A review of behind-the-meter solar forecasting

BC Erdener, C Feng, K Doubleday, A Florita… - … and Sustainable Energy …, 2022 - Elsevier
Solar photovoltaic systems largely integrated within the distribution grid are operated
'behind-the-meter'and power generation cannot be directly monitored by most utilities. The …

Behind-the-meter load and pv disaggregation via deep spatiotemporal graph generative sparse coding with capsule network

M Saffari, M Khodayar, ME Khodayar… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
Nowadays, rooftop photovoltaic (PV) panels are getting enormous attention as clean and
sustainable sources of energy due to the increasing energy demand, depreciating physical …

Solar disaggregation: State of the art and open challenges

X Chen, O Ardakanian - Proceedings of the 5th International Workshop …, 2020 - dl.acm.org
Disaggregating solar power from net meter data has got traction in recent years as utility
companies are seeking ways to identify behind-the-meter solar photovoltaics, improve their …

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 …

[HTML][HTML] Probabilistic short-term load forecasting incorporating behind-the-meter (BTM) photovoltaic (PV) generation and battery energy storage systems (BESSs)

JW Cha, SK Joo - Energies, 2021 - mdpi.com
Increased behind-the-meter (BTM) solar generation causes additional errors in short-term
load forecasting. To ensure power grid reliability, it is necessary to consider the influence of …

Construction of Forecast Models based on Bayesian Structural Time Series

I Kalinina, P Bidyuk, A Gozhyj - 2022 IEEE 17th International …, 2022 - ieeexplore.ieee.org
The article discusses the methodology for solving problems of modeling and forecasting
time series using the method of Bayesian structural time series (BSTS). The analysis used …

[PDF][PDF] Modeling and forecasting of nonlinear nonstationary processes based on the Bayesian structural time series

ІО Калініна, ОП Гожий - Прикладні аспекти інформаційних технологій, 2022 - aait.od.ua
The article describes an approach to modelling and forecasting non-linear non-stationary
time series for various purposes using Bayesian structural time series. The concepts of non …

Sparse Attention Graph Gated Recurrent Unit for Spatiotemporal Behind-The-Meter Load and PV Disaggregation

M Khodayar, AF Bavil, M Saffari - 2024 16th International …, 2024 - ieeexplore.ieee.org
The increasing adoption of rooftop photovoltaic (PV) power generation systems in
residential areas necessitates accurate monitoring and disaggregation of behind-the-meter …

Estimating the Output of Behind the Meter Solar Farms by Breaking Irradiance Data into its Diffuse and Direct Components

C Ozatalar, R Ahmad, P Pambuh… - 2023 IEEE PES Grid …, 2023 - ieeexplore.ieee.org
As more behind the meter solar farms are installed onto the power grid, the true load on the
power grid becomes more hidden to the utility because the meters only read the net …

Data Efficient Solar Disaggregation with Behind-the-meter Energy Resources

X Chen - 2022 - era.library.ualberta.ca
Solar photovoltaic (PV) generation is one of the fastest-growing renewable energy sources
worldwide. Almost half of this growth is projected to be behindthe-meter (BTM) installations …