Rapid development of power-to-gas technology provides a potential solution for virtual power plants (VPP) to achieve near-zero carbon emissions. In this paper

a bi-level hybrid stochastic/robust optimization model is proposed for low-carbon VPP day-ahead dispatch considering uncertainties from renewable generation and market prices. First

Karush-Kuhn-Tucker optimality conditions are employed to convert the bi-level model to a single level one. Next

the single level problem is decomposed into a master problem in the base case and several subproblems in extreme cases

which can then be solved by using the column-and-constraint generation algorithm iteratively. Numerical results indicate the proposed approach can effectively satisfy system operation constraints including the carbon emission limit

enhance computational efficiency and algorithm robustness compared with the stochastic method

and improve VPP revenue compared with the robust method.