Novel inverse heat transfer technique for estimation of properties and location-specific process parameters of roof-mounted solar PV plants. (1st October 2020) - Vaka, Ananda S.; Talukdar, Prabal
Highlights: An improved dynamic thermal model for a roof-mounted solar PV module is presented. A novel method to predict the properties and location-specific process parameters. Salp Swarm Algorithm based IHTP technique with limited temperature data. Actual experimental data is used to demonstrate the proposed methodology. This model can be used to predict the module temperature variation and dust deposition. Abstract: Accurate quantification of properties and location-specific process parameters of roof-mounted solar PV power plants are essential for design and development of the power plant as well as for operation and maintenance and capacity improvement/reclaim of the power plant. In this work, a novel inverse heat transfer technique based on an efficient optimization method, Salp Swarm Algorithm (SSA), has been used to estimate the unknown properties and process parameters. This methodology uses limited on-site plant recorded data and consumes relatively less computational and experimental resources. Numerical and experimental analysis is carried out for representative periods and for representative days. The observed results indicate that the location-specific process parameters can be estimated with reasonable accuracy and these results can be used to estimate the module temperature which in turn is used for accurate estimation of power generated using temperature coefficients and healthiness of the system. The proposed methodology is simple to implement, uses only limited experimental data and is recommended for studies aimed towards estimating the unknown properties and process parameters.