Optimal planning and operation of energy hub by considering demand response algorithms and uncertainties based on problem-solving approach in discrete and continuous space

Abstract

• Energy hub optimal planning and operation based on stochastic-probability indices. • Implement and evaluate the impact of DR/IDR algorithms. • Load uncertainty analysis and probability behaviour of renewable energy sources. In this research, the two-level structure of optimal planning and operation of the energy hub (EH) based on demand uncertainty and renewable energy resources (RES) is presented. The optimal planning based on stochastic-probability models is presented at the primary and optimal operation based on stochastic-probability models is also presented at the secondary level. The proposed method is planned based on the problem-solving approach in continuous and discrete space. The optimal planning objectives include determining the optimal capacity of EH equipment and minimizing investment costs. Optimal operation objectives are also planned and formulated based on minimizing EH operation cost, reducing greenhouse gas emissions, increasing RES utilization based on stochastic-probability modelling, and examining the demand response/integrated demand response (DR/IDR) effect. The DR programs implementation causes a reduction of 14.3% of the EH total cost, and the IDR programs implementation also causes a reduction of 16.56% of the EH total cost. The use of the proposed optimal two-level model, in addition to efficiency in different operation scenarios, has also reduced the calculation time. The optimization problem is solved based on Mixed Integer Linear Programming (MILP) and Binary Real-Coded Hybrid Genetic Algorithm (HRBC-GA).