Optimal scheduling for charging and discharging of electric vehicles based on deep reinforcement learning

The growing scale of electric vehicles (EVs) brings continuous challenges to the energy trading market. In the process of grid-connected charging of EVs, disorderly charging behavior of a large number of EVs will have a substantial impact on the grid load. Aiming to solve the problem of optimal scheduling for charging and discharging of EVs, this paper first establishes a model for the charging and discharging scheduling of EVs involving the grid, charging equipment, and EVs. Then, the established scheduling model is described as a partially observable Markov decision process (POMDP) in the multi-agent environment. This paper proposes an optimization objective that comprehensively considers various factors such as the cost of charging and discharging EVs, grid load stability, and user usage requirements. Finally, this paper introduces the long short-term memory enhanced multi-agent deep deterministic policy gra dient (LEMADDPG) algorithm to obtain the optimal scheduling strategy of EVs. Simulation results prove that the proposed LEMADDPG algorithm can obtain the fastest convergence speed, the smallest fluctuation and the highest cumulative reward compared with traditional deep deterministic policy gradient and DQN algorithms

Prediction and Diagnosis for Unsteady Electromagnetic Vibroacoustic of IPMSMs for Electric Vehicles Considering Rotor Step Skewing and Current Harmonics

Purpose: This study provides a detailed investigation on the prediction and diagnosis of unsteady electromagnetic vibroacoustic performance of IPMSMs for electric vehicles under typical unsteady operating conditions with consideration of rotor step skewing and current harmonics. Methods: Firstly, the control model considering the influence of PWM carrier modulation and rotor step skewing is established. Based on this, the currents of the IPMSM under unsteady operating conditions (driving condition and feedback braking condition) are obtained. Accordingly, the currents calculated through the control model are used as the excitation source of electromagnetic finite element. Then, the electromagnetic vibroacoustic performance under unsteady operating conditions is calculated through electromagnetic force subsection mapping and acoustic transfer vector (ATV) method. Moreover, the conditions where resonance vibroacoustic occurs are diagnosed. Finally, the results of prediction and diagnosis are fully verified by experiments of multiple physical fields. Results and Conclusions: The amplitude errors between prediction results and test results are less than 3.2%. The influence of current harmonics on electromagnetic vibroacoustic can be predicted. The frequency range and speed range of predicted peak vibroacoustic are consistent with the experimental results. The rotor step skewing can be used to weaken the vibroacoustic amplitude of IPMSMs under typical unsteady conditions in the full speed range. This study provides guidance for prediction and diagnosis for electromagnetic vibroacoustic performance of IPMSMs under typical unsteady operating conditions.</p

Prediction and Diagnosis for Unsteady Electromagnetic Vibroacoustic of IPMSMs for Electric Vehicles Considering Rotor Step Skewing and Current Harmonics

Purpose: This study provides a detailed investigation on the prediction and diagnosis of unsteady electromagnetic vibroacoustic performance of IPMSMs for electric vehicles under typical unsteady operating conditions with consideration of rotor step skewing and current harmonics. Methods: Firstly, the control model considering the influence of PWM carrier modulation and rotor step skewing is established. Based on this, the currents of the IPMSM under unsteady operating conditions (driving condition and feedback braking condition) are obtained. Accordingly, the currents calculated through the control model are used as the excitation source of electromagnetic finite element. Then, the electromagnetic vibroacoustic performance under unsteady operating conditions is calculated through electromagnetic force subsection mapping and acoustic transfer vector (ATV) method. Moreover, the conditions where resonance vibroacoustic occurs are diagnosed. Finally, the results of prediction and diagnosis are fully verified by experiments of multiple physical fields. Results and Conclusions: The amplitude errors between prediction results and test results are less than 3.2%. The influence of current harmonics on electromagnetic vibroacoustic can be predicted. The frequency range and speed range of predicted peak vibroacoustic are consistent with the experimental results. The rotor step skewing can be used to weaken the vibroacoustic amplitude of IPMSMs under typical unsteady conditions in the full speed range. This study provides guidance for prediction and diagnosis for electromagnetic vibroacoustic performance of IPMSMs under typical unsteady operating conditions.</p

Domestication syndrome is investigated by proteomic analysis between cultivated cassava (Manihot esculenta Crantz) and its wild relatives

Cassava (Manihot esculenta Crantz) wild relatives remain a largely untapped potential for genetic improvement. However, the domestication syndrome phenomena from wild species to cultivated cassava remain poorly understood. The analysis of leaf anatomy and photosynthetic activity showed significantly different between cassava cultivars SC205, SC8 and wild relative M. esculenta ssp. Flabellifolia (W14). The dry matter, starch and amylose contents in the storage roots of cassava cultivars were significantly more than that in wild species. In order to further reveal the differences in photosynthesis and starch accumulation of cultivars and wild species, the globally differential proteins between cassava SC205, SC8 and W14 were analyzed using 2-DE in combination with MALDI-TOF tandem mass spectrometry. A total of 175 and 304 proteins in leaves and storage roots were identified, respectively. Of these, 122 and 127 common proteins in leaves and storage roots were detected in SC205, SC8 and W14, respectively. There were 11, 2 and 2 unique proteins in leaves, as well as 58, 9 and 12 unique proteins in storage roots for W14, SC205 and SC8, respectively, indicating proteomic changes in leaves and storage roots between cultivated cassava and its wild relatives. These proteins and their differential regulation across plants of contrasting leaf morphology, leaf anatomy pattern and photosynthetic related parameters and starch content could contribute to the footprinting of cassava domestication syndrome. We conclude that these global protein data would be of great value to detect the key gene groups related to cassava selection in the domestication syndrome phenomena

Cassava genome from a wild ancestor to cultivated varieties

Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology

Multi-messenger searches via IceCube’s high-energy neutrinos and gravitational-wave detections of LIGO/Virgo

We summarize initial results for high-energy neutrino counterpart searches coinciding with gravitational-wave events in LIGO/Virgo\u27s GWTC-2 catalog using IceCube\u27s neutrino triggers. We did not find any statistically significant high-energy neutrino counterpart and derived upper limits on the time-integrated neutrino emission on Earth as well as the isotropic equivalent energy emitted in high-energy neutrinos for each event