Energy Scheduling in the Multiple Energy System with Optimal Operation of the Responsive Loads

In this research, an approach is presented for the optimal scheduling of a smart energy Hub system with multiple objectives in the day ahead. The objectives include minimizing emission pollution and operation costs on the generation side, reducing the loss of energy supply probability on the demand side, and minimizing the deviation of electrical and thermal loads from their optimal profiles in the day ahead. To achieve the third objective of flattening the electrical and thermal demand profiles, a Demand response strategy is proposed, which involves the optimal shifting of electrical and thermal shiftable loads. Additionally, stochastic modelling of renewable energy sources and energy loads using the Monte Carlo technique is conducted. The proposed approach utilizes the epsilon-constraint method to obtain nondominated Pareto solutions for the objectives. Finally, several case studies are performed to validate the proposed approach.