A review on machine learning applications for solar plants

E Engel, N Engel - Sensors, 2022 - mdpi.com
A solar plant system has complex nonlinear dynamics with uncertainties due to variations in
system parameters and insolation. Thereby, it is difficult to approximate these complex …

A machine learning approach for solar power technology review and patent evolution analysis

AJC Trappey, PPJ Chen, CV Trappey, L Ma - Applied Sciences, 2019 - mdpi.com
Solar power systems and their related technologies have developed into a globally utilized
green energy source. Given the relatively high installation costs, low conversion rates and …

Design and operation of hybrid ground source heat pump systems: A review

JL Wang, T Yan, X Tang, WG Pan - Energy, 2025 - Elsevier
Ground source heat pump (GSHP) technology as an efficient and environmentally friendly
solution for heating and cooling systems has gained widespread attention. However, issues …

Distributed online energy management in interconnected microgrids

H Zou, Y Wang, S Mao, F Zhang… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
In this article, a hierarchical online distributed algorithm (HODA) is developed to achieve
optimal energy management in interconnected microgrids (IMG). The energy management …

[HTML][HTML] Predicting Energy Production in Renewable Energy Power Plants Using Deep Learning

A Karakan - Energies, 2024 - mdpi.com
It is very important to analyze and forecast energy production for investments in renewable
energy resources. In this study, the energy production of wind and solar power plants, which …

Методы машинного обучения для задач прогнозирования и максимизации выработки электроэнергии солнечной электростанции

ЕА Энгель, НЕ Энгель - Вестник ВГУ. Серия: Системный анализ и …, 2023 - journals.vsu.ru
Системы прогнозирования и максимизации выработки электроэнергии солнечной
электростанции на основе методов машинного обучения повышают эффективность …

Model‐agnostic online forecasting for PV power output

HY Lee, JG Lee, NW Kim, BT Lee - IET Renewable Power …, 2021 - Wiley Online Library
A reliable forecasting model is required for photovoltaic (PV) power output because solar
energy is highly volatile. Another driver for the need of a reliable forecasting model is …

[HTML][HTML] Система непрямого прогнозирования вырабатываемой электроэнергии массивом солнечных панелей на основе модифицированной нечеткой …

ЕА Энгель, НЕ Энгель - Журнал Сибирского федерального …, 2023 - cyberleninka.ru
Интеллектуальные системы прогнозирования вырабатываемой электроэнергии
массивом солнечных панелей повышают эффективность солнечной электростанции и …

A hybrid energy-saving prediction model based on SSA-DNN for district heating system

M Gong, J Sun, Y Zhao, C Han, B Yan… - Advances in Building …, 2023 - Taylor & Francis
Accurate heat load prediction is a prerequisite for feed-forward control and on-demand heat
supply in district heating system. However, considering that the experimental data used to …