A5110951271- Astronomy and Astrophysical Research
- Stellar, planetary, and galactic studies
- Smart Grid Energy Management
- Electric Vehicles and Infrastructure
- Forecasting Techniques and Applications
- Stock Market Forecasting Methods
- Transportation and Mobility Innovations
- Metamaterials and Metasurfaces Applications
- Integrated Energy Systems Optimization
- Hybrid Renewable Energy Systems
- Underwater Acoustics Research
- Astronomical Observations and Instrumentation
- Acoustic Wave Resonator Technologies
- Geophysics and Gravity Measurements
- Wireless Signal Modulation Classification
- Photonic Crystals and Applications
- Digital Platforms and Economics
- Energy Load and Power Forecasting
- Blind Source Separation Techniques
- Microgrid Control and Optimization
Nankai University
2024
Institute of Physics
2024
Chinese Academy of Sciences
2024
University of Chinese Academy of Sciences
2024
Tsinghua–Berkeley Shenzhen Institute
2022-2024
Tsinghua University
2021-2024
Sichuan University
2023
Tsinghua University-Ma Huateng Telescopes for Survey (TMTS), located at Xinglong Station of NAOC, has a field view upto 18 deg^2. The TMTS started to monitor the LAMOST sky areas since 2020, with uninterrupted observations lasting about 6 hours on average each area and cadence 1 minute. Here we introduce data analysis preliminary scientific results first-year observations, which covered 188 plates ( 1970 deg^2). These have generated over 4.9 million light curves, least 100 epochs them....
Abstract Nonlinear optical (NLO) van der Waals (vdW) crystals containing 1D building blocks exhibit large NLO coefficients and birefringence that are crucial for their applications. In this work, 21 with second harmonic generation (SHG) susceptibility from the Computational Materials Database (C1DB) screened. Among them, 14 hitherto unreported have SHG susceptibilities approaching theoretical upper limits. Forty‐five new vdW then constructed by stacking one or two of blocks. Eighteen them...
Abstract Determining the number of sources under low signal-to-noise ratio (SNR) and signal interference with same frequency modulation presents a significant challenge. To address this challenge, we propose novel method for detecting from single-channel that leverages reconstruction deep learning. The employs subspace projection based on Hankel matrix to reconstruct measured signals, effectively suppressing noise. Furthermore, incorporate correlation information integrity feature in signal,...
To minimize total operation cost considering carbon emission, the energy management problem of a micro-grid is formulated by scheduling conventional generators (CGs), storage systems (ESSs) and power trading with main grid. It proposed in this paper to convert Markov Decision Process (MDP) solve it soft actor-critic (SAC), cutting-edge deep reinforcement learning (DRL) algorithm. The agent able capture uncertainty load renewable generation (RG) from large volumes historical data training...
Abstract Blue large-amplitude pulsators (BLAPs) represent a new and rare class of hot pulsating stars with unusually large amplitudes short periods. Up to now, only 21 confirmed BLAPs have been identified from more than one billion monitored stars, including group pulsation period longer 20 min (classical BLAPs; [1]) the other below 10 (high-gravity [2]). The evolutionary path that could give rise such kinds stellar configurations is unclear. Here we report on comprehensive study peculiar...
The power and gas sectors must take the responsibility to pave way reduce their carbon emissions realize commitment of peak neutrality. developing power-to-gas turbines tighten relationship between networks. So this paper proposes carbon-aware integrated energy system optimization model with demand response. It formulates DC flow-based network, piecewise-based transmission hub, response model. Based on models, presents model, which analyzes emission from generators hubs utilizes quota-based...