부산대학교 도서관

Abstract In this paper, the optimal operation of Energy hub (EH) based upon both demand and renewable energy resources (RESs) uncertainties is investigated. Here, an innovative scenario‐based energy hub energy management system (EH‐EMS) is proposed for simultaneous cost and emission reduction considering the abovementioned uncertainties. Moreover, a multi objective hybrid heuristic algorithm, the so‐called hBES‐MOGWO, is introduced for solving the proposed EH‐EMS, which is a combination of bald eagle search (BES) and multi objective gray wolf optimization (MOGWO) algorithms. The proposed EH consists of photovoltaic (PV), wind turbine (WT), boiler, heat storage (HS),combined heat and power (CHP) and multi‐carrier energy storage technology such as power to gas (PtG) technology, electric vehicles and heat storages. Flexible loads are also taken into account for reducing cost and emission by participation in demand response programs (DRPs). The optimization results demonstrate the effectiveness of the proposed hBES‐MOGWO algorithm. The simulation results illustrated that the total cost of EH‐EMS can be effectively reduced by installing energy storage systems and implementing DRPs. The results emphasize that considering uncertainties can lead to increase the operating costs and emission, while flexible loads participation in DRPs and PtG can reduce the aforementioned ones.