Budget-constrained optimal and equitable retrofitting problems for achieving energy efficiency

Abstract

Retrofitting is an important step in reducing the energy footprint of the existing building stock and providing long-term savings for households. Realizing the potential benefits of retrofit strategies at granular spatial level requires detailed data in terms of the building stock in a region, household socioeconomic and demographic attributes, and household-level energy demands. In this paper, we present a two-step optimization problem using agent-based models at household level for maximizing energy savings through retrofitting using simple linear programming. We also investigate the effect of household behaviors in retrofitting decisions at the appliance level. Additionally, we explore different investment strategies such as grant+loan and green revolving fund (GRF) for residential settings. Our results from the two-step optimization model reveal a better utilization of the retrofitting cost ( lesser) yielding higher proportional energy savings. GRF scheme generated a return on investment of 75.6% under the upfront investment of the corpus.