Stochastic day-ahead unit commitment scheduling of integrated electricity and gas networks with hydrogen energy storage (HES), plug-in electric vehicles (PEVs) and renewable energies

This study investigates stochastic day-ahead unit commitment scheduling of integrated natural gas and power systems that consist of a non-gas-fired unit (NGFU), gas-fired unit (GFU), combined heat and power (CHP) unit, and renewable production units considering AC power flow. Natural gas storage is incorporated into the problem to support the gas network during peak natural gas demand hours by reducing pipeline congestion. Moreover, integrating hydrogen energy storage (HES) along with new flexible technologies, such as power to gas (P2G) system and demand response program (DRP) is proven to reduce total operation cost by facilitating renewable energy dispatch and shifting peak load demand to off-peak hours. A sensitivity analysis is carried out to evaluate the impact of thermal load increment on the operation of the CHP unit as its thermal and electrical output are interrelated variables. A residential plug-in electric vehicle (PEV) charging station is integrated into the problem to observe its impact on the operation of the networks, as PEVs introduce a new unplanned and uncertain load to the system. Furthermore, the sensitivity of the problem for PEV penetration is investigated. The uncertain parameters of the problem are electrical load demand, PEVs? load demand, and wind power. Eventually, the proposed mixed integer non-linear problem (MINLP) is applied to several case studies involving an integrated 6bus power system and 6-node gas network.