Applications of synthetic biotechnology on carbon neutrality research: a review on electrically driven microbial and enzyme engineering

X Zhuang, Y Zhang, AF Xiao, A Zhang… - … in Bioengineering and …, 2022 - frontiersin.org
With the advancement of science, technology, and productivity, the rapid development of
industrial production, transportation, and the exploitation of fossil fuels has gradually led to …

Operational signature-based symbolic hierarchical clustering for building energy, operation, and efficiency towards carbon neutrality

Y Hong, S Yoon, S Choi - Energy, 2023 - Elsevier
Buildings are considered the enormous source of untapped energy efficiency potential in the
global carbon neutrality. It is necessary to ensure that buildings are energy-efficient using …

[HTML][HTML] A machine learning-based detection framework against intermittent electricity theft attack

H Fang, JW Xiao, YW Wang - International Journal of Electrical Power & …, 2023 - Elsevier
The widespread installation of advanced metering infrastructure (AMI) brings convenience to
applications including but not limited to load management and demand response. However …

[HTML][HTML] A new deep clustering method with application to customer selection for demand response program

JW Xiao, Y Xie, H Fang, YW Wang - … Journal of Electrical Power & Energy …, 2023 - Elsevier
Demand response (DR) is regarded as a promising solution to the problem of renewable
energy integration, while it remains one of the key barriers for DR to target the right …

Industrial park electric power load pattern recognition: An ensemble clustering-based framework

K Zhou, N Peng, D Hu, Z Shao - Energy and Buildings, 2023 - Elsevier
Electric power load pattern recognition from various accumulated load data is performed for
energy efficiency improvement, power system operation support, and demand side …

A method for analyzing the irrepazrability of diverse electricity consumption data based on improved data generation technology

Y Ma, X Kong, L Zhao, G Liu, B Gao - Applied Energy, 2024 - Elsevier
The quality of electricity consumption data significantly influences business model
construction, affecting performance and accuracy. This paper proposes a method for …

Self-training convolutional autoencoder for consumer characteristics identification with imbalance datasets

H Fang, JW Xiao, YW Wang - Engineering Applications of Artificial …, 2023 - Elsevier
Consumer characteristics can help energy utilities implement efficient demand response
programs and personalized services. However, there are two problems in obtaining …

Urban Mobility and Knowledge Extraction from Chaotic Time Series Data: A Comparative Analysis for Uncovering COVID-19 Effects

G You - Annals of the American Association of Geographers, 2023 - Taylor & Francis
The COVID-19 pandemic exerted devastating effects on the global economy, public health,
and urban life. The geographical consequences lie in spatial time series dimensions, but the …

A New Binary Encoding Method for Energy Consumption Patterns Quantification

H Fang, JW Xiao, YW Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Extracting users' energy consumption patterns (ECPs) from smart meter data is an important
work for retailers. The existing literature usually describe these patterns by clustering the …

A Novel Aggregated Short-Term Load Forecasting Method Based on Clustering

Z Yao, H Fang, S Cui, M Cai, F Ai, J Li… - 2023 35th Chinese …, 2023 - ieeexplore.ieee.org
Household short-term load forecasting is one of the essential work of electricity utilities,
which is of great significance to the construction of smart grids and the safe operation of …