Abstract

The virtual power plant (VPP) can aggregate massive, dispersed, and heterogeneous distributed energy resources (DERs) and provide an effective energy management way for an active distribution system (ADS). In this paper, three parameters of upper and lower limits of active power output, ramping, and discharging energy is used to describe the aggregate flexibility of VPP. Based on this, a two-stage robust optimization (RO) model with dispatch instructions (DI) from the superior power grid (SPG) as uncertainty variables was constructed. Considering that the range of DI from the SPG changes during the iteration of the column and constraint generation (C&CG) algorithm, a position set is proposed to record the boundary information of the uncertain set of DI issued by the SPG when the sub-problem (SP) finds the worst scenario in each iteration, and the corresponding constraints are added to the master problem (MP). For the solution of SP, the bilevel max-min model is firstly transformed into a single-level bilinear programming (BLP) model by the duality theory and then solved by the concave-convex process (CCP) iterative method. Compared with transforming the BLP problem to a mixed integer programming (MILP) problem based on Karush-Kuhn-Tucker (KKT) condition, it can not only meet the engineering accuracy but also greatly save the solution time. Finally, the effectiveness of the proposed model and algorithm was verified on a modified IEEE 33-bus system.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call