Stochastic framework for day-ahead scheduling of coordinated electricity and natural gas networks considering multiple downward energy hubs

Abstract

The integrated operation of electricity and gas networks in the presence of downward energy hub networks leads to the development of smarter and more environment-friendly networks. This paper presents an optimal model for the day-ahead scheduling of electricity and natural gas networks by considering three downward energy hubs and a power-to-gas system (P2G). The system studied in this paper consists of a 33-bus distribution electricity network and a 14-node gas network. Moreover, the uncertainties of the electrical, cooling, heating loads, the renewable energy sources (RES's) output power, and price are taken into account to study their effects on the scheduling results. In the proposed model, first, each hub performs its optimal day-ahead scheduling and sends it to the ISO. Afterward, the ISO performs the scheduling of electricity and natural gas networks considering the optimal schedule of each hub. The final problem is modeled as a mixed-integer non-linear programming (MINLP) problem and is solved using the DICOPT solver in GAMS software. According to our analysis of the results, the proposed model reduces the operation costs by 5.1 and 4.8 percent in the deterministic and stochastic modes, respectively. Moreover, our analysis of the results in the contingent event reflects the loss of about 1429kW of the load in the absence of the P2G system.