Engineers and scientists are increasingly interested in clean energy options to replace fossil fuels in response to rising environmental concerns and dwindling fossil fuel resources. There has been an increase in the installation of renewable energy resources, and at the same time, conventional energy conversion systems have improved in efficiency. in this paper, several multi-generation systems based on geothermal energy are modeled, assessed, and optimized with an organic Rankine cycle and proton-exchange membrane electrolyzer subsystem in five different arrangements. Based on the results, the evaporator mass flow rate and inlet temperature, turbine efficiency, and inlet temperature are the most influential parameters on system outputs, namely, net output work, hydrogen production, energy efficiency, and cost rate. In this case study, the city of Zanjan (Iran) is selected for a case study, and the results of system energy efficiency for changes in ambient temperature are examined during the four seasons of the year. To determine the optimal values of the objective functions, energy efficiency, and cost rate, NSGA-II multi-objective genetic algorithm is employed, and a Pareto chart is derived as a result. A system's irreversibility and performance are gauged by energy and exergy analyses. At the optimum state, the best configuration yields an energy efficiency and cost rate of 0.65% and 17.40 $/h, respectively.