Aggregate Flexibility of Virtual Power Plants With Temporal Coupling Constraints

Abstract

The virtual power plant (VPP) provides an efficient way to manage a bunch of distributed energy resources (DERs). In order to participate in the system operation and power market as a whole, the estimation of VPP power flexibility is indispensable. However, the temporal coupling constraints make it intractable to aggregate the power flexibility directly. In this paper, we formulate the flexibility evaluation problem as a chance constrained optimization model incorporated the randomness of renewables. To make it tractable, the evaluated flexibility is represented by the combination of a virtual generator and a virtual battery which is decomposed by a robust optimization algorithm. Then, a novel high-dimensional polytope based bound shrinking method is proposed to estimate the parameters of the virtual generator and virtual battery. The numerical test results show the proposed method obtain much more precise results with lower conservativeness than those of existing methods. The disaggregation feasibility of the evaluation results is also verified.