Cloud computing and IoT based intelligent monitoring system for photovoltaic plants using machine learning techniques

M Emamian, A Eskandari, M Aghaei, A Nedaei… - Energies, 2022 - mdpi.com
This paper proposes an Intelligent Monitoring System (IMS) for Photovoltaic (PV) systems
using affordable and cost-efficient hardware and also lightweight software that is capable of …

A taxonomy of short‐term solar power forecasting: Classifications focused on climatic conditions and input data

IK Bazionis, MA Kousounadis‐Knousen… - IET Renewable …, 2023 - Wiley Online Library
A review of the state‐of‐the‐art in short‐term Solar Power Forecasting (SPF) methodologies
is presented in this paper. Over the last few years, developing and improving solar …

Autonomous monitoring and analysis of photovoltaic systems

M Aghaei - Energies, 2022 - mdpi.com
At the beginning of 2022, photovoltaic (PV) installation exceeded 1 TWp which was an
impressive milestone in the solar energy industry. In 2021, at least 183 GW was installed …

A meta-modeling power consumption forecasting approach combining client similarity and causality

D Kontogiannis, D Bargiotas, A Daskalopulu… - Energies, 2021 - mdpi.com
Power forecasting models offer valuable insights on the electricity consumption patterns of
clients, enabling the development of advanced strategies and applications aimed at energy …

[PDF][PDF] Autonomous Monitoring and Analysis of Photovoltaic Systems. Energies 2022, 15, 5011

M Aghaei - 2022 - researchgate.net
At the beginning of 2022, photovoltaic (PV) installation exceeded 1 TWp which was an
impressive milestone in the solar energy industry. In 2021, at least 183 GW was installed …

Cloud Computing and IoT Based Intelligent Monitoring System for Photovoltaic Plants Using Machine Learning Techniques

M Aghaei - 2022 - ntnuopen.ntnu.no
This paper proposes an Intelligent Monitoring System (IMS) for Photovoltaic (PV) systems
using affordable and cost-efficient hardware and also lightweight software that is capable of …