Enhancing energy hub efficiency through advanced modelling and optimization techniques: A case study on micro-refinery output products and parking lot integration

Abstract

A new model of energy carriers (micro-refinery output products) in the concept of an energy hub is presented. In addition, in the presented model, the effect of different models of parking lot in an energy hub is analyzed. In this study, the uncertainty of the number of electric vehicles was modeled using the Monte Carlo method, and then considering the same conditions, the uncertainty of the number of electric vehicles was calculated using the Probability-Possibility hybrid method. In addition, the study uses a scenario-based approach to address uncertainties related to multi-carrier energy demand and multi-carrier energy prices. In the present paper, ensuring water demand is of great importance, which is why the proposed energy hub structure of a sea desalination unit and sour water treatment that is extracted from the micro refinery output was analyzed. The optimization model presented in this paper for the energy hub is a complex integer linear programming (MILP) that is solved using a CPLEX solver in the GAMS environment. The results show that the use of the Probability-Possibility method resulted in an 8 % reduction in the final energy supply cost in the energy hub compared to the Monte Carlo method.

Keywords

• Energy hub
• Micro refinery
• Probability-possibility
• Parking lot
• Sour water