Probabilistic scheduling of power-to-gas storage system in renewable energy hub integrated with demand response program

Abstract Reliable energy supply is a significant challenge for the power system operators. The increase of emerging resources, as well as multi-carrier consumers in energy systems, lead to the integration of multi-carrier energy systems. The energy hub (EH) is one of the central infrastructures which smooths the combination and interdependency of various energy carriers to increase the efficiency and reliability. A novel technology, such as power-to-gas (P2G) storage, is a great option for achieving a renewable resources-based integrated energy system with high efficiency. The P2G storage is regarded as a viable energy storage approach to cover ever-increasing renewable energy resources variability in power system operations. The contribution of this paper is to present an optimal stochastic scheduling problem of EH integrated with P2G storage, combined heat and power (CHP) unit, wind power, boiler, electrical storage, and thermal storage to meet electrical, heat, and gas demands considering demand response program (DRP). The load shifting based DRP is applied on the electrical loads to reduce the operation cost of the EH. Also, the P2G storage system is used as a new resource that makes a connection between electrical and natural gas networks by converting the power to hydrogen and after that to natural gas through two processes including electrolysis and mechanization, respectively. A scenario-based stochastic approach is applied to handle the uncertainties related to the electrical loads, wind power, and electricity price. The objective of the proposed problem is to minimize the total operation cost of EH, which is modeled as a mixed-integer linear programming (MILP) problem model. The numerical results are implemented for different cases which demonstrate the effectiveness of the integration of the P2G based multi-carrier energy storage and DRPs on the operation cost of EH. The achieved results confirm the proposed approach by demonstrating the considerable reduction in operating cost of the EHS by approximately 7%.