Framework and Clustering Dashboard for Analysing Temporal-Based Parameters of Solar PV Output Model

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 tenyear
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.