Artificial intelligent control of energy management PV system

Renewable energy systems, such as photovoltaic (PV) systems, have become increasingly significant in response to the pressing concerns of climate change and the imperative to mitigate carbon emissions. When static converters are used in solar power systems, they change the current, which uses reacti...

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Bibliographic Details
Published in:Results in control and optimization Vol. 14; p. 100343
Main Authors: Smadi, Takialddin Al, Handam, Ahmed, Gaeid, Khalaf S, Al-Smadi, Adnan, Al-Husban, Yaseen, Khalid, Al smadi
Format: Journal Article
Language:English
Published: Elsevier B.V 01.03.2024
Elsevier
Subjects:
Artificial Intelligence (AI): Photovoltaic panel
Energy control
Fuzzy-neural network control
Management control
PV system
Management control
Artificial Intelligence (AI): Photovoltaic panel
PV system
Fuzzy-neural network control
Energy control
ISSN:2666-7207, 2666-7207
Online Access:Get full text
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Summary:Renewable energy systems, such as photovoltaic (PV) systems, have become increasingly significant in response to the pressing concerns of climate change and the imperative to mitigate carbon emissions. When static converters are used in solar power systems, they change the current, which uses reactive energy. A proportional-integral controller regulates active and reactive powers, whereas energy storage batteries enhance energy quality by storing current and voltage as they directly affect steady-state error. The utilization of artificial intelligence (AI) is crucial for improving the energy generation of PV systems under various climatic circumstances, as conventional controllers do not effectively optimize the energy output of solar systems. Nevertheless, the performance of PV systems can be influenced by fluctuations in meteorological conditions. This study presents a novel approach for integrating solar PV systems with high input performance through adaptive neuro-fuzzy inference systems (ANFIS). A fuzzy neural inference-based controller regarding energy generation and consumption aspects was designed and examined. This study examines the importance of artificial intelligence in facilitating continuous power supply to clients using a battery system, hence emphasizing its significance in energy management. Moreover, the findings demonstrated promising outcomes in energy regulation and management.
ISSN:2666-7207
2666-7207
DOI:10.1016/j.rico.2023.100343