Considering the unstable inversion of ill‐conditioned intermediate matrix required in each integral arc in the short‐arc approach presented in Chen et al. (2015, https://doi.org/10.1002/2014JB011470), an optimized short‐arc method via stabilizing the inversion is proposed. To account for frequency‐dependent noise in observations, a noise whitening technique is implemented in the optimized short‐arc approach. Our study shows that the optimized short‐arc method is able to stabilize the inversion and eventually prolong the arc length to 6 hr. In addition, the noise whitening method is able to mitigate the impacts of low‐frequency noise in observations. Using the optimized short‐arc approach, a refined time series of Gravity Recovery and Climate Experiment (GRACE) monthly models called Tongji‐Grace2018 has been developed. The analyses allow us to derive the following conclusions: (a) During the analyses over the river basins (i.e., Amazon, Mississippi, Irrawaddy, and Taz) and Greenland, the correlation coefficients of mass changes between Tongji‐Grace2018 and others (i.e., CSR RL06, GFZ RL06, and JPL RL06 Mascon) are all over 92% and the corresponding amplitudes are comparable; (b) the signals of Tongji‐Grace2018 agree well with those of CSR RL06, GFZ RL06, ITSG‐Grace2018, and JPL RL06 Mascon, while Tongji‐Grace2018 and ITSG‐Grace2018 are less noisy than CSR RL06 and GFZ RL06; (c) clearer global mass change trend and less striping noise over oceans can be observed in Tongji‐Grace2018 even only using decorrelation filtering; and (d) for the tests over Sahara, over 36% and 19% of noise reductions are achieved by Tongji‐Grace2018 relative to CSR RL06 in the cases of using decorrelation filtering and combined filtering, respectively.
Featured Application: The proposed strategy is aimed to solve the peak charging power demand issue of pure electric bus fast-charging station. It is effective for the charging power suppression of stations in the area with extremely limited distribution capacity.Abstract: In order to reduce the recharging time of electric vehicles, the charging power and voltage are becoming higher, which has led to a huge distribution capacity demand and load fluctuation, especially in pure electric buses (PEBs) with large onboard batteries. Based on one actual direct current (DC) fast-charging station, a two-step strategy for the suppression of the peak charging power was developed in this paper, which combined charging optimization and a battery energy storage system (BESS) configuration. A novel charging strategy was proposed, with the PEBs fast-charging during operating hours and normal charging at night, based on a new charging topology. Then, a charging sequence optimization model was established, according to the operation characteristics analysis of the DC fast-charging station. The particle swarm optimization (PSO) algorithm is applied to optimize the charging sequence, which is disordered at present. Linear programming is used to configure the battery energy storage system in order to further decrease the peak charging power and satisfy the distribution capacity constraint. The two-step strategy was simulated by the dataset from the real station. The results show that the distribution capacity demand, charging load fluctuation, electricity cost, and size of the BESS were significantly decreased.
Mass redistribution within the Earth system deforms the surface elastically. Loading theory allows us to predict loading induced displacement anywhere on the Earth’s surface using environmental loading models, e.g., Global Land Data Assimilation System. In addition, different publicly available loading products are available. However, there are differences among those products and the differences among the combinations of loading models cannot be ignored when precisions of better than 1 cm are required. Many scholars have applied these loading corrections to Global Navigation Satellite System (GNSS) time series from mainland China without considering or discussing the differences between the available models. Evaluating the effects of different loading products over this region is of paramount importance for accurately removing the loading signal. In this study, we investigate the performance of these different publicly available loading products on the scatter of GNSS time series from the Crustal Movement Observation Network of China. We concentrate on five different continental water storage loading models, six different non-tidal atmospheric loading models, and five different non-tidal oceanic loading models. We also investigate all the different combinations of loading products. The results show that the difference in RMS reduction can reach 20% in the vertical component depending on the loading correction applied. We then discuss the performance of different loading combinations and their effects on the noise characteristics of GNSS height time series and horizontal velocities. The results show that the loading products from NASA may be the best choice for corrections in mainland China. This conclusion could serve as an important reference for loading products users in this region.
This study demonstrates an efficient 5.8 GHz microwave wireless power transmission (MWPT) system. The whole system comprises a transmitting subsystem and a receiving subsystem. A 64-way phased microwave power source and a transmitting antenna array of 1 m  1 m are included in the transmitting subsystem. By exciting the transmitting array with a 10-dB Gaussian amplitude distribution and a quadratic phase distribution via the phased microwave power source, the transmitting subsystem radiates a low side-lobe and focused microwave beam. The receiving subsystem comprises a receiving antenna array of 0.5 m  0.5 m and 64 rectifiers. The efficient receiving antenna array and rectifiers realize an efficient rectenna array. An experiment on the MWPT system is conducted. The total microwave power output from the source is 24 W, and the transmission distance is 10 m. According to the measurements, the total rectified direct current (DC) power is 4.58 W, and the overall RF-DC efficiency is 19.08%.
Global navigation satellite systems (GNSS) techniques, such as GPS, can be used to accurately record vertical crustal movements induced by seasonal terrestrial water storage (TWS) variations. Conversely, the TWS data could be inverted from GPS-observed vertical displacement based on the well-known elastic loading theory through the Tikhonov regularization (TR) or the Helmert variance component estimation (HVCE). To complement a potential non-uniform spatial distribution of GPS sites and to improve the quality of inversion procedure, herein we proposed in this study a novel approach for the TWS inversion by jointly supplementing GPS vertical crustal displacements with minimum usage of external TWS-derived displacements serving as pseudo GPS sites, such as from satellite gravimetry (e.g., Gravity Recovery and Climate Experiment, GRACE) or from hydrological models (e.g., Global Land Data Assimilation System, GLDAS), to constrain the inversion. In addition, Akaike’s Bayesian Information Criterion (ABIC) was employed during the inversion, while comparing with TR and HVCE to demonstrate the feasibility of our approach. Despite the deterioration of the model fitness, our results revealed that the introduction of GRACE or GLDAS data as constraints during the joint inversion effectively reduced the uncertainty and bias by 42% and 41% on average, respectively, with significant improvements in the spatial boundary of our study area. In general, the ABIC with GRACE or GLDAS data constraints displayed an optimal performance in terms of model fitness and inversion performance, compared to those of other GPS-inferred TWS methodologies reported in published studies.
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