Electrical, thermal and optical modeling of photovoltaic systems: Step-by-step guide and comparative review study. (February 2022)

• Record Type: Journal Article
• Authors: Gholami, Aslan; Ameri, Mohammad; Zandi, Majid; Gavagsaz Ghoachani, Roghayeh
• Is Part Of: Sustainable energy technologies and assessments. Volume 49(2022)
• Publication Date: 2022-02
• Subjects: Photovoltaic system -- Extraction methods -- Parameter modification -- Heat transfer mechanism -- Radiation tracking; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101711
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: Reviewed and classified applied assumptions and correlations for each model. Digressing from STC could results in more than 17% prediction error in some models. Proposed modifications to improve modeling accuracy up to 35% considering dust. Provided a state-of-the-art reference for modeling under any varying conditions. Analyzed the gaps and challenges and suggested future study recommendations. Abstract: The presented study conducted a substantial literature review regarding the electrical, thermal, and optical modeling of photovoltaic systems. All the main models suggested in the literature to predict a photovoltaic system's behavior were reviewed. The study performed a step-by-step investigation, comparison, and classification, followed by an in-depth and critical analysis of the state of the art. The diode-based equivalent electrical circuit models were selected for further investigations for electrical modeling. The models' unknown parameters, the corresponding extraction methods, and parameter modification methods were introduced and compared based on accuracy, computing costs, and applicability. It was found that neglecting the variation in environmental conditions could easily lead to considerable errors up to 17%. However, proper modifications such as considering dust impacts in a model may improve the prediction results up to 35%. The present analysis pointed out that for electrical modeling, parameters extraction continues to be a long-lasting topic. However, for optical and thermal modeling, the favorable research topic is the precise identification of heat transfer coefficient and heat transfer mechanisms. The reviewed documents were assessed critically to identify the research gaps and some directions for future research are proposed to cope with the remaining shortages.