A Stochastic Multi-Objective Operation Approach of Multi-Energy Hubs and Parking Lots of PEVs in Smart Microgrids

Energy hubs (EH) could provide reliable, efficient, and flexible operation in terms of multiple energy carriers such as electrical, thermal, and gas. However, when it comes to developing an optimal operational scheme, the interaction of these different energy sectors, along with the uncertainty associated with renewable energy sources (RES) and the driving patterns of plug-in electric vehicle (PEV) owners, would pose a challenge. Accordingly, this paper proposes a stochastic seasonal multi-objective optimal operation scheduling scheme for four EHs incorporated into the IEEE-69 system. Moreover, the model investigates the optimal charging and discharging of four parking lots connected to the same system, taking into consideration the stochastic nature of the PEVs. The price-based demand response has also been addressed in this work. Mainly, the aim is to reduce the operation costs and the generated emission amounts. The multiobjective artificial hummingbird algorithm (MOAHA) has been utilized, and the Pareto optimal front has been employed to find the best-compromised solution out of a set of non-dominated ones. Two different case studies have been investigated, and the simulation outcomes confirmed the effectiveness of the proposed approach with 26.62% and 91.92% reductions achieved in operation cost and emission amounts, respectively.