[HTML][HTML] Photovoltaic power estimation and forecast models integrating physics and machine learning: A review on hybrid techniques

L de Oliveira Santos, T AlSkaif, GC Barroso… - Solar Energy, 2024 - Elsevier
Photovoltaic (PV) models are essential for energy planning and grid integration applications.
The models used for PV power conversion typically adopt physical, data-driven, or hybrid …

An adaptive interval power forecasting method for photovoltaic plant and its optimization

M Ma, B He, R Shen, Y Wang, N Wang - Sustainable Energy Technologies …, 2022 - Elsevier
With the high photovoltaic (PV) access ratio, high precision PV power prediction is of great
significance for the large-scale PV plants. The existing deterministic prediction methods are …

[HTML][HTML] MAS-DR: An ML-Based Aggregation and Segmentation Framework for Residential Consumption Users to Assist DR Programs

P Tzallas, A Papaioannou, A Dimara, N Bezas… - Sustainability, 2025 - mdpi.com
The increasing complexity of energy grids, driven by rising demand and unpredictable
residential consumption, highlights the need for efficient demand response (DR) strategies …

[HTML][HTML] Optimems: An adaptive lightweight optimal microgrid energy management system based on the novel virtual distributed energy resources in real-life …

AD Bintoudi, L Zyglakis, AC Tsolakis, PA Gkaidatzis… - Energies, 2021 - mdpi.com
As microgrids have gained increasing attention over the last decade, more and more
applications have emerged, ranging from islanded remote infrastructures to active building …

[PDF][PDF] Solar Generation Forecasting with Transfer Learning

D Mylonas - 2023 - ikee.lib.auth.gr
Περίληψη Η ενέργεια αποτελεί αναπόσπαστο κομμάτι της ανθρώπινης κοινωνίας εδώ και
πολλούς αιώνες και η αξιοποίηση της έπαιξε καθοριστικό ρόλο στην επιβίωση και την εξέλιξη …