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Automation of technological and business-processes
Article . 2025 . Peer-reviewed
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EFFICIENT DATA STORAGE SYSTEMS FOR MONITORING AND OPTIMIZING THE PERFORMANCE OF PHOTOVOLTAIC PANELS

Authors: Filip Batalov; Antonio Karaganov;

EFFICIENT DATA STORAGE SYSTEMS FOR MONITORING AND OPTIMIZING THE PERFORMANCE OF PHOTOVOLTAIC PANELS

Abstract

Abstract The advancement of photovoltaic (PV) systems has led to the generation of a massive volume of data related to electricity production, which continues to grow at an exponential rate. This data encompasses information on output power, voltage, frequency, and other electrical parameters, as well as environmental conditions, all of which are recorded in real time. Effective management of this data is essential for optimizing energy production and maintaining both the performance and functionality of the system. However, traditional centralized data storage methods often prove to be insufficiently flexible and secure for the effective management and protection of data, especially as photovoltaic power plants grow in size and generate increasingly larger volumes of information. Blockchain technology presents a promising alternative for storing data related to the generation and operational status of photovoltaic installations. Through decentralized storage, it enhances the reliability, transparency, and security of the data. Unlike traditional databases, blockchain is immutable and distributed, allowing for secure storage of information across multiple nodes while preserving its integrity and traceability—even in the event of cyber threats or system failures.

Keywords

blockchain, T59.5, data protection, Automation, data storage, photovoltaic panels, decentralized storage, monitoring systems, performance optimization, energy efficiency

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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