Electric energy disaggregation via non-intrusive load monitoring: A state-of-the-art systematic review

S Dash, NC Sahoo - Electric Power Systems Research, 2022 - Elsevier
Appliance energy consumption tracking in a building is one of the vital enablers of energy
and cost saving. An economical and viable solution would be to estimate individual …

Smart solutions shape for sustainable low-carbon future: A review on smart cities and industrial parks in China

Y Wang, H Ren, L Dong, HS Park, Y Zhang… - … Forecasting and Social …, 2019 - Elsevier
To promote sustainable urban development and green industrial process are critical
solutions for sustainable and low-carbon society transition in China, considering the …

Non-intrusive load disaggregation using graph signal processing

K He, L Stankovic, J Liao… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
With the large-scale roll-out of smart metering worldwide, there is a growing need to account
for the individual contribution of appliances to the load demand. In this paper, we design a …

Energy sustainability in smart cities: Artificial intelligence, smart monitoring, and optimization of energy consumption

KT Chui, MD Lytras, A Visvizi - Energies, 2018 - mdpi.com
Energy sustainability is one of the key questions that drive the debate on cities' and urban
areas development. In parallel, artificial intelligence and cognitive computing have emerged …

On a training-less solution for non-intrusive appliance load monitoring using graph signal processing

B Zhao, L Stankovic, V Stankovic - IEEE Access, 2016 - ieeexplore.ieee.org
With ongoing large-scale smart energy metering deployments worldwide, disaggregation of
a household's total energy consumption down to individual appliances using analytical …

[HTML][HTML] Non-intrusive load decomposition based on CNN–LSTM hybrid deep learning model

X Zhou, J Feng, Y Li - Energy Reports, 2021 - Elsevier
With the rapid development of science and technology, the problem of energy load
monitoring and decomposition of electrical equipment has been receiving widespread …

A hybrid signature-based iterative disaggregation algorithm for non-intrusive load monitoring

A Cominola, M Giuliani, D Piga, A Castelletti… - Applied energy, 2017 - Elsevier
Abstract Information on residential power consumption patterns disaggregated at the single-
appliance level is an essential requirement for energy utilities and managers to design …

A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing

D Tan, M Suvarna, YS Tan, J Li, X Wang - Applied Energy, 2021 - Elsevier
The dynamic nature of chemical processes and manufacturing environments, along with
numerous machines, their unique activity states, and mutual interactions, render challenges …

An overview of non-intrusive load monitoring: Approaches, business applications, and challenges

M Zhuang, M Shahidehpour, Z Li - … international conference on …, 2018 - ieeexplore.ieee.org
Load Monitoring (LM) is a fundamental step to implement effective energy management
schemes. LM includes Intrusive LM (ILM) and Non-Intrusive LM (NILM). Compared with …

A non-intrusive carbon emission accounting method for industrial corporations from the perspective of modern power systems

C Yang, G Liang, J Liu, G Liu, H Yang, J Zhao, Z Dong - Applied Energy, 2023 - Elsevier
Accurate and timely carbon emission accounting (CEA) is vital to industrial corporations,
especially those who participate in the carbon market. With the rapid development of …