Sayyad Nojavan

Among different renewable energies, the sun as an endless source of energy has been the focus of many researchers worldwide. The use of solar radiation energy in conventional power generation systems can play an important role in reducing fuel consumption and environmental pollution. The importance of this energy has been increased when we need to supply the load demand, especially in desert-like places. The main objective of this research is to propose a new optimal hybrid solar/diesel/battery system to cover the demand load of a rural part in the Gobi Desert in China. The main objectives for optimization are the loss of load probability, CO2 emissions value, and the annualized cost of the system. Here, the ε-constraint method is adopted to simplify the multi-objective problem into a single objective problem. The optimization of the problem is performed by a developed version of the elephant herd optimization algorithm and the system sensitivity analysis has been analyzed on the parameters. Simulation results show that the proposed method can provide a reliable supplement for the load demand such that the PV penetration has a prominent impact by 97.9% of the costs. The results also present that the emitted CO2 gas by the proposed cEHO algorithm by 1735 kg/year is the minimum value compared with the PSO-based optimal system and HOMER software results. The initial capital cost of the system is also achieved 48,680 $ that specifies less value than the net present cost.