Distributionally robust coordination optimization scheduling for electricity-gas-transportation coupled system considering multiple uncertainties

The advance of the dynamic wireless charging technique for electric vehicles makes the electrified transportation system to be the development trend. On the other hand, the interdependency between electricity and natural gas systems has been intensified increasingly with the expansion of renewable energy. This creates a critical motivation to formulate the coordination operation model for the integrated electricity, gas and transportation system. In this context, a distributionally robust optimization (DRO) model is proposed considering multiple uncertainties comprehensively for the multi-energy coupled system. Specifically, the traffic flow uncertainty is transformed as the charging load uncertainty while the gas consumption uncertainty by gas-fired units is regarded as the reserve capacity configuration of units. Furthermore, the uncertainties of wind power and charging load are described as an ambiguity set incorporating the distribution information. Then the master-subproblem framework is developed, and a combination of the Benders decomposition and the transformation technique for bi-level sub-problem is implemented for solving this model. Simulation results indicate that DRO has saved the operation cost by 5.06% and 5.11% for the 6-bus and 24-bus systems compared with the traditional robust optimization model, which is beneficial for system decision-makers to achieve a balance between the reliability and economy in practice.