A robust bi-level optimization framework for participation of multi-energy service providers in integrated power and natural gas markets

This paper presents a bi-level scheduling model for a new energy system under the concept of multi-energy service providers (MESPs) to participate in the integrated power and natural gas market (IPNGM). While the presented bi-level model takes full consideration of the unit commitment constraints of the power network and line pack constraints of the gas network into consideration at the lower level, the MESPs minimize the cost of purchasing power and natural gas by operating energy storage systems as well as the demand response program (DRP) as flexible technologies at the upper level. In order to solve the bi-level problem, an iterative-based two-step algorithm is developed. Moreover, since the MESPs cannot accurately predict other participants in the IPNGM, especially renewable energy sources (RESs), the power price determined by IPNGM is considered an uncertain parameter, and a robust optimization (RO) method is employed to capture this uncertainty. The proposal is formulated as a mixed-integer linear programming (MILP) and carried out on the IEEE 6-bus power system integrated with the 6-node natural gas network and considering one MES using the CPLEX solver in the general algebraic modeling system (GAMS) environment. Further, to show the model flexibility, simulation results are extended to the IEEE 118-bus power system integrated with the 10-node natural gas network by considering six MESs. The obtained results verified the effectiveness of the model by reducing the cost of the purchased power and natural gas up to 4.39% by employing flexible energy sources.