and 130%), which is suitable when gas field production attenuation is relatively fast. The experimental device was insensitive to the pressure and temperature of the feed gas, and exhibited excellent adaptability.

Abstract Predicting the distribution and resource of gas hydrates and understanding gas hydrate forming mechanisms are critical for assessing natural gas hydrate exploration potential, as well as exploiting hydrates. This study aims to provide a portable solution for evaluating resource of natural gas hydrate and quantifying contribution of methane sources via numerical simulations constrained by site-specific data. To numerically describe the complex process of biogenic methane production, an integrated simulation package, TOUGH + Hydrate + React (TOUGH + HR), was developed by coupling reactive transport, biodegradation and deposition of organic matter with behavior of hydrate-bearing system. Based on observed data from site SH2 in the South China Sea, a growing one-dimensional column model was constructed, and simulated via the developed TOUGH + HR tool. The results showed that when considering biogenic methane was the only source for hydrate, simulated maximum saturation of hydrate reached ~ 0.19, which is much lower than the observed value (~0.46), suggesting that the in-situ biogenic methane is not enough to form the high-saturation hydrate. When the upward flux of methane (considered as thermogenic methane) increased to 1.00 × 10−11 k g · m - 2 · s - 1 , both simulated saturation and distribution of hydrates matched the observed data well, including the profile of remained total organic carbon (TOC), the location of interface between dissolved methane and sulfate (SMI), and the derived chlorinity. Simulation results suggest that the ratio of biogenic methane to thermogenic methane forming hydrates was about 1:3. Predicted amount of methane hydrate using the column model was 3258.33 kg, very close to the estimated based on field observation (3112.82 kg).

This paper intends to contribute to the revision process of the IEEE Standard 115 by demonstrating the applicability of the standstill frequency response (SSFR) test on large salient pole hydrogenerators. The presented SSFR tests are carried out on a 55.6-MVA salient pole machine with laminated rotor, non-continuous damper windings, and a nonintegral slot number. The IEEE-115 SSFR test procedure is applied with special care to rotor positioning as well as accurate data acquisition in the low-frequency range. The maximum likelihood estimation method is utilized for machine parameter identification from the SSFR tests. Obtained parameters are compared with design values in addition to the ones obtained using traditional “sudden no-load three-phase short-circuit,” Dalton–Cameron and “open stator d-axis transient time constant” methods. The accuracy of parameters is also confirmed by comparing the measured three-phase short-circuit current waveforms with the ones obtained by simulating the SSFR-based machine models in an electromagnetic transient -type software. Unlike previous SSFR test cases on large salient pole hydrogenerators, accurate results are obtained.

Abstract Submerged combustion vaporizer (SCV) is a type of liquefied natural gas (LNG) vaporizer which utilizes the combustion heat from the produced natural gas (NG) or boil-off gas (BOG). Because of its compact structure and quick start-up ability, SCV is widely equipped among the world's LNG receiving terminals. In this paper, the operation characteristics of a typical SCV are simulated numerically. The curves of LNG temperature and heat transfer coefficient along the heat transfer tube under the rated condition are calculated and analyzed. The water bath temperature, which is one of the key operation parameters of SCV, is analyzed to evaluate the performance under off-design conditions. It decreases with LNG inlet temperature, and increases with LNG mass flow rate and tube fouling resistance. However, it has little relation with LNG inlet pressure. The minimum heat load, a special issue of SCV to avoid freezing in the bath, is discussed in the end.