Multi-objective Optimization of Hybrid Energy Systems Based on Life Cycle Exergy and Economic Criteria

The present study aims to develop a novel optimal design of hybrid energy systems based on exergy and lifecycle concepts using genetic algorithms. The model consists of both stand-alone and on-grid options with scenarios for exchanging energy with the grid. The objectives include cost minimization or benefit maximization primarily, and lifecycle exergy efficiency, i.e., cost as the sustainability index secondarily. This research considers renewable sources such as solar, wind, hydropower, and hydrogen production and storage in addition to conventional diesel generators. The optimization was performed subject to weather conditions and solar radiation profiles, demand, and environmental or economic aspects. Also, the model contains various modules such as water-heating, waste energy utilization, as well as the options of power exchange with the distribution network and injection of hydrogen produced from excess renewable sources into the gas network. The application was demonstrated in a case study, where specific demands and the climate of Tehran were assumed. The case study considers four scenarios, including standalone, completely on-grid, on-grid with a non-backup generator, and on-grid without an energy sale option. The first optimal objective, the levelized unit cost of energy for the standalone system, is $0.22 per kWh. Moreover, the second optimal objective, the lifecycle exergy cost, ranges from 1.93 to 4.13 in different grid-connection states.