A5101860008- Energy Load and Power Forecasting
- Electric Vehicles and Infrastructure
- Environmental Impact and Sustainability
- Smart Grid Energy Management
- Image and Signal Denoising Methods
- Air Quality Monitoring and Forecasting
- Supercapacitor Materials and Fabrication
- Electric Power System Optimization
- Solar Radiation and Photovoltaics
- Advanced Battery Technologies Research
- Green IT and Sustainability
- Smart Grid and Power Systems
- Thermal Analysis in Power Transmission
- Advancements in Battery Materials
- Integrated Energy Systems Optimization
- Advanced Battery Materials and Technologies
- Energy Efficiency and Management
- Recycled Aggregate Concrete Performance
- Impact of Light on Environment and Health
- Big Data Technologies and Applications
- Microgrid Control and Optimization
- Risk and Safety Analysis
- Advanced Chemical Sensor Technologies
- Polymer composites and self-healing
- Wind Energy Research and Development
Wenzhou University
2025
Chinese University of Hong Kong, Shenzhen
2019-2024
China Tobacco
2024
Durham University
2024
Shenzhen Research Institute of Big Data
2022-2023
Shenzhen Academy of Robotics
2022-2023
Tsinghua University
2022
Qingdao University of Technology
2021
Nanchang University
2020
North China Electric Power University
2017
Achieving carbon neutrality is widely recognized as the key measure to mitigate climate change. As basis for achieving neutrality, corporate footprint (CCF) estimation mainly based on disclosed information of corporates roughly estimate direct emission, but may not be comprehensive, timely, and accurate. In this article, CCF problem formulated a novel methodology proposed first time indirect emissions factories in real time. An appliance identification method multihead self-attention...
Nowadays, with the wide installation of distributed energy resources and independent storage systems, prosumers as a new type electricity market entity have emerged. Since numerous can significantly impact carbon emission power grid, this paper proposes an improved flow method for grid prosumers. This accurately clarify detailed distribution electrical in grids. First, based on flow, prosumers' impacts are quantified from three aspects that include sources, network indirect individuals....
Abstract The real‐time carbon emission estimation of generators helps quantify the costs and reduce power system emissions generation. Accurate relies on accuracy factors (EFs) generation measurements. dynamic factor (DEF) was proposed recently as a linear function output power. However, there is significant deviation between modelled DEFs actual measurement EFs, especially when low. This paper first presents general definition DEF to characterize focuses unit‐level (UDEF). piecewise...
Abstract Cities in China are on the frontline of low-carbon transition which requires monitoring city-level emissions with low-latency to support timely climate actions. Most existing CO 2 emission inventories lag reality by more than one year and only provide annual totals. To improve timeliness temporal resolution inventories, we present Carbon Monitor Cities-China (CMCC), a near-real-time dataset daily from fossil fuel cement production for 48 major high-emission cities China. This...
Cement stabilized macadam base has high strength and excellent bearing capacity, but the problems of water-temperature sensitivity, easy shrinkage cracking large demand for aggregate limit further development application cement base. At same time, with economy development, increase solid waste, such as waste tires construction caused great pressure on ecological environment. In order to ensure better mechanical properties resistance basis full use waste. this paper, tests unconfined...
Estimating the product carbon footprint (PCF) is crucial for sustainable consumption and supply chain decar-bonlization. The current life cycle assessment (LCA) methods frequently employed to evaluate PCFs often en-counter challenges, such as difficulties in determining emission inventory factors (EFs), well significant labor time costs. To address these limitations, this paper presents AutoPCF, a novel auto-matic PCF estimation framework conduct cradle-to-gate LCA products. It utilizes deep...
Abstract Load forecasting is crucial for the economic and secure operation of power systems. Extreme weather events, such as extreme heat typhoons, can lead to more significant fluctuations in consumption, making load difficult. At present, due lack relevant public data, research on under events still blank, so it necessary release a large-scale dataset containing events. The includes electricity consumption data industrial commercial users typhoons heat, which are collected at 15-minute...
In recent years, extreme weather disasters have occurred frequently, so reducing greenhouse gas emissions is an urgent task. How to accurately estimate corporate carbon in real-time directly affects this Therefore, a estimation framework of based on load identification proposed paper. the framework, total emission consists two parts: direct and indirect emission. First, Convolutional Neural Network - Bidirectional Long Short-Term Memory (CNN-BLSTM) model presented employed monitor states...
The product carbon footprint (PCF) is crucial for decarbonizing the supply chain, as it measures direct and indirect greenhouse gas emissions caused by all activities during product's life cycle. However, PCF accounting often requires expert knowledge significant time to construct cycle models. In this study, we test compare emergent ability of five large language models (LLMs) in modeling 'cradle-to-gate' cycles products generating inventory data inputs outputs, revealing their limitations...
As an important part of renewable energy, wind power is crucial to the realization carbon neutrality. It worth studying on how accurately predict output so that it can be integrated into grid as much possible enhance its utilization rate. In this article, a data enhancement method and framework are proposed assist forecasting. The uses super-resolution perception technology first detect completeness correctness historical meteorological collected by industrial devices. Then, detected errors...
In order to reduce the negative volume effect of Silicon (Si) and Silica (SiO[Formula: see text] as anode materials, CNTs@SiO 2 /Si@C is prepared by sol–gel method magnesiothermic reduction process. SEM TEM results show that surface Carbon nanotubes (CNTs) uniformly coated with active materials including SiO Si. Active (SiO /Si) closely contact conductive network constructed CNTs, which greatly improves conductivity composite material. Moreover, large specific area tubular structure provides...
Identifying industrial appliances can assist in demand-side management smart grids. In this paper, a temporal convolutional neural network with attention mechanism based method is proposed for non-intrusive load monitoring (NILM). First, the sequence segmented into fixed length subsequences, and ON-OFF states of are also recorded simultaneously. Then, some subsequences used as input method, corresponding classifiers different trained by using together appliance states. Finally, to classify...
As it pertains to the institutional perspective, central-local fiscal interest conflict implies between central control and provincial autonomy.The term autonomy means authority, independence, influence that government has in operation of tax system utilization financial resources.The authority monitoring utilization.The experiences two levels development.At first level, desires improve collection efforts retain as much revenues possible for
Machine learning models deployed on edge devices have enabled numerous exciting new applications, such as humanoid robots, AR glasses, and autonomous vehicles. However, the computing resources available these are not catching up with ever-growing number of parameters in models. As become bigger more complicated, novel yet sophisticated structure challenges inference runtime optimization. We present FluidML, a generic memory management optimization framework that can flexibly transform model...
In this paper, an optimal planning model of battery energy storage systems (BESS) in radial distribution networks is proposed to regulate bus voltage and reduce cost. The number, locations capacity for BESS obtained by a hierarchical model. firstly determines the number. Then most effective can be selected based on sensitivity analysis. Given number location, determined constrained mixed-integer nonlinear programming problem solved natural aggregation algorithm (NAA). final configuration...