Advanced Signal Processing Techniques for Monitoring East/West Oriented Solar Photovoltaic Systems: A Case Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F24%3A43930102" target="_blank" >RIV/60461373:22340/24:43930102 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/24:00378195 RIV/68407700:21730/24:00378195 RIV/70883521:28140/24:63584818

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10744544" target="_blank" >https://ieeexplore.ieee.org/document/10744544</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2024.3492017" target="_blank" >10.1109/ACCESS.2024.3492017</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Advanced Signal Processing Techniques for Monitoring East/West Oriented Solar Photovoltaic Systems: A Case Study

Popis výsledku v původním jazyce

Solar photovoltaic (PV) systems are increasingly recognized as crucial sustainable energy sources with diverse applications. Their implementation leverages rapid advancements in material engineering, communication systems, and computational intelligence tools. This paper focuses on selected mathematical methods for analyzing time series of power generated by PV systems, including numerical methods and algorithms for multichannel signal processing, digital filtering, and signal feature extraction. These methods monitor the characteristics of individual PV panels and identify their feature clusters. Specifically, it examines systems with east/west oriented photovoltaic panels, employing statistical methods and computational tools to analyze power signals, assess time and positioning data, evaluate symmetry coefficients, and apply machine learning tools to detect potential panel failures. Additionally, a general graphical user interface for data analysis is proposed. A detailed case study is presented, analyzing the distribution of selected features over time segments of a PV system comprising seven east-oriented and seven west-oriented panels, with data recorded over a selected set of days at a sampling rate of 15 minutes. The results reveal distinct and well-separated feature clusters for healthy PV panels. General conclusions underscore the effectiveness of signal processing tools in the statistical analysis of PV systems and the potential of feature clustering and symmetry estimation for evaluating disorders of system behaviour using communication technologies, data storage, and remote system monitoring.

Název v anglickém jazyce

Advanced Signal Processing Techniques for Monitoring East/West Oriented Solar Photovoltaic Systems: A Case Study

Popis výsledku anglicky

Solar photovoltaic (PV) systems are increasingly recognized as crucial sustainable energy sources with diverse applications. Their implementation leverages rapid advancements in material engineering, communication systems, and computational intelligence tools. This paper focuses on selected mathematical methods for analyzing time series of power generated by PV systems, including numerical methods and algorithms for multichannel signal processing, digital filtering, and signal feature extraction. These methods monitor the characteristics of individual PV panels and identify their feature clusters. Specifically, it examines systems with east/west oriented photovoltaic panels, employing statistical methods and computational tools to analyze power signals, assess time and positioning data, evaluate symmetry coefficients, and apply machine learning tools to detect potential panel failures. Additionally, a general graphical user interface for data analysis is proposed. A detailed case study is presented, analyzing the distribution of selected features over time segments of a PV system comprising seven east-oriented and seven west-oriented panels, with data recorded over a selected set of days at a sampling rate of 15 minutes. The results reveal distinct and well-separated feature clusters for healthy PV panels. General conclusions underscore the effectiveness of signal processing tools in the statistical analysis of PV systems and the potential of feature clustering and symmetry estimation for evaluating disorders of system behaviour using communication technologies, data storage, and remote system monitoring.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Svazek periodika

12

Číslo periodika v rámci svazku

Dec

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

165042-165049

Kód UT WoS článku

001354547300001

EID výsledku v databázi Scopus

2-s2.0-85208669750