Robust management and optimization strategy of energy hub based on uncertainties probability modelling in the presence of demand response programs

The energy hub is considered one of the most important parts of the multi-carrier energy distribution systems. One of the major challenges facing the energy hub idea is the optimal distribution and management of energy based on renewable and non-renewable power generation resources in the presence of demand response programs and uncertainties. This study aims to present an optimal management and distribution model of energy based on uncertainties of probability modelling of renewable energy resources, uncertainties of electrical loads (electric vehicles (EVs)), operating and maintenance cost, cost modelling of greenhouse gas emissions, and electric and thermal demand response programs. Therefore, the proposed model is presented based on a robust optimization model and mixed-integer linear programming. Uncertainties in this research are divided into two categories; technical and economic. The technical part includes the uncertainties caused by renewable energy resources and EVs, simulated based on the Monte Carlo method and their probability distribution function. The economic part includes modelling the uncertainty caused by the price of electricity. The operation model and the objective function of the optimization problem are modelled using the demand response models based on peak shaving and load shifting techniques.