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A distributionally robust optimization based gas-electricity model is established.

A three-level adjustable robust optimization model is developed for comparison.

A data-driven distributionally robust optimization method is used for comparison.

The effect of natural gas system on the reserve in power system is analyzed.

The impact of several related factors on the final solutions are investigated.


As the interdependency between natural gas system and power system is significantly close and the integration of renewable energy with uncertainty and volatility greatly increased in the last decades, the operation security and economics of the gas-electricity integrated energy system has attracted growing concerns. A two-stage distributionally robust optimization (DRO) model is proposed to study the coordination optimization scheduling for this multi-energy coupled system considering wind power uncertainty. Integrating the advantages of stochastic programming and traditional adjustable robust optimization (ARO), DRO aims to minimize the expectation of the operation cost under the worst-case distribution over an ambiguity set. The operation constraints of the above two energy subsystems are fully considered, moreover, the feasibility check subproblem for the reserve capacity configuration by gas-fired units is built. As a result, the DRO model is solved in a master-subproblem framework. A case study is implemented on a 6-bus power system with a 7-node natural gas system to demonstrate the superiority of the proposed DRO model compared to the existing ARO and data-driven DRO models. Furthermore, the modified IEEE 24-bus system with a 10-node gas system is used to verify the effectiveness and practicability of the proposed model.


Distributionally robust optimization

Wind power uncertainty

Gas and electricity integrated system

Coordination operation

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