Deep learning-based fault diagnosis of photovoltaic systems: A comprehensive review and enhancement prospects

M Mansouri, M Trabelsi, H Nounou, M Nounou - IEEE Access, 2021 - ieeexplore.ieee.org
Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …

A review of machine learning-based photovoltaic output power forecasting: Nordic context

BD Dimd, S Völler, U Cali, OM Midtgård - IEEE Access, 2022 - ieeexplore.ieee.org
Motivated by factors such as the reduction in cost and the need for a shift towards achieving
UN's Sustainable Development Goals, PV (Photovoltaic) power generation is getting more …

Hydrogen energy storage systems to improve wind power plant efficiency considering electricity tariff dynamics

NG Kiryanova, PV Matrenin, SV Mitrofanov… - International Journal of …, 2022 - Elsevier
One of the limitations of the efficiency of renewable energy sources is the stochastic nature
of generation; consequently, it is necessary to use high-capacity energy storage systems …

Ultra-short-term photovoltaic power prediction based on similar day clustering and temporal convolutional network with bidirectional long short-term memory model: A …

M Zhang, Y Han, C Wang, P Yang, C Wang, AS Zalhaf - Applied Energy, 2024 - Elsevier
Due to its strong dependence on weather conditions, photovoltaic (PV) power is highly
intermittent in nature. In light of this, this paper introduces a PV power prediction model …

Prediction of Solar Energy Yield Based on Artificial Intelligence Techniques for the Ha'il Region, Saudi Arabia

L Kolsi, S Al-Dahidi, S Kamel, W Aich, S Boubaker… - Sustainability, 2022 - mdpi.com
In order to satisfy increasing energy demand and mitigate global warming worldwide, the
implementation of photovoltaic (PV) clean energy installations needs to become common …

Solar Irradiance Forecasting with Natural Language Processing of Cloud Observations and Interpretation of Results with Modified Shapley Additive Explanations

PV Matrenin, VV Gamaley, AI Khalyasmaa… - Algorithms, 2024 - mdpi.com
Forecasting the generation of solar power plants (SPPs) requires taking into account
meteorological parameters that influence the difference between the solar irradiance at the …

Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on k-Means and k-Nearest Neighbors Algorithms

PV Matrenin, AI Khalyasmaa, VV Gamaley… - 2023 - elar.urfu.ru
Renewable energy sources (RES) are seen as a means of the fuel and energy complex
carbon footprint reduction but the stochastic nature of generation complicates RES …

Averaged errors as a risk factor for intelligent forecasting systems operation in the power industry

A Khalyasmaa, P Matrenin… - 2021 Ural-Siberian …, 2021 - ieeexplore.ieee.org
The paper discusses the operational risk in intelligent systems for forecasting time series.
Typically, when developing and testing regression models based on machine learning, their …

[HTML][HTML] Исследование ансамблевых и нейросетевых методов машинного обучения в задаче краткосрочного прогнозирования электропотребления горных …

ДВ Антоненков, ПВ Матренин - Электротехнические системы и …, 2021 - cyberleninka.ru
В статье рассмотрена проблема прогнозирования электропотребления горных
предприятий, особенностью которого является высокий уровень нестационарности и …

Machine learning-based intelligent weather modification forecast in smart city potential area

Z Chao - Computer Science and Information Systems, 2023 - doiserbia.nb.rs
It is necessary to improve the efficiency of meteorological service monitoring in smart cities
and refine the prediction of extreme weather in smart cities continuously. Firstly, this paper …