A Comprehensive Review of Behind-the-Meter Distributed Energy Resources Load Forecasting: Models, Challenges, and Emerging Technologies
Behind the meter (BTM) distributed energy resources (DERs), such as photovoltaic (PV)
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …
systems, battery energy storage systems (BESSs), and electric vehicle (EV) charging …
[HTML][HTML] Smart Non-Intrusive Appliance Load-Monitoring System Based on Phase Diagram Analysis
D Stanescu, F Enache, F Popescu - Smart Cities, 2024 - mdpi.com
Much of today's power grid was designed and built using technologies and organizational
principles developed decades ago. The lack of energy resources and classic power …
principles developed decades ago. The lack of energy resources and classic power …
[HTML][HTML] Comparing four machine learning algorithms for household non-intrusive load monitoring
Abstract The combination of Machine Learning (ML), smart energy meters, and availability of
household appliance energy profile data has opened new opportunities for Non-Intrusive …
household appliance energy profile data has opened new opportunities for Non-Intrusive …
FOCCA: Fog-cloud continuum architecture for data imputation and load balancing in Smart Grids
MTM Barbosa, EBC Barros, VFS Mota, DM Leite Filho… - Computer Networks, 2025 - Elsevier
A Smart Grid operates as an advanced electricity network that leverages digital
communications technology to detect and respond to local changes in usage, generation …
communications technology to detect and respond to local changes in usage, generation …
Development of Realtime Co-Simulation Platform Harnessing Consumer Energy Flexibility Through an Aggregator to Provide Grid Support
The integration of renewable energy resources and nearly zero energy buildings (nZEBs)
into the grid requires a balance between demand and supply, which makes energy flexibility …
into the grid requires a balance between demand and supply, which makes energy flexibility …
Disaggregating Household Water End-Uses: A Comparative Study Between XGBoost and TabNet
P Pradeep, W Zhao, M Kowalski… - 2024 6th International …, 2024 - ieeexplore.ieee.org
In a world where water is consumed at an unsustainable level, smart water-saving
approaches could play a fundamental role in managing and preserving this resource. By …
approaches could play a fundamental role in managing and preserving this resource. By …
Analisis Pengaruh Noise pada Performa K-Nearest Neighbors Algorithm dengan Variasi Jarak untuk klasifikasi Beban Listrik
ABSTRAK Teknik Non-Intrusive Load Monitoring (NILM) digunakan dalam pemantauan
konsumsi energi. Variabel pengukuran yang digunakan yaitu Real Power dan Reactive …
konsumsi energi. Variabel pengukuran yang digunakan yaitu Real Power dan Reactive …
Comparative Analysis of Machine Learning Techniques for Indoor Illuminance Prediction and Building Energy Efficiency: Innovative Approaches for Efficient Daylight …
B Sharif, M Bonomolo, A Biondi, V Di Dio… - Available at SSRN … - papers.ssrn.com
Artificial lighting systems have to meet technical standards and best design practices to
guarantee the right amount of lighting at a high energy efficiency. One way to accomplish …
guarantee the right amount of lighting at a high energy efficiency. One way to accomplish …