In this paper, a Genetic Algorithm (GA) is utilized to implement a tri-objective design of a grid independent PV/Wind/Split-diesel/Battery hybrid energy system for a typical residential building with the objective of minimizing the Life Cycle Cost (LCC), CO2 emissions and dump energy. To achieve some of these objectives, small split Diesel generators are used in place of single big Diesel generator and are aggregable based on certain set of rules depending on available renewable energy resources and state of charge of the battery. The algorithm was utilized to study five scenarios (PV/Battery, Wind/Battery, Single big Diesel generator, aggregable 3-split Diesel generators, PV/Wind/Split-diesel/Battery) for a typical load profile of a residential house using typical wind and solar radiation data. The results obtained revealed that the PV/Wind/Split-diesel/Battery is the most attractive scenario (optimal) having LCC of $11,273, COE of 0.13 ($/kWh), net dump energy of 3MWh, and net CO2 emission of 13,273kg. It offers 46%, 28%, 82% and 94% reduction in LCC, COE, CO2 emission and dump energy respectively when compared to a single big Diesel generator scenario.