A generalized flow for B2B sales predictive modeling: An azure machine-learning approach

A Rezazadeh - Forecasting, 2020 - mdpi.com
Predicting the outcome of sales opportunities is a core part of successful business
management. Conventionally, undertaking this prediction has relied mostly on subjective …

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 …

Distribution system state estimation using PV separation strategy in LV feeders with high levels of unmonitored PV generation

A Mokaribolhassan, G Nourbakhsh… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Distribution system state estimation (DSSE) is a critical analysis tool for active distribution
networks (DNs). Unlike weighted least squares techniques, which are static DSSE methods …

A novel data-driven method for behind-the-meter solar generation disaggregation with cross-iteration refinement

K Pan, Z Chen, CS Lai, C **e, D Wang… - … on Smart Grid, 2022 - ieeexplore.ieee.org
Photovoltaic (PV) generation is increasing in distribution systems following policies and
incentives to promote zero-carbon emission societies. Most residential PV systems are …

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 data-driven democratized control architecture for regional transmission operators

X Fan, D Moscovitz, L Du… - 2022 IEEE Power & Energy …, 2022 - ieeexplore.ieee.org
As probably the most complicated and critical infrastructure system, US power grids become
increasingly vulnerable to extreme events such as cyber-attacks and severe weather, as …

Photovoltaic output power estimation and baseline prediction approach for a residential distribution network with behind-the-meter systems

K Pan, C **e, CS Lai, D Wang, LL Lai - Forecasting, 2020 - mdpi.com
Considering that most of the photovoltaic (PV) data are behind-the-meter (BTM), there is a
great challenge to implement effective demand response projects and make a precise …

Data efficient energy disaggregation with behind-the-meter energy resources

X Chen, O Ardakanian - Sustainable Energy, Grids and Networks, 2022 - Elsevier
The deployment of behind-the-meter energy resources is set to increase in the next decade.
Yet, utilities are not ready to safely manage these resources owing to the lack of visibility into …

A novel non-intrusive framework for real-time disaggregation of behind-the-meter solar generation from smart meter data

HM Usman, R ElShatshat, AH El-Hag - Electric Power Systems Research, 2023 - Elsevier
As the number of behind-the-meter (BTM) photovoltaic (PV) modules installed in residential
premises increases, it is important to develop a non-intrusive framework for the real-time …

Behind-the-Meter Solar Generation Disaggregation at Varying Aggregation Levels Using Consumer Mixture Models

CM Cheung, SR Kuppannagari… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The increasing penetration of solar PhotoVoltaic (PV) panels in residential markets is
leading to increasing solar generation hidden behind metering instruments of utility …