Load-Data Imputation and Economic Feasibility Analysis of an Academic Institution

This study focuses on utilizing linear regression for imputing missing data in the context of electrical load profile analysis. Specifically, the study aims to utilize complete time series electric load profile data from the Indian Institute of Technology Guwahati (IITG) campus in Assam, India. The collected data is subjected to a linear regression analysis to impute missing values. The imputed data is then utilized for an economic feasibility analysis of solar photovoltaic (SPV) systems, emphasizing an increased fraction of renewable energy. The imputed data is further utilized for an economic feasibility analysis of solar photovoltaic (SPV) systems with an increased fraction of renewable energy. The analysis, conducted using the HOMER-Pro software, provides valuable insights into the economic viability and sustainability implications of integrating higher fractions of renewable energy in the energy mix of academic institutions. The findings of this study contribute to the development of accurate and comprehensive load profile datasets and highlight the potential benefits of implementing SpV systems with increased renewable energy fraction (REF).