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 framework's 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.