A novel method for assessment rooftop PV potential based on remote sensing images

J Yang, J Wu, J Lu, X Peng, H Yuan, LL Lai - Renewable Energy, 2024 - Elsevier
The assessment of rooftop photovoltaic (PV) potential is highly significant for energy policy
formulation. With the rapid development of computer vision (CV) and remote sensing …

Self-supervised learning method for consumer-level behind-the-meter PV estimation

CC Liu, H Chen, J Shi, L Chen - Applied Energy, 2022 - Elsevier
Driven by cost reduction and sustainable policies, the penetration of distributed photovoltaic
(PV) systems has deepened in recent years. Most of these PV systems are installed behind …

A Comprehensive Review of Behind-the-Meter Distributed Energy Resources Load Forecasting: Models, Challenges, and Emerging Technologies

A Zaboli, SR Kasimalla, K Park, Y Hong, J Hong - Energies, 2024 - mdpi.com
Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV)
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …

[HTML][HTML] Quantifying spatio-temporal carbon intensity within a city using large-scale smart meter data: Unveiling the impact of behind-the-meter generation

S Sugano, Y Fujimoto, Y Ihara, M Mitsuoka, S Tanabe… - Applied Energy, 2025 - Elsevier
This study introduces a novel method for calculating spatio-temporal carbon intensity
variations within a city using smart meter data. By integrating smart meter data with solar …

Innovative liquid cooling channel enhanced battery thermal management (BTM) structure based on stepwise optimization method

C Wu, X Yuan, B Kong, Y Zou, H Shi - Journal of Energy Storage, 2024 - Elsevier
Lithium-ion batteries have garnered significant attention in the field of new energy
technology due to their impressive high energy density characteristics. The lightweight and …

Unsupervised disaggregation of aggregated net load considering behind-the-meter PV based on virtual PV sample construction

Z Qu, X Ge, J Lu, F Wang - Applied Energy, 2025 - Elsevier
Most of the distributed photovoltaics (PV) are installed behind the meter (BTM), single-meter
deployments permit distribution system operators to monitor only the net load and exclude …

A Deep Learning Framework for Net Load Forecasting With Unsupervised Behind-The-Meter Disaggregated Data

C Thepprom, N Nupairoj, P Vateekul - IEEE Access, 2024 - ieeexplore.ieee.org
Recently, distributed photovoltaic (PV) generation has increased significantly, leading to a
high penetration of behind-the-meter (BTM) solar generation systems. In this work, we aim to …

Deep recurrent extreme learning machine for behind-the-meter photovoltaic disaggregation

M Saffari, M Khodayar, ME Khodayar - The Electricity Journal, 2022 - Elsevier
In recent years, sustainable sources of energies attract significant interest due to the serious
environmental issues of fossil fuels. Rooftop photovoltaic (PV) panels are among the …

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

R Hossain, M Gautam, J Olowolaju, H Livani… - Electric Power Systems …, 2024 - Elsevier
Active distribution grids can experience voltage fluctuations and violations due to the high
penetration of variable distributed energy resources (DERs). These problems might occur …

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles With High Penetration of Behind-the-Meter Solar

Z Zhao, D Moscovitz, S Wang, L Du… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
The ever-growing integration of distributed energy resources (DERs), especially behind-the-
meter (BTM) solar generations, poses imperative operational challenges to system …