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The concept of VES provides a new way that utilizes the existing resources and devices to achieve functions similar to an energy storage system (ESS) without introducing physical energy storage devices. By adjusting the loads of energy-intensive devices or the output of power generation resources in the existing self-supply entity (SSE), VES can realize power transfer functions and provide regulation services to power systems according to the scheduling strategies. In this context, this paper mainly discusses the economic dispatch problem with VES under uncertainties and proposes a novel multi-stage method while guaranteeing nonanticipativity and multi-stage robustness. Firstly, a conceptual single-level multi-stage robust economic dispatch model is proposed subject to the systematic constraints of VES. To make the economic dispatch model tractable with solution feasibility guaranteed, a specific feasible region for dispatch variables is defined based on the constraints’ structure. Based on the feasible region, the original model can be transformed into a mixed integer linear programming (MILP) problem and can be implemented via a rolling horizon. Numerical results in a real area illustrate the effective performance of the proposed method. Note to Practitioners—This article is motivated to realize the function of the storage facility by scheduling the existing self-supply entity, defined as virtual energy storage (VES). And the scheduling method can be applied to deal with other multi-stage robust problems with the same constraints’ structure. One of the main challenges in scheduling systems with VES under uncertainty is to decouple the ramp-rate constraints of thermal units and VES as well as the nonlinear coupling constraints of VES. To make the problem tractable with solution feasibility guaranteed, two groups of nonanticipative and multi-stage robust constraints are introduced based on the constraints’ structure. An efficient method is then established based on the feasible condition and the method performs better than the existing methods. The proposed method allows the decision maker to obtain the economic scheduling decisions of the VES more efficiently.