Tanoto, Yusak and Budhi, Gregorius Satia (2023) Framework and Clustering Dashboard for Analysing Temporal-Based Parameters of Solar PV Output Model. In: 2023 11th International Conference on Smart Grid and Clean Energy Technologies (ICSGCE), 15-10-2023 - 15-10-2023, Kuala Lumpur - Malaysia.
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Abstract
This paper presents a framework and dashboard designed to analyze and present long-term hourly temporal-based parameters of a solar photovoltaic (PV) output model. The framework uses time series and artificial intelligence-based methods to analyze direct and diffuse irradiance, as well as temperature data, while the web-based dashboard aims to present the characterization and prediction results of these parameters. The frameworks first part clusters the three parameters and solar PV output over a ten-year period and beyond, focusing on the Java-Bali region in Indonesia. The paper emphasizes the importance of a dashboard that visualizes areas across regions resulting from the k-means clustering analysis. This framework provides vital insights into the potential of solar photovoltaics, specifically regarding spatial issues that may influence investment decision making.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Link Scopus author: https://www.scopus.com/authid/detail.uri?authorId=57202082032 |
Uncontrolled Keywords: | framework, hourly temporal, dashboard, solar photovoltaic, machine learning |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Industrial Technology > Electrical Engineering Department |
Depositing User: | Admin |
Date Deposited: | 08 Mar 2024 20:25 |
Last Modified: | 19 Apr 2024 23:55 |
URI: | https://repository.petra.ac.id/id/eprint/20906 |
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