A calculation model of charge and discharge capacity of electric vehicle cluster based on trip chain

The rapid response characteristics and high-speed growth of electric vehicles (EVs) demonstrate its potential to provide auxiliary frequency regulation services for independent system operators through vehicle-to-grid (V2G). However, due to the spatiotemporal random dynamics of travel behavior, it is challenging to evaluate the ability of EV cluster to provide ancillary services under the premise of reaching the expected state of charge (SOC) level. To address this issue, a novel calculation model of charge and discharge capacity of EV cluster based on trip chain with excellent parallel computing performance is presented in this work. Following the introduction of the characteristic variables of the proposed trip chain model, the user’s continuous travel behavior in a time scale of several weeks is simulated. In particular, a bidirectional V2G scheduling strategy based on the five-zone map is designed to guide the charging and discharging behavior of EVs, where the expected SOC levels are guaranteed. The results of a 3-week travel simulation verify the effectiveness of the presented model in coordinating the V2G scheme and calculating the charge and discharge capacity of the EV cluster

Application of Time-Fractional Order Bloch Equation in Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is one novel fast quantitative imaging framework for simultaneous quantification of multiple parameters with pseudo-randomized acquisition patterns. The accuracy of the resulting multi-parameters is very important for clinical applications. In this paper, we derived signal evolutions from the anomalous relaxation using a fractional calculus. More specifically, we utilized time-fractional order extension of the Bloch equations to generate dictionary to provide more complex system descriptions for MRF applications. The representative results of phantom experiments demonstrated the good accuracy performance when applying the time-fractional order Bloch equations to generate dictionary entries in the MRF framework. The utility of the proposed method is also validated by in-vivo study.Comment: Accepted at 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019

DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection

Monocular 3D detection has drawn much attention from the community due to its low cost and setup simplicity. It takes an RGB image as input and predicts 3D boxes in the 3D space. The most challenging sub-task lies in the instance depth estimation. Previous works usually use a direct estimation method. However, in this paper we point out that the instance depth on the RGB image is non-intuitive. It is coupled by visual depth clues and instance attribute clues, making it hard to be directly learned in the network. Therefore, we propose to reformulate the instance depth to the combination of the instance visual surface depth (visual depth) and the instance attribute depth (attribute depth). The visual depth is related to objects' appearances and positions on the image. By contrast, the attribute depth relies on objects' inherent attributes, which are invariant to the object affine transformation on the image. Correspondingly, we decouple the 3D location uncertainty into visual depth uncertainty and attribute depth uncertainty. By combining different types of depths and associated uncertainties, we can obtain the final instance depth. Furthermore, data augmentation in monocular 3D detection is usually limited due to the physical nature, hindering the boost of performance. Based on the proposed instance depth disentanglement strategy, we can alleviate this problem. Evaluated on KITTI, our method achieves new state-of-the-art results, and extensive ablation studies validate the effectiveness of each component in our method. The codes are released at https://github.com/SPengLiang/DID-M3D.Comment: ECCV 202

Protection for submodule overvoltage caused by converter valve-side single-phase-to-ground faults in FB-MMC based bipolar HVDC systems

One of the most critical faults affecting modular multilevel converter (MMC) based bipolar high-voltage direct-current (HVDC) transmission systems is the single-phase-to-ground (SPG) faults between the converter transformer and the valve. However, half-bridge (HB) and full-bridge (FB) based MMCs exhibit a different behavior following such a fault and, thus, converter protection should be addressed in a different manner for each configuration. For HB-MMCs, an SPG fault at the valve-side leads to a severe overvoltage on the submodule (SM) capacitors in the converter upper arms and to grid-side non-zero crossing currents. Although FB-MMCs only exhibit overvoltage, these are more severe than for their HB counterparts. To address this problem, this paper presents a protection strategy considering thyristor bypass branches placed in parallel with upper arms of FB-MMCs. By employing this configuration, the upper arm overvoltage in the faulted converter is mitigated and remote converters can be quickly blocked using their local protection schemes. For completeness, the effectiveness of the strategy is verified through time-domain simulations in PSCAD/ EMTDC. The studies in this paper demonstrate the effectiveness of the presented protection scheme for station internal faults occurring in FB-MMCs in bipolar HVDC systems