A sustainable multi-objective optimization model for the design of hybrid power supply networks under uncertainty

In today's industrialized world, the scarcity of fossil fuels and the adverse biological effects resulting from fossil fuel consumption, on one hand, and the increasing population and energy demands, on the other hand, have posed significant challenges to the sustainable development of societies. This research has developed an optimization model for designing a hybrid energy supply network that simultaneously addresses economic, environmental, and social objectives. The economic goal of the model is to maximize after-tax company profits, while the environmental objective is to minimize greenhouse gas emissions, and the social objective is to maximize social profit. The optimal solution for individual goals reveals that the gas field is active and beneficial for economic objectives, renewable plants are active for environmental goals, and for social objectives, the gas field, combined heat and power (CHP), and wind power are active. The model is solved using the augmented epsilon-constraint method, and the resulting Pareto optimal solutions are provided to decision-makers. To account for real-world complexities, uncertainties in key model parameters have been considered. Validation for this study has been conducted using data from Iran, an energy exporter to Pakistan.