Improving Economic and Reliability Performance in Hybrid 2 Renewable Energy Systems for Isolated Buildings Using 3 Modified Smell Agent Optimization

This paper presents the optimal sizing of a hybrid renewable energy system (HRES) for 12 an isolated residential building using a modified Smell Agent Optimization (mSAO). The paper 13 introduces a time-dependent approach that adapts the selection of the original SAO control param-14 eters as the algorithm progresses through the optimization hyperspace. This modification addresses 15 issues of poor convergence and suboptimal search in the original algorithm. Both the modified and 16 standard algorithms were employed to design an HRES system comprising photovoltaic panels, 17 wind turbines, fuel cells, batteries, and hydrogen storage, all connected via a DC-bus microgrid. The 18 components were integrated with the microgrid using DC-DC power converters and supplied a 19 designated load through a DC-AC inverter. Multiple operational scenarios and multi-objective cri-20 teria, including techno-economic metrics such as Levelized Cost of Energy (LCOE) and Loss of 21 Power Supply Probability (LPSP), were evaluated. Comparative analysis demonstrated that mSAO 22 outperforms the standard SAO. Simulation results highlighted that the PV-wind turbine-battery 23 system achieved the best economic performance using SAO and mSAO. The mSAO reduced the 24 total annual cost (TAC) to approximately $614,288.8 and the levelized cost of energy (LCOE) to 25 (0.6868477489) $0.013/kWh, compared to the SAO which obtained a TAC, $615217 and the LCOE, 26 (0.7108991366) $0.077/kWh respectively.